Alternatives to Antaeus

Minimize the likelihood of piecemeal and reactive operational decision-making by implementing analytically based business rules to enhance and streamline decisions throughout your organization. The SAS Business Rules Manager offers a centralized repository for rules, serving as a unified platform for overseeing the development and implementation of rules, along with automating workflows. Administrators benefit from a singular control point that manages user authorization, access, and security settings for each individual. An integrated workflow allows for the customization of processes while ensuring that all publishing activities are traceable and properly versioned. Furthermore, the system grants detailed control over rule functionalities, which upholds role-based security to confirm that users possess the necessary authorizations. By leveraging analytical modeling, businesses can extract rules directly from their operational data, enabling the automatic production of rule definitions and associated vocabularies. This approach not only enhances decision-making but also fosters a more consistent and reliable operational environment.

Red Hat® Decision Manager serves as a robust platform for creating containerized microservices and applications designed to automate business decision-making processes. This comprehensive solution features capabilities for managing business rules, processing complex events, and optimizing resources. Organizations have the ability to seamlessly integrate advanced decision-making logic into their line-of-business applications, enabling them to swiftly modify core business rules in response to evolving market conditions. The seventh iteration of Red Hat® Decision Manager stands out as a powerful, scalable open-source business rules management system that harnesses both business resource optimization and complex event processing (CEP) technologies. It empowers organizations to effectively capture intricate business logic while facilitating the development of applications that streamline business decisions. Additionally, Decision Manager 7 is fully compatible with the Red Hat Application Services suite and integrates seamlessly with Red Hat OpenShift® for deployment across hybrid cloud environments, ensuring that businesses can leverage its capabilities no matter where their infrastructure is hosted. This flexibility further enhances its appeal for modern enterprises seeking to optimize their operational efficiency.

Leapter is a platform that leverages AI to assist in the development, experimentation, and implementation of business rules and decision-making logic. Users can articulate rules in everyday language, transforming them into visual and executable Blueprints that allow both business professionals and developers to collaboratively review and enhance them. Teams have the capability to test different scenarios, evaluate modifications, and track the reasoning behind each decision made. The logic that receives approval operates in a deterministic manner, ensuring that identical inputs and rules yield consistent outputs without relying on a language model during execution. Business logic can be seamlessly integrated with applications, AI agents, and automation processes via APIs and MCP, or it can be exported as JavaScript or Python. Common applications for this platform include pricing calculations, eligibility assessments, underwriting criteria, risk evaluation, and policy verification. Ultimately, Leapter empowers teams to maintain clarity, testability, and human oversight over their business logic, fostering a collaborative environment for continuous improvement. By doing so, it enhances the efficiency and accuracy of decision-making within organizations.

Plurai serves as a real-world trust platform dedicated to AI agents, designed for simulation-based assessment, safeguarding, and enhancement, effectively transforming agents into dependable and progressively advanced production systems. It assists teams in developing evaluations and protective measures specific to their requirements, facilitating the transition from initial prototypes to robust, scalable production. Plurai's simulation framework equips agents for real-world challenges rather than controlled environments, employing hyper-realistic, product-specific experimentation and assessment that addresses the intricacies of production. The platform creates genuine multi-turn interactions, diverse personas, essential artifacts, and tool simulations, utilizing organizational PRDs, pertinent references, and policies to construct a knowledge graph that broadens edge-case coverage. By moving away from static datasets, manual test formulation, and inconsistent LLM evaluation methods, Plurai organizes assessments into coherent, executable experiments, enabling teams to test new iterations, track regressions, and confirm enhancements prior to deployment. Ultimately, this innovative approach ensures that AI agents are not only trusted but also continuously refined for optimal performance in dynamic environments.

