Alternatives to Tragentics

Opal Zero serves as a governance platform for AI agents that provides just-in-time access management by cataloging every agent and linking it with a responsible owner, evaluating access requests, and implementing decisions through the existing MCP gateway. This comprehensive solution allows organizations to maintain a unified inventory across various identity providers and AI platforms, including Okta, Entra, Anthropic, OpenAI, Bedrock AgentCore, and Cursor, revealing the permissions each agent holds and their respective ownership. The Risk Center highlights access that may be misaligned with intended use, unassigned, or excessive, directing concerns to the relevant owner while offering immediate corrective measures. Paladin assesses requests against established policies and contextual information, pinpoints the least-privileged access routes, adheres to ownership boundaries, and elucidates the rationale behind each resolution. By analyzing real user behavior, Policy Insights uncovers instances of redundant access and suggests enhancements to access policies, moving beyond sporadic fixes. Furthermore, Gateway Enforcement ensures that approved access decisions are implemented as specific, temporary policies within the existing gateway infrastructure, thereby fostering a more secure and organized environment for managing AI agents.

Flint AI serves as a local-first and framework-agnostic AgentOps command-line interface designed to assist developers in assessing the reliability of AI agents prior to their deployment in production environments. By executing the command flintai scan, users can evaluate Python source code for various issues such as security flaws, misconfigurations, and inadequate safety measures, while also employing AI reasoning to filter out potential false positives. Additionally, the command flintai eval tests a running agent by sending both functional and adversarial prompts, grading its responses against over 35 established criteria, which encompass aspects like factual accuracy, adherence to instructions, and resilience against prompt injections and jailbreak attempts. Each evaluated agent is assigned a reliability score, with the results linked to the OWASP Agentic Security Initiative risk categories ASI01 through ASI10 and severity assessed via CVSS v4.0 metrics. Flint AI is compatible with several agent frameworks and SDKs, including Claude Agents SDK, LangChain, CrewAI, Anthropic SDK, OpenAI SDK, MCP servers, and AutoGen, ensuring a broad range of applications in the development ecosystem. Furthermore, this versatile tool not only enhances the security and quality of AI agents but also streamlines the evaluation process, ultimately fostering greater confidence in AI deployment.

Snapper serves as a comprehensive security platform for AI agents, aimed at ensuring thorough governance and protection for organizations that utilize AI across various applications, networks, and systems. It implements runtime enforcement by scrutinizing every action an agent takes, such as tool interactions, API calls, and data access requests, prior to execution, utilizing a multi-layered policy-driven rule engine. Additionally, Snapper provides a holistic view of AI activity by analyzing network traffic, browser usage, DNS queries, and running processes to uncover unauthorized tools and hidden AI applications. It also proactively intercepts outgoing large language model requests via SDK wrappers and a network proxy, allowing it to assess, redact, and document sensitive information in real time. Enhancing its security features, Snapper possesses sophisticated threat detection mechanisms that can recognize prompt injection tactics, exploit chains, unusual behaviors, and complex attack patterns, leveraging behavioral baselines, kill chain analysis, and a composite trust scoring system for robust protection. Ultimately, Snapper represents a critical asset for organizations seeking to navigate the risks associated with AI deployment while maintaining operational integrity.

AgentShield is an innovative identity platform designed to authenticate both human users and AI agents representing them. It allows organizations to verify an agent's identity, confirm the authorization from the individual behind the agent, and assess the agent's reliability, all through user-friendly APIs and JavaScript integrations. This platform also features capabilities for identifying agent interactions on websites and implements identity and permission validations for both agent-to-agent and agent-to-service communications, adhering to the open Model Context Protocol Identity (MCP-I) standards. Additionally, with the KYA feature, companies can effectively oversee agent identities and their permissions, establish audit trails, automate workflows, and apply precise access controls for autonomous systems. This comprehensive approach not only safeguards against the misuse of digital identities but also promotes clarity when AI systems operate on behalf of users, ultimately enhancing trust in digital interactions. As technology evolves, maintaining such robust security measures becomes increasingly crucial for organizations navigating the complexities of digital identity management.

Mountain Theory controls what autonomous AI agents can do. Every action an agent is about to take is checked against your rules before it runs, and comes back ALLOW, HOLD or BLOCK. An agent that works around a block is stopped on the workaround. An agent that drifts off its task is caught. New bad behavior is stopped the day it appears, with no new rule written. Personal data is kept from leaving your environment, and instructions hidden in emails and documents are blocked. Rules are plain English, so changing one takes no code. Every decision is logged for your auditor. It works with any AI you already use, in your environment or the cloud. Our recorded tests are published with the misses included.

AIM Intelligence is a comprehensive AI security platform designed to maintain control over AI systems as they make decisions, invoke APIs, and perform actions within actual business environments. It proactively defends against potential threats to AI before malicious actors can exploit vulnerabilities, implementing real-time guardrails to ensure that every agent adheres to corporate policies. The platform offers an array of integrated solutions, including automated AI red teaming, immediate guardrail enforcement, and consulting on security frameworks, which assist organizations in navigating intricate AI risks throughout both development and production phases. Stinger enhances the process of AI vulnerability detection by simulating countless attack scenarios, facilitating extensive agentic red teaming beyond mere prompt-level threats, and conducting tests across a variety of modalities such as text, image, audio, video, and physical AI, while also allowing for tailored vulnerability assessments based on business logic. Meanwhile, Starfort provides real-time enforcement of AI guardrails by identifying and safeguarding sensitive information, including personally identifiable information (PII) and trade secrets, while also regulating unusual API requests made by autonomous agents. By combining these elements, AIM Intelligence equips organizations with the tools necessary to maintain a secure and compliant AI environment.