Create cloud-native applications designed to streamline business decisions and processes. Red Hat® Process Automation Manager serves as a robust platform for crafting containerized microservices and applications aimed at automating these business functions. It encompasses various technologies, including business process management (BPM), business rules management (BRM), as well as business resource optimization and complex event processing (CEP). Additionally, it features a user experience platform that facilitates the development of interactive user interfaces for process and decision services with minimal coding efforts. This platform equips business users with essential tools for modeling flows and policies, utilizing Business Process Model and Notation (BPMN) models, Decision Model and Notation (DMN) models, and specialized rule languages tailored to specific domains. With a focus on cloud development, users can seamlessly deploy their finished models as containerized microservices on Red Hat OpenShift. Furthermore, it leverages the full power of Drools, a widely recognized open-source rules engine, ensuring flexible and effective automation solutions. Overall, this approach enhances operational efficiency and fosters innovation across various business sectors.

GoRules is a business rules management system where the policy your analysts read and the logic your systems execute are the same artifact. Write conditions the way the business says them, lay decisions out on a graph canvas, or author full policy documents with prose and decision tables. Everything compiles to ZEN, an MIT-licensed engine written in Rust that evaluates a typical decision in about 10 microseconds. Because ZEN is a library with bindings for Node.js, Python, Go, Java, Kotlin, C#, Swift, and Rust, one compiled ruleset serves your REST API, your AI agents over MCP, and your PySpark batch jobs with no second implementation. Before a change reaches production it passes static analysis for type errors, unreachable rules, and contradictions between policies, then moves through branches, scenario tests, reviews, and versioned releases across environments. Every answer carries a replayable trace. Start free on the managed cloud, self-host, or embed the engine directly.

Code Effects is a powerful decision automation platform designed specifically for .NET applications. It provides a human-readable business rules engine that simplifies how organizations manage and execute complex business logic. Through its intuitive web-based rule editor, business users can create, edit, and maintain rules without relying on developers. The platform’s high-speed lambda expression engine ensures fast and reliable rule evaluation even at large scale. Code Effects supports reusable rules and flexible integrations with databases, APIs, and custom objects. Its modular design allows the rule editor and engine to run together or independently across systems. The solution eliminates the need for external rule services, keeping data and security fully in-house. With a perpetual licensing model, it offers long-term cost efficiency without recurring fees. Trusted by Fortune 500 companies and government agencies, Code Effects delivers enterprise-grade reliability. It transforms business logic into a manageable, scalable asset.

Agenta provides a complete open-source LLMOps solution that brings prompt engineering, evaluation, and observability together in one platform. Instead of storing prompts across scattered documents and communication channels, teams get a single source of truth for managing and versioning all prompt iterations. The platform includes a unified playground where users can compare prompts, models, and parameters side-by-side, making experimentation faster and more organized. Agenta supports automated evaluation pipelines that leverage LLM-as-a-judge, human reviewers, and custom evaluators to ensure changes actually improve performance. Its observability stack traces every request and highlights failure points, helping teams debug issues and convert problematic interactions into reusable test cases. Product managers, developers, and domain experts can collaborate through shared test sets, annotations, and interactive evaluations directly from the UI. Agenta integrates seamlessly with LangChain, LlamaIndex, OpenAI APIs, and any model provider, avoiding vendor lock-in. By consolidating collaboration, experimentation, testing, and monitoring, Agenta enables AI teams to move from chaotic workflows to streamlined, reliable LLM development.

Agent Control represents a groundbreaking open-source framework designed to manage the behavior of AI agents on a large scale, setting a new benchmark for governance in this domain. It addresses the issue of disjointed and hardcoded checks by providing teams with a unified governance layer that enforces regulations at each step, all managed from a single control interface that can be updated dynamically without altering the agent's underlying code. Developers can easily designate any function as governable by applying the control() decorator, thereby transforming key decision points within an agent into independently regulated control points, each equipped with its own governance policies. When a decorated function runs, Agent Control assesses the input or output against the prevailing policy and generates a response that could be to deny, steer, warn, log, or allow the action. If a denial occurs, the SDK triggers a ControlViolationError, preventing any unsafe actions from being executed. This separation of policies from the actual code empowers developers to strategically position control hooks, while policy teams determine the enforcement specifics of those hooks, ensuring a collaborative approach to governance. The flexibility and robustness of Agent Control make it an invaluable tool for organizations looking to standardize AI agent governance effectively.