Harden AIF serves as a security platform specifically designed for AI coding agents, ensuring agent endpoint security by assessing tool calls prior to execution based on the developer's intent, session context, organizational policy, and the potential impact of the action proposed. This platform effectively safeguards against threats such as harmful commands, unauthorized access, accidental data transfers, exposure of sensitive information, misuse of privileges, and other risky actions undertaken by agents. By allowing legitimate operations to proceed without disruption, it can also safely redact sensitive information during supported workflows while preventing actions that deviate from the developer's intent or exceed their authority from executing. Harden AIF is compatible with a variety of widely used coding agents and development tools, including Claude Code, Codex, Cursor, Antigravity CLI, Kiro, Hermes, and OpenClaw, thus offering a uniform security framework throughout the agent ecosystem. This comprehensive approach not only enhances security but also fosters a safer environment for developers working with AI technologies.

AI Security Guard is a comprehensive solution for safeguarding autonomous AI systems, featuring a protective SDK, versatile product tools, educational resources, and pioneering research focused on the future of agentic technology. The Protection SDK serves as a user-friendly API wrapper, designed to defend AI agents against vulnerabilities such as jailbreaks, prompt injection, and other potentially damaging content before it can impact your models. Powered by this API, AgentGuard360 actively monitors AI interactions in real time, ensuring that harmful content is intercepted before it can reach your agents; this tool offers dual-layer content scanning, supply chain security, and device fortification, all while prioritizing user privacy by keeping data local unless premium analysis is requested. Moreover, the platform is committed to advancing knowledge through original research that explores the implications of autonomous AI, addressing critical topics related to security, privacy, and safety, including insightful reports such as "Shipping the Future." This holistic approach not only enhances the protection of AI but also contributes to a broader understanding of the challenges and opportunities that lie ahead in the realm of autonomous technology.

Peta serves as an advanced control plane for the Model Context Protocol (MCP), streamlining, securing, governing, and overseeing how AI clients and agents interact with external tools, data, and APIs. This platform integrates a zero-trust MCP gateway, a secure vault, a managed runtime environment, a policy engine, human-in-the-loop approvals, and comprehensive audit logging into a cohesive solution, enabling organizations to implement nuanced access controls, safeguard raw credentials, and monitor all tool interactions conducted by AI systems. At the heart of Peta is Peta Core, which functions as both a secure vault and gateway, encrypting credentials, generating short-lived service tokens, verifying identity and compliance with policies for each request, managing the MCP server lifecycle through lazy loading and auto-recovery, and injecting credentials during runtime without revealing them to agents. Additionally, the Peta Console empowers teams to specify which users or agents can access particular MCP tools within designated environments, establish approval protocols, manage tokens, and review usage statistics and associated costs. This multifaceted approach not only enhances security but also fosters efficient resource management and accountability within AI operations.

Enkrypt AI is an AI security and compliance platform built to protect generative AI applications, autonomous agents, models, data, and AI infrastructure. It provides security agents and controls for detecting vulnerabilities, preventing threats, continuously monitoring AI systems, and automating compliance processes. Enkrypt AI's red teaming capabilities dynamically generate use-case-specific attacks that adapt during testing to uncover security, safety, and brand risks that static evaluations may miss. The platform addresses threats including prompt injection, jailbreaking, data leakage, model inversion, adversarial attacks, policy violations, hallucinations, model drift, bias, toxic content, deceptive behavior, and unmonitored agent actions. Real-time guardrails inspect AI interactions and can stop threats as they occur while continuously adapting based on prompts and observed activity. Monitoring capabilities provide ongoing visibility into AI risk and compliance so organizations can identify issues, track protection effectiveness, and maintain evidence for audits. Enkrypt AI can translate internal organizational policies and external regulatory requirements into automated guardrails to reduce manual compliance work. Its product portfolio includes Agent Red Teaming, Agent Guardrails, an Agent Policy Engine, AI Data Risk Audit, MCP Scanner, and MCP Gateway, with solutions for customer-facing agents, frontier models, third-party AI risk, AI compliance, MCP security, and secure AI development. The company also maintains an LLM Safety Leaderboard that continuously red teams and benchmarks more than 200 AI models to help organizations evaluate model security and safety.

Mindgard is an automated AI red teaming and offensive security platform purpose-built for AI systems and agents. It continuously red teams models, agents, and applications to find the vulnerabilities most likely to cause a breach, validates whether guardrails and controls hold, and shows security and engineering teams how to close each gap. Tests emulate real attacker behavior across prompt injection, jailbreaks, data extraction, poisoning, and agentic tool abuse, with findings mapped to OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, and the EU AI Act. Mindgard cuts AI risk assessment from weeks to hours and supports continuous compliance as AI systems change. Modules: AI Discovery & Recon, AI Red Teaming, AI Assessment, AI Runtime Protection, Model Scanning, AI Governance & Compliance.

General Analysis serves as a cutting-edge AI security platform designed to aid security teams in adversarially testing, monitoring, and safeguarding AI agents and systems that are actively deployed. Its primary objective is to enable organizations to grasp AI-related risks, avert potential incidents, and secure various real-world AI applications, which include employee copilots, coding agents, customer support tools, healthcare assistants, legal aids, financial copilots, and creative workflows. By mapping out AI applications and agents through an extensive range of parameters such as prompts, retrieval methods, tools, MCP servers, browser activities, permissions, repositories, cloud accounts, SaaS workflows, and business processes, it effectively identifies context-aware attacks that highlight vulnerabilities within the system. The platform's automated red teaming employs adaptable attacker models that respond to target behaviors and generate complex multi-step exploit chains, providing security teams with the ability to discover vulnerabilities that traditional static prompt sets or endpoint-only testing might overlook. Ultimately, General Analysis empowers organizations to enhance their AI security posture while ensuring that their deployments remain resilient against evolving threats.

The OpsAgents CLI Gateway provides a unified authenticated gateway for your AI agents, enabling access to all necessary command-line interfaces without the need for local installations. With this system, you can execute various commands, including gcloud, gh, Firebase, Shopify, Trello, and others, along with typed JSON routes, all through a single remote cloud gateway. Each command issued is authenticated, scoped, and logged, ensuring that the agent sends the CLI and its parameters, while the gateway executes it remotely and delivers structured results back to you. Additionally, a comprehensive audit trail is maintained for every command executed, offering transparency and accountability. This solution serves as the foundational platform for the OpsAgents agent fleet. Subscription plans are available at Starter for $29, Pro for $99, and Scale for $299 per month, catering to different user needs. OpsAgents AI is proud to offer this innovative service.

The NVIDIA Open Agent Safety Platform serves as an open reference framework designed to monitor and manage the behavior of AI agents continuously, ensuring that organizations can maintain agents that are isolated, observable, auditable, and operate within set boundaries. This platform integrates real-time governance, ongoing threat detection, and the enforcement of policies through hardware isolation, providing robust protection for enterprise AI agents from the initial testing phases all the way to deployment. The NVIDIA OpenShell contributes to this by offering an open-source runtime that differentiates the execution of agents from their access to data, tools, and outside systems, utilizing sandboxed environments and a zero-trust policy approach to strictly regulate agents' visibility, actions, and interactions. Policies are enforced externally to the agent process, effectively mitigating the risks associated with unpredicted behavior. Furthermore, NVIDIA Sentry enhances security by adding an extra layer that meticulously monitors agent requests and responses, verifies agent identities, and continuously manages access to data, tools, APIs, and services while also having the capability to isolate agents when necessary. This comprehensive approach ensures that organizations can safeguard their AI agents while promoting a secure and controlled operational environment.

Vulnify serves as a runtime authorization platform tailored for developers and security teams creating AI agents that interact with tools or APIs. Prior to executing a tool, the agent transmits action metadata—which encompasses details about the agent, the action being taken, the resource involved, the destination, and the count of records—and subsequently receives a decision categorized as ALLOW, REVIEW, or BLOCK, accompanied by a risk score ranging from 0 to 100 along with justifications. Teams have the flexibility to define and test YAML policies via a command-line interface, while also incorporating checks through Node.js or Python SDKs, a REST API, or various adapters compatible with agent frameworks. Additionally, the monitor mode enables the logging of decisions without hindering actions, and in the event that Vulnify becomes unavailable, a fail-closed protocol will prevent actions unless a fail-open setting is established. An audit log that utilizes hash chaining maintains a record of decisions made, with paid subscriptions offering the inclusion of human review processes. Typical applications of Vulnify include overseeing data exports, managing external communications, processing payments, and other actions initiated by agents. It is important to note that Vulnify focuses on evaluating action metadata instead of the actual contents of the records affected, ensuring a streamlined approach to authorization. Overall, this unique system helps enhance security and compliance for AI-driven operations.

Lasso is an enterprise AI security platform built to secure AI agents, generative AI applications, and emerging agentic systems across complex business environments. The solution delivers end-to-end visibility into AI deployments by discovering, cataloging, and continuously monitoring AI assets throughout their lifecycle. Organizations can use the platform to identify models, prompts, tools, guardrails, and configurations while maintaining an up-to-date inventory of AI resources. Automated AI red teaming capabilities help uncover vulnerabilities, weaknesses, and attack vectors before they can be exploited in production environments. Runtime enforcement mechanisms monitor interactions in real time, ensuring AI systems operate within approved policies and security boundaries. The platform’s intent-based analysis approach helps detect threats that traditional security tools may miss due to the non-deterministic nature of AI behavior. Lasso also supports AI detection and response workflows that help security teams investigate incidents and mitigate risks more effectively. Enterprise-ready performance, scalability, and governance features make the platform suitable for organizations adopting AI at scale. By providing continuous visibility, protection, and risk management, Lasso helps businesses innovate confidently while reducing exposure to AI-related threats.

Pillar Security serves as a comprehensive AI security platform designed to safeguard the agentic workforce throughout the entire AI lifecycle, encompassing stages from development to deployment and ongoing runtime protection. By integrating business context during phases of discovery, testing, and protection, it ensures that security intelligence accumulates across various AI applications, including agents, models, prompts, frameworks, tools, MCP servers, skills, coding agents, and both SaaS and cloud environments. The platform enables organizations to identify and manage AI assets effectively, even those that are unapproved or fall under shadow AI, while also evaluating risks related to supply chain and overall security posture. Additionally, it maps out the attack surfaces associated with agentic systems and verifies critical vulnerabilities that need addressing. With its AI Security Posture Management features, Pillar scrutinizes interconnected agents, tools, permissions, data sources, prompts, models, and supply chain elements to reveal high-risk pathways, policy breaches, misconfigurations, and potential threats posed by coding agents, all of which enhance the understanding of the impact when a single component encounters a breach. Ultimately, Pillar Security empowers organizations to maintain a robust security framework while navigating the complexities of AI technology.