Phoenix serves as a comprehensive open-source observability toolkit tailored for experimentation, evaluation, and troubleshooting purposes. It empowers AI engineers and data scientists to swiftly visualize their datasets, assess performance metrics, identify problems, and export relevant data for enhancements. Developed by Arize AI, the creators of a leading AI observability platform, alongside a dedicated group of core contributors, Phoenix is compatible with OpenTelemetry and OpenInference instrumentation standards. The primary package is known as arize-phoenix, and several auxiliary packages cater to specialized applications. Furthermore, our semantic layer enhances LLM telemetry within OpenTelemetry, facilitating the automatic instrumentation of widely-used packages. This versatile library supports tracing for AI applications, allowing for both manual instrumentation and seamless integrations with tools like LlamaIndex, Langchain, and OpenAI. By employing LLM tracing, Phoenix meticulously logs the routes taken by requests as they navigate through various stages or components of an LLM application, thus providing a clearer understanding of system performance and potential bottlenecks. Ultimately, Phoenix aims to streamline the development process, enabling users to maximize the efficiency and reliability of their AI solutions.

Kastra serves as the crucial authorization framework for AI systems, determining the permissions of agents, models, and tools prior to their execution. Positioned along the execution path of all interactions such as prompts, tool calls, shell commands, database operations, and API requests, it evaluates each action based on deterministic, attribute-driven policies, rendering decisions to allow, deny, redact, or escalate in less than a millisecond. In contrast to monitoring solutions that only track AI actions post-execution, Kastra proactively prevents unauthorized activities before they can impact any tool, API, database, or production environment. Its comprehensive control plane integrates a policy engine, edge decision-making capabilities, various integrations, and a tamper-proof evidence vault that securely signs each decision for auditing and replay purposes. Furthermore, with Kastra Edge, local enforcement is extended to developer environments, safeguarding coding agents such as Claude Code, Cursor, and Codex CLI from harmful commands, unauthorized data extraction, unsafe file modifications, and improper tool usage. This proactive approach to authorization not only enhances security but also ensures compliance and accountability in AI-driven processes.

Drools serves as a comprehensive Business Rules Management System (BRMS) that includes a core Business Rules Engine (BRE) and a web-based application for authoring and managing rules, known as Drools Workbench. Additionally, it offers complete runtime support for Decision Model and Notation (DMN) models, adhering to Conformance level 3, along with an Eclipse IDE plugin to facilitate core development tasks. As an open-source solution released under the Apache License 2.0, Drools is developed entirely in pure Java™ and is compatible with any Java Virtual Machine (JVM). Furthermore, it can be readily accessed through the Maven Central repository, making it convenient for developers to integrate into their projects. This accessibility and flexibility highlight its appeal in various business environments.

Tev1 is a rapid decision-making and classification model developed by Together AI, which has been fine-tuned from Qwen3.5 4B. Its user-friendly interface allows for the input of a state, a question, and between 2 to 24 labeled choices, enabling the model to output a single letter that can be mapped back to a semantic key by software. This design is particularly beneficial for various production tasks, such as managing support ticket routing, assessing automated returns, enforcing policy guidelines, sentiment analysis, document categorization, and integrating precise decision-making steps into larger agent workflows. With a parameter count of 4.7B and a 32.8K-token context window, the model operates with non-thinking generation to ensure fast and reliable classification. It has been trained on a diverse set of 37,840 examples covering areas such as intent detection, boolean comprehension, sentiment evaluation, policy application, as well as categorizing news and academic papers. The recommended configuration suggests using a temperature setting of 0 along with a minimal output budget, ensuring that the responses are both consistent and straightforward to interpret. In summary, Tev1 stands out as a versatile tool that efficiently addresses a wide range of classification needs.