XecGuard, developed by CyCraft, serves as a firewall for trustworthy and agentic AI, specifically engineered to safeguard enterprise AI systems against various threats such as prompt injection, data leakage, and unsafe outputs. Leveraging CyCraft's extensive experience in red and blue teaming within sectors like government, finance, and high-tech manufacturing, XecGuard enhances security measures by integrating AI guardrails with cybersecurity protocols, compliance safeguards, and risk management tactics, ultimately facilitating the safe adoption of enterprise AI. This innovative solution functions as a plug-and-play LoRA security module, allowing organizations to bolster their LLM defenses seamlessly without necessitating modifications to the underlying model architecture, thus ensuring rapid implementation while maintaining optimal performance. By utilizing proprietary security datasets and advanced multi-stage fine-tuning methods, XecGuard significantly improves the resilience of LLMs against adversarial attacks, malicious interventions, and unauthorized extraction of sensitive information, making it an essential component for any enterprise aiming to fortify its AI systems effectively. Furthermore, its ability to adapt quickly to emerging threats underscores its value in today’s fast-evolving technological landscape.

KYDE serves as a behavioral firewall designed specifically for AI agents, ensuring they can be entrusted with significant responsibilities. By delineating prohibited actions, documenting completed tasks, and safeguarding your proprietary knowledge, KYDE enhances the reliability of AI agents. Positioned externally, KYDE operates in the request pathway between your agents and all LLM providers, systematically intercepting, scoping, and signing each action prior to execution. This external placement ensures it cannot be overridden by the agent itself, maintaining strict control. With no need for code alterations and only one environment variable required, KYDE is both provider-agnostic and ready for multi-cloud platforms, targeting a latency of under 100 milliseconds. It encompasses three essential functions within a single layer. The first is PROVE, which creates an audit trail that remains independent of any LLM provider; actions are signed using Ed25519, hash-linked, and recorded at the boundary, making them irretrievable by the agent. In this scenario, the perpetrator cannot fabricate their own account. The second function is RATE, which evaluates agent behavior across different providers on a unified scale known as the KYDE Trust Score™. While vendors assess their own performance, KYDE focuses on objectively grading agent behavior, creating a more transparent evaluation system. Finally, this comprehensive framework not only enhances accountability but also fosters an environment of trust in AI interactions.

Onyx serves as a robust AI control platform designed for the discovery, protection, governance, optimization, and evaluation of AI agents and models within an organization. It provides crucial visibility for security, governance, and AI teams into both authorized and unauthorized AI activities across various environments, including SaaS applications, cloud services, endpoints, and code, encompassing aspects such as prompts, responses, and agent behaviors. The AI Security feature enhances the organization's security posture by pinpointing vulnerabilities and implementing real-time safeguards against potential threats and misuse. Meanwhile, AI Governance ensures compliance with security standards and regulatory mandates by offering opt-in coverage and allowing policy controls to be articulated in natural language. Additionally, AI Orchestration streamlines the process of deploying agents and Multi-Cloud Platforms (MCPs), while optimizing for cost, accuracy, and latency. The AI ROI component facilitates the measurement of adoption, the establishment of objectives, and the tracking of results across various departments within the organization. Furthermore, the Onyx Guardian Agent functions as an overseeing AI, perpetually identifying risks and resolving issues throughout the platform, thereby enabling organizations to effectively manage a large number of agents seamlessly. Ultimately, Onyx empowers businesses to harness the full potential of AI while maintaining control and oversight.

TrojAI is a comprehensive AI security solution built to address the unique risks associated with generative AI, large language models, and autonomous AI agents. The platform helps organizations identify, assess, and mitigate vulnerabilities before AI systems are deployed into production environments. Through its security testing capabilities, TrojAI uncovers weaknesses that could lead to prompt injection, data leakage, jailbreak attacks, tool misuse, or unauthorized behavior. Runtime protection features continuously monitor AI applications and agent activities to detect and block threats as they occur. The platform also helps organizations align with security frameworks such as OWASP, NIST, and MITRE, simplifying governance and compliance initiatives. TrojAI Detect focuses on securing AI models during development and testing phases, helping teams strengthen models before release. TrojAI Defend provides real-time protection for deployed AI systems, reducing the risk of operational disruptions and security incidents. Flexible deployment options allow organizations to integrate the platform into cloud, hybrid, or self-hosted environments while maintaining control over sensitive data. By combining proactive testing with continuous monitoring, TrojAI helps enterprises build and operate secure AI ecosystems.

F5 AI Guardrails is an enterprise AI security platform that provides runtime protection for deployed AI models, agents, and applications across diverse environments. The solution is designed to address emerging AI risks by monitoring interactions, enforcing policies, and preventing malicious attempts to manipulate AI behavior. Organizations can use the platform to defend against prompt injection attacks, jailbreak techniques, data leakage incidents, and other adversarial threats targeting AI systems. Distributed data protection capabilities inspect AI interactions in real time and help enforce data loss prevention policies across applications and models. The platform includes automated compliance features that support frameworks and regulations such as GDPR, HIPAA, and the European Union AI Act. Advanced observability and auditing tools provide detailed records of AI activity, enabling stronger governance and accountability. F5 AI Guardrails also supports dynamic model routing and low-latency security controls to maintain operational performance while enforcing protections. Model-agnostic functionality allows organizations to secure both proprietary and open-source AI models using a unified approach. By integrating security, compliance, observability, and runtime protection, F5 AI Guardrails helps organizations confidently scale their AI initiatives.