LayerLens serves as an autonomous platform dedicated to evaluating AI models, providing insights into their performance through verified benchmarks, prompt-specific outcomes, agentic comparisons, and audit-ready assessments across different vendors. This platform enables teams to conduct side-by-side comparisons of over 200 AI models, utilizing transparent benchmarks and consistent evaluation techniques focused on accuracy, latency, behavior, and practical application in real-world scenarios. Designed for comprehensive model analysis, LayerLens features Spaces that allow teams to organize benchmarks and evaluations, identify strengths in tasks, and monitor performance trends in relevant contexts. The platform also facilitates ongoing evaluations by continuously assessing model updates, prompt modifications, judge changes, and live traces, thereby empowering teams to identify issues like quality regressions, drift, silent failures, contamination, and policy concerns before they impact production. By prioritizing transparency and collaboration, LayerLens ensures that teams can make informed decisions about their AI model choices.

Flow-Like is a locally-operated, open-source workflow automation engine that emphasizes strong typing and allows users to build and execute automation and AI workflows in environments that are self-hosted or offline. By integrating visual, graph-based workflows with deterministic execution, it simplifies the complexities often associated with system maintenance and validation. In contrast to various other tools that depend on untyped JSON, cloud-exclusive backends, or obscure runtime processes, Flow-Like prioritizes explicit and inspectable data flow and execution. This versatility enables workflows to function seamlessly on local machines, private servers, within containers, or on Kubernetes without altering their intended behavior. Built in Rust, the core runtime is optimized for safety, performance, and portability, ensuring it meets high standards. Flow-Like also accommodates event-driven automation, data processing, document ingestion, and AI pipelines, which include typed agent and retrieval-augmented generation (RAG) workflows, utilizing either local or cloud-based models. Ultimately, it is crafted for developers and organizations seeking dependable automation while maintaining comprehensive control over both their data and underlying infrastructure, thereby fostering an environment of transparency and reliability.

With OpenRules®, business professionals can create and evaluate decision models and subsequently collaborate with IT to seamlessly integrate these models into existing information systems. The platform clearly defines all necessary integration points for ease of use. If your organization seeks to automate intricate business logic to enhance operational decision-making in a cost-effective manner, you’ve found the perfect solution. OpenRules® provides tools that empower business analysts to develop, test, and manage Operational Decision Services while working alongside developers for deployment either on-premise or in the cloud. Furthermore, OpenRules® Decision Manager enables business users to create, test, and maintain rules-based decision models that can be effortlessly deployed in various environments, whether cloud-based or on-site. It operates business rules with exceptional performance and scalability. Notably, OpenRules® does not require users to master proprietary graphical interfaces or unique rule languages, allowing them to utilize familiar tools such as MS Excel® or Google Sheets® alongside the standard file manager or OpenRules Graphical Explorer, making the process even more accessible and user-friendly. This focus on simplicity ensures that all team members can contribute effectively to the decision-making process without extensive training.

Kusari’s platform provides "always-on transparency," delivering the essential visibility and insights necessary for your needs. It secures your entire software development lifecycle from start to finish, utilizing open-source GUAC and adhering to open standards. With GUAC, a queryable open-source knowledge graph, you can comprehend the makeup of any software artifact. Before incorporating new artifacts, assess them and establish policies that automatically block risky or vulnerable dependencies from infiltrating your supply chain. By making security the default in your development process, you ensure that developer workflows remain uninterrupted. Kusari seamlessly integrates with your current IDE and CI/CD tools, adapting to your specific environment. Additionally, it automates the best practices for software supply chain security, ensuring each build's integrity and producing the necessary metadata to validate it. This approach not only enhances security but also simplifies compliance efforts for development teams.