Secure Traces is an AI-first technology and cybersecurity provider that helps enterprises modernize operations while maintaining strong security and compliance controls. Its primary focus areas include agentic AI, healthcare and pharmaceutical technology, cyber defense, cloud modernization, Oracle platforms, and enterprise applications. The company develops autonomous AI agents, LLM pipelines, intelligent automation, and model governance capabilities that can move enterprise workflows from analysis into action. Healthcare and life sciences services include clinical, pharmacy, payer, and modernization solutions designed for HIPAA and GxP-aligned environments. Cybersecurity offerings include 24/7 SOC operations, threat research, threat hunting, defense engineering, risk management, and operational technology monitoring across SCADA, ICS, and field systems. Secure Traces also provides ERP and enterprise application services, including Oracle Fusion Cloud implementations and custom business applications. Its engagement model typically moves through assessment and discovery, strategic planning, implementation and monitoring, and ongoing response and optimization. The company holds certifications including ISO 9001 and ISO/IEC 20000-1:2018 and positions provable security as a core part of its delivery approach. Secure Traces is intended for enterprises that need to adopt AI, modernize regulated technology environments, and improve cyber resilience without separating innovation from security.

Transitioning from development to production, as well as from traditional data engineering to artificial intelligence, requires securing the various environments, pipelines, tools, and open-source components integral to your data and AI supply chain. It is essential to continuously identify, prevent, and rectify security and compliance vulnerabilities in AI before they reach production. In addition, monitoring AI applications in real-time allows for the detection and mitigation of adversarial AI attacks while enforcing specific application guardrails. Noma integrates smoothly across your data and AI supply chain and applications, providing a detailed map of all data pipelines, notebooks, MLOps tools, open-source AI elements, and both first- and third-party models along with datasets, thereby automatically generating a thorough AI/ML bill of materials (BOM). Additionally, Noma constantly identifies and offers actionable solutions for security issues, including misconfigurations, AI-related vulnerabilities, and non-compliant training data usage throughout your data and AI supply chain. This proactive approach enables organizations to enhance their AI security posture effectively, ensuring that potential threats are addressed before they can impact production. Ultimately, adopting such measures not only fortifies security but also boosts overall confidence in AI systems.

Google has introduced the Agent Payments Protocol (AP2), a collaborative open protocol developed with over 60 diverse companies in payments, fintech, and technology, including Mastercard, PayPal, Adyen, Coinbase, and Etsy, aimed at facilitating secure transactions led by agents across various platforms. This new protocol builds upon previous open standards such as Agent2Agent (A2A) and the Model Context Protocol (MCP) to ensure that when an AI agent processes a payment on behalf of a user, it adheres to three essential criteria: authorization, to confirm that the user has explicitly consented to the specific transaction; authenticity, to verify that the purchase intended by the agent aligns with the user's actual intent; and accountability, to maintain transparent audit trails and assign responsibility in the event of any errors or fraudulent activities. In order to uphold these standards, the protocol incorporates mandates, which are cryptographically signed digital contracts that are supported by verifiable credentials, ensuring a high level of security and trust in agent-led transactions. The implementation of AP2 represents a significant advancement in the realm of digital payments, aiming to enhance user confidence in automated financial interactions.

AIVM Brain serves as a regulated and verifiable AI knowledge-sharing platform utilized by a company's workforce alongside its AI agents. It integrates seamlessly with existing tools such as Slack, Google Drive, Notion, GitHub, Box, Confluence, Salesforce, and Telegram, ensuring that the original permissions of each source remain intact, allowing both users and agents to access only the information they are authorized to view. All access is meticulously logged in a tamper-proof, content-agnostic audit trail that confirms who requested information and what was revealed, while refraining from storing any actual content, and this log can be verified independently by auditors. Agents interact with Brain through a controlled MCP endpoint that incorporates mandates, human oversight, and an emergency kill switch. The platform is designed to be model-agnostic, compatible with AI models like Claude, OpenAI, and Gemini, or even a customer's proprietary model using a bring-your-own-key approach, and it ensures that no customer data is used for training purposes. Among its enterprise capabilities are single sign-on (SSO), tenant isolation, the ability to revoke permissions in real-time, and ongoing compliance with SOC 2 and ISO 42001 standards. Delivered as a software-as-a-service solution, it offers various access methods, including hosted SaaS, MCP, SDK, REST API, and CLI options, adapting to a variety of enterprise needs. Its robust security and compliance features make it a reliable choice for organizations looking to leverage AI technology responsibly.

Amplify Console is a security orchestration platform built as an agentic security harness for security engineering teams. The platform helps teams move from idea to production by creating, testing, deploying, tracking, and reporting on custom agentic security detections. Unlike general-purpose coding agents, Amplify Console is designed around security-native workflows, deep codebase context, and cloud-to-production execution. Its custom detection agents can be tailored to a company’s specific risks, priorities, and environment. Security-native context gives teams visibility across codebases and maps relationships that generic agents may miss. The platform also supports custom triage, reachability analysis, automated remediation, live integrations, and narrative-based reporting. The Reachability Engine helps teams focus on vulnerabilities that are actually reachable or exploitable. Automated remediation supports one-click fixes that can be customized, reviewed, and coordinated with developers. By combining custom detection agents, security workflow context, pipeline execution, triage automation, reachability analysis, remediation, integrations, and reporting, Amplify Console helps security teams move faster and reduce low-value vulnerability work.

Constellation Gate AI serves as an auxiliary defense mechanism for AI agents, positioned strategically between the agent and the model to filter all requests for potential threats and data leaks. This solution functions as an inline gateway for coding agents and model APIs, ensuring protection of workflows while eliminating the need for significant code modifications. Users can direct existing tools such as Claude Code, Cursor, OpenClaw, Codex, or OpenCode to utilize Gate, thereby gaining access to defenses against prompt injection, secret detection, PII redaction, token optimization, and a reliable audit trail. The platform specifically addresses three critical vulnerabilities: prompt injection attacks, leakage of credentials and PII, and unauthorized tool calls. Rather than depending on the model's self-defense mechanisms, Gate preemptively intercepts attacks before they penetrate the model, removes sensitive information prior to the return of responses, and prevents outputs from compromised tools before an agent can act on them. Gate is compatible with the existing calls made by agents, relaying them to the model while meticulously scanning each request and response in both directions, ensuring comprehensive protection against emerging threats. This proactive approach not only enhances security but also instills confidence in users about the integrity and safety of their AI workflows.

Bevel serves as a vendor-neutral, Git-integrated control plane tailored for enterprise AI agents, allowing organizations to define their agents, context, skills, tools, permissions, and identities as owned files within their infrastructure, which can then be accessed by any agent runtime through MCP. The context is organized as typed knowledge nodes, each with documented provenance detailing its source, the last modification, and verification timestamps, and this information is compiled into a navigable graph that can be updated and utilized for creating dashboards. Skills are articulated as straightforward Markdown procedures, enabling process owners to easily read, review changes, and transfer them across different runtimes. Additionally, tool manifests outline the capabilities available, while sensitive information is stored securely in a vault, governed by access rules that dictate which agents can read certain files or invoke specific endpoints. Each agent is assigned a unique identity and credentials, ensuring that all actions can be traced back to their source. This comprehensive framework not only enhances security and organization but also promotes transparency and accountability in AI operations.

NVIDIA OpenShell serves as an open and secure runtime environment specifically designed for autonomous AI agents, regulating their execution, access rights, and the pathways for inference traffic. Instead of embedding security within the model or application, it maintains safety measures in the surrounding environment, meaning that nothing is allowed by default; permissions are assigned through established policies, and enforcement mechanisms operate outside the agent process to prevent any circumvention via prompts. Each autonomous agent operates within a confined sandbox, which restricts direct network connectivity, limits file access, and implements kernel-level monitoring of system calls to ensure rigorous oversight. Acting as the control plane, a gateway is responsible for user authentication, lifecycle management of sandboxes, and the provision of policies, settings, credentials, and inference configurations to the agents. Additionally, a supervisor operates externally to each sandbox, scrutinizing network requests according to policies at various levels—including binary, destination, method, and path—and only grants access to credentials when explicitly permitted, thus enhancing the overall security framework. This layered architecture ensures that the agents function effectively while maintaining robust security protocols throughout their operations.

Dendrite is a versatile platform that operates independently of any specific framework, allowing developers to design web-based tools for AI agents that can authenticate, interact with, and gather data from any online source. This innovative system mimics human browsing actions, which aids AI applications in navigating websites and retrieving information effortlessly. It features a Python SDK that equips developers with essential resources to create AI agents capable of engaging with web elements and extracting relevant data. Dendrite’s adaptable nature ensures it can seamlessly fit into any technology stack, making it an ideal choice for developers looking to improve the web interaction abilities of their AI agents. The Dendrite client synchronizes securely with website authentication sessions already established in your local browser, eliminating the need to share or store sensitive login information. Additionally, the Dendrite Vault Chrome Extension allows users to safely share their browser-based authentication sessions with the Dendrite client, further enhancing convenience and security. Ultimately, Dendrite empowers developers to create intelligent web interactions, streamlining the integration of AI into everyday online tasks.

Multifactor is an advanced platform designed for account-sharing and access management that emphasizes a zero-trust approach, utilizes post-quantum cryptography, and features intricate permission settings. Instead of merely exchanging credentials, users can safely store their online accounts—including passwords, passkeys, and 2FA codes—in a secure vault, allowing them to send controlled links to authorize access for both people and AI agents. The ability to revoke access immediately ensures that the underlying credentials remain concealed, enhancing security. Users can set specific permissions, such as allowing someone to "read transactions" without permitting them to "initiate transfers," while also generating comprehensive, non-repudiable audit trails for every action taken. Moreover, the platform incorporates robust encryption and a post-quantum security framework to guarantee that only authorized individuals ever access sensitive information. Additionally, it can function as a comprehensive identity and access management solution, providing support for various authentication methods, including biometrics and hardware tokens, as well as facilitating authorization, access auditing, enforcement of device and network endpoints, and secure sharing of accounts and resources. This multifaceted approach not only simplifies access management but also enhances overall cybersecurity measures.

Pi serves as a proactive product security platform designed to cultivate a robust institutional security memory, enabling organizations to identify, address, and avert recurring vulnerabilities without hindering their development processes. By continuously assimilating various elements like codebases, historical incidents, penetration test reports, and support tickets into a dynamic inventory, it provides essential context regarding the organization's software development and security practices. Upon discovering a vulnerability, Pi not only identifies its architectural root cause but also searches the entire codebase for similar variants, facilitating a comprehensive resolution of related issues instead of addressing each finding in isolation. The remediation process is tailored to align with the organization's specific programming languages, architectural frameworks, and coding conventions, seamlessly integrating into developers' workflows. Additionally, the insights gained by the system are transformed into preventive guardrails that can be implemented in integrated development environments (IDEs) and during pull requests, effectively intercepting known insecure practices before they can be deployed into production. Ultimately, this approach not only enhances security but also streamlines the development lifecycle, ensuring that security becomes an integral part of the coding process.

Lakera Guard enables organizations to develop Generative AI applications while mitigating concerns related to prompt injections, data breaches, harmful content, and various risks associated with language models. Backed by cutting-edge AI threat intelligence, Lakera’s expansive database houses tens of millions of attack data points and is augmented by over 100,000 new entries daily. With Lakera Guard, the security of your applications is in a state of constant enhancement. The solution integrates top-tier security intelligence into the core of your language model applications, allowing for the scalable development and deployment of secure AI systems. By monitoring tens of millions of attacks, Lakera Guard effectively identifies and shields you from undesirable actions and potential data losses stemming from prompt injections. Additionally, it provides continuous assessment, tracking, and reporting capabilities, ensuring that your AI systems are managed responsibly and remain secure throughout your organization’s operations. This comprehensive approach not only enhances security but also instills confidence in deploying advanced AI technologies.

AgentScan is a no-cost, deterministic security scanner specifically designed for evaluating AI agent skills. It meticulously inspects a skill directory, which includes platforms like Claude Code, Codex, OpenCode, and MCP servers, for various vulnerabilities such as prompt injection, hidden secrets, network activity, malware signatures, and obfuscation techniques prior to installation. Each identified issue is accompanied by specific file:line references and an associated confidence score. The tool operates without executing the skill or uploading any data, functioning entirely offline. Being free and open-source under the MIT license, it also offers the Trust Pack feature, which facilitates the addition of 90 pre-audited skills with a single command. This ensures users can enhance their security measures efficiently.

GuardionAI serves as an Agent and MCP Security Gateway, delivering comprehensive security for AI agents and Model Context Protocol tools that interact with enterprise data. Positioned within the execution path, it effectively identifies and redacts sensitive information, implements protective measures, and offers enhanced visibility into activities that conventional SIEM, DLP, and identity frameworks typically miss. Every action performed by agents is meticulously scrutinized, enforced, and logged at the protocol level, encompassing AI agents, LLM applications, RAG systems, chatbots, coding assistants, MCP servers, internal applications, databases, operating systems, and cloud infrastructures. GuardionAI is designed to counteract critical AI vulnerabilities including prompt injection, system overrides, web-based assaults, MCP tool tampering, malicious code execution, exposure of NSFW content, leakage of PII and credentials, unauthorized access to confidential data, off-topic drift, and breaches of access control, all aligned with the OWASP LLM Top 10 and agentic AI threat frameworks. Notably, the gateway offers a robust four-layer protection system, ensuring that organizations can safeguard their AI assets more effectively than ever before. This multifaceted approach not only enhances security but also empowers teams with the insights needed to navigate the complexities of modern AI environments.

Every app, build pipeline and AI agent that calls Stripe, OpenAI or any other third-party API needs that API key. So copies of live keys pile up in .env files, CI settings, laptops and agent environments, and each copy is one more place a key can leak from: a poisoned package, a prompt-injected agent, a compromised build or a config file pushed by mistake. A stolen key keeps working until someone notices, then has to be replaced everywhere it was copied. KnoxCall keeps the real key in one place and adds it to each call on its way out. Your apps, pipelines and agents hold only a KnoxCall token. If a token leaks, one click revokes it everywhere, without rotating the provider key. Every call is logged with the name of the app or agent that made it. Because every call already passes through KnoxCall, it's also the natural place to put guardrails on AI agents. Each agent can be given its own spending limit, every prompt is checked before it reaches the model, and the personal data KnoxCall detects is swapped out before the model sees it, then put back in the reply. Security teams stay in control of the foundations. CI jobs can authenticate with workload identity instead of a stored secret, and on the Enterprise plan you can lock your keys with a master key held in your own cloud account and manage access through your existing single sign-on and SCIM provisioning. KnoxCall fits the stack you already use, with SDKs for Node, Python, Go, PHP, Ruby, React and the browser. Start on the free plan with no card required, or move to a paid plan from $19 a month.

kgateway is a widely deployed Kubernetes gateway designed to power modern microservices and AI-driven workloads. It serves as a control plane for advanced ingress, API management, and AI gateway use cases. Built on Envoy and open-source foundations, kgateway implements the Kubernetes Gateway API for consistent, cloud-native connectivity. The platform aggregates APIs and applies authentication, authorization, and rate limiting in one centralized layer. Kgateway also protects AI models, tools, and agents by securing LLM consumption and data access. Intelligent routing capabilities support AI inference workloads directly inside Kubernetes clusters. The platform scales from lightweight microgateways to massively parallel centralized gateways. Kgateway supports agent-to-agent and MCP-based communication through a single secure endpoint. It enables omni-directional API connectivity across hybrid and multi-cloud environments. Kgateway helps organizations innovate faster while maintaining security and governance.

InstaVM offers a robust production sandbox and cloud solution designed specifically for AI agents, equipping them with immediate access to computing resources including runtime, storage, networking, secrets, and policy management. Unlike traditional sandboxes, it utilizes hardware-isolated virtual machines instead of containers, ensuring that teams can provide AI agents with secure environments that feature complete Linux filesystems, networking capabilities, package management, RESTful API access, and the ability to maintain persistent states. The platform's support for snapshots enables users to create forks of any sandbox and revert to previous states, while its persistent volumes ensure that data is retained across executions. Additionally, egress control allows teams to manage which connections can be made externally, and features like secrets injection and Vault work to safeguard sensitive information from potential prompt injections. Moreover, public URL deployments can make any port accessible on the public web, enhancing its versatility. It is specifically tailored for various agent patterns, including code interpreters, deployment agents, deep research agents, AI evaluations, reinforcement learning applications, computer usage, and vibe coding applications, making it a comprehensive tool for developers. With its innovative architecture and extensive features, InstaVM solidifies its position as a leading solution for AI-driven projects.

Introducing a premier developer platform designed for the testing and debugging of AI agents, we provide the essential tools so you can focus on innovation. With our system, you can visually monitor events like LLM calls, tool usage, and the interactions of multiple agents. Additionally, our rewind and replay feature allows for precise review of agent executions at specific moments. Maintain a comprehensive log of data, encompassing logs, errors, and prompt injection attempts throughout the development cycle from prototype to production. Our platform seamlessly integrates with leading agent frameworks, enabling you to track, save, and oversee every token your agent processes. You can also manage and visualize your agent's expenditures with real-time price updates. Furthermore, our service enables you to fine-tune specialized LLMs at a fraction of the cost, making it up to 25 times more affordable on saved completions. Create your next agent with the benefits of evaluations, observability, and replays at your disposal. With just two simple lines of code, you can liberate yourself from terminal constraints and instead visualize your agents' actions through your AgentOps dashboard. Once AgentOps is configured, every execution of your program is documented as a session, ensuring that all relevant data is captured automatically, allowing for enhanced analysis and optimization. This not only streamlines your workflow but also empowers you to make data-driven decisions to improve your AI agents continuously.

Thoughtly allows businesses to create and implement advanced AI voice agents in a mere 17 minutes, ushering in a new era of communication. Enhance your strategic decisions with in-depth analytics, comprehensive reports, and A/B testing capabilities. Thoughtly offers immediate data visualization and performance insights, allowing you to refine your communication strategies, grasp customer preferences, and boost conversion rates effectively. Your Thoughtly agent integrates seamlessly with your calendar, collaborating with callers to identify the most suitable meeting times, ensuring coordination is a breeze. Each incoming call is a chance for engagement. With Thoughtly, no potential lead will go unanswered, as your agent expertly guides them to the most appropriate contact point, ensuring perfect routing every time and maximizing conversion opportunities. Additionally, Thoughtly's unique features make it easier than ever to stay ahead in a competitive landscape.

MintMCP serves as a robust Model Context Protocol (MCP) gateway and governance solution designed for enterprises, offering a centralized approach to security, observability, authentication, and compliance for AI tools and agents that interface with internal data, systems, and services. This platform empowers organizations to deploy, oversee, and manage their MCP infrastructure on a large scale, providing real-time insights into each MCP tool interaction while implementing role-based access control and enterprise-level authentication, all while ensuring comprehensive audit trails that adhere to regulatory standards. Functioning as a proxy gateway, MintMCP effectively aggregates connections from various AI assistants, including ChatGPT, Claude, and Cursor, streamlining monitoring processes, mitigating risky behaviors, managing credentials securely, and enforcing detailed policy measures without necessitating individual security implementations for each tool. By centralizing these functions, MintMCP not only enhances operational efficiency but also fortifies the security posture of organizations leveraging AI technologies.

Laptops vanish from spreadsheets, and agents left unchecked make auditors twitch. Flottix is one registry that fixes both halves: hardware, license inventory, custody records, and audit history sit in a database governed by a strict state machine, and AI agents run the errands through MCP. When an agent prepares an onboard, moves custody, or counts stock, the action lands as a proposal. A person approves it; only then does the registry change. Every transition is logged, each customer's data stays walled off from the others, and rewriting a log entry isn't possible through the API. Claude, Cursor, or any other MCP client works. The quickstart has you taking inventory through Claude in five minutes. 50 items free, protocol fully unlocked at every tier. Starter costs EUR 19/month; Professional (EUR 59/month) adds staged approvals, so a second person signs off on agent actions. Self-hosting isn't on the roadmap. This is a hosted service.

The Agent Client Protocol (ACP) serves to unify the communication between code editors, integrated development environments (IDEs), and coding agents, establishing agent-editor interoperability as a standard rather than necessitating unique integrations for every conceivable pairing. It establishes a common interface for interaction between AI agents and client applications, featuring a flexible, extensible, and platform-independent architecture suitable for both local and remote use cases. By tackling issues related to integration costs, limited compatibility, and developer dependency, ACP allows agents adhering to the protocol to function seamlessly with any compatible editor, while editors that embrace ACP can tap into a wider network of ACP-compatible agents. Much like the Language Server Protocol facilitated standardized language server integration, ACP separates agents from editors, enabling both to evolve independently, thereby empowering developers to select the most effective tools for their specific workflows. This innovation fosters a collaborative environment where tools can be easily integrated, enhancing overall productivity and efficiency for developers.

Forest is an operational backend for regulated companies that need to run human teams, AI agents, BPOs, LLMs, workflows, and suppliers in one governed environment. The platform connects databases, compliance providers, internal tools, specialized agents, and external systems while keeping data inside the customer’s infrastructure. Forest provides the shared control plane where business logic, workflows, permissions, RBAC, smart actions, and audit trails are managed. Teams can use Forest to run regulated workflows on top of existing KYC and KYB providers such as Sumsub, Onfido, Veriff, Persona, and Trulioo. It supports onboarding workflows that combine identity verification, business registry checks, beneficial-owner discovery, document checks, screening, risk-based routing, agent triage, and human review. Forest’s MCP support lets AI agents call the same workflows used by human operators while attaching audit records to each action. The platform is designed for agentic operations in regulated environments where every action by humans, agents, BPOs, LLMs, and workflows must remain traceable. Forest also provides an implementation method that maps the company’s ecosystem, connects data and suppliers, designs operator journeys, and brings workflows into production. By combining governed workflows, live data access, MCP-based agent execution, auditability, permissions, and compliance controls, Forest helps regulated companies scale operations safely.