Maetra serves as an AI governance control plane tailored for teams managing tool-utilizing AI agents. It identifies agents and their associated repositories, assesses risks based on established frameworks, and reviews potential actions against versioned governance policies prior to execution. Additionally, it facilitates human approvals, monitors prompts and tool interactions for runtime vulnerabilities, ensures ongoing tasks remain aligned with authorized objectives, and maintains unalterable records of decisions for auditing purposes. The system features several modules, including Govern, Secure, Task Guard, Interaction Guard, Discover, Comply, Audit, and Decision Intelligence, which can function independently or as part of a cohesive control plane, enhancing overall operational efficiency and compliance. Ultimately, this integrated approach ensures robust management and oversight of AI agent activities within organizational frameworks.

Cedar is an open-source policy language and evaluation framework created by AWS to enhance fine-grained access control within applications. This tool allows developers to craft clear and succinct authorization policies, effectively separating access control mechanisms from the core application logic. Cedar accommodates various authorization paradigms, such as role-based access control and attribute-based access control, which empowers developers to write expressive and analyzable policy definitions. The design of Cedar prioritizes both readability and performance, ensuring that the policies remain understandable while also being efficient in their enforcement. By utilizing Cedar, applications can achieve precise authorization decisions, which in turn improves both security and maintainability. Furthermore, the policy structure is optimized for quick access and supports swift, scalable real-time evaluations with consistent low latency. Additionally, Cedar facilitates the use of analytical tools that can enhance your policies and verify that your security framework aligns with your expectations, thus fostering greater confidence in your security posture. Overall, Cedar represents a pivotal advancement in managing application access control efficiently.

Tuning Engines serves as a comprehensive AI control and governance framework designed for teams engaged in building production intelligence that spans various models, agents, tools, and specialized systems. This platform consolidates the entire AI lifecycle into a single, regulated environment, encompassing aspects like inference, model routing, fallback strategies, fine-tuning tasks, datasets, evaluations, model imports and exports, custom models, agents, MCP servers, reusable skills, guardrails, AGT YAML policies, data capture, runtime tracing, usage analytics, API management, billing, team roles, and numerous integrations. Developers benefit from APIs compatible with OpenAI, routes aligned with Anthropic, CLI workflows, MCP access, and seamless coding-agent integrations, along with a comprehensive resource catalog for models, agents, tools, and skills. Moreover, teams have the ability to link various AI workflows, including Claude Code, OpenCode, Aider, Cline, Roo, Continue.dev, Cursor, VS Code, Windsurf, and more, all through a singular, governed platform that enhances collaboration and efficiency.

OpenText Process Automation is a powerful low-code development platform for building and managing business process automation and dynamic case management solutions tailored to evolving customer, employee, and partner demands. It accelerates application development by leveraging intuitive drag-and-drop tools, reusable building blocks, and pre-built accelerators, cutting down time-to-market and development expenses. The platform seamlessly connects and orchestrates data flows across various enterprise systems, enabling end-to-end automation and more efficient workflows. With embedded business intelligence, users gain real-time, actionable insights through customizable reports that simplify decision-making. The solution supports collaborative development, allowing business experts and developers to work together and increase agility. Its cloud-native architecture offers deployment flexibility on-premises, hybrid, or fully in the cloud, adapting to organizational strategies. OpenText Process Automation also includes mobile-first design principles, empowering users to access and manage workflows from any device. It integrates easily with enterprise content management and robotic process automation tools to deliver comprehensive process optimization.

Enhance the security of your OpenAI interactions by implementing enterprise-grade features tailored for robust oversight. While OpenAI's LLM APIs offer remarkable capabilities, they often fall short in providing the detailed control and transparency that larger organizations require. Usage Panda addresses these shortcomings effectively. It scrutinizes security protocols for each request prior to submission to OpenAI, ensuring compliance. Prevent unexpected charges by restricting requests to those that stay within predetermined cost limits. Additionally, you can choose to log every request, along with its parameters and responses, for thorough tracking. The platform allows for the creation of an unlimited number of connections, each tailored with specific policies and restrictions. It also empowers you to monitor, censor, and block any malicious activities that seek to manipulate or expose system prompts. With Usage Panda's advanced visualization tools and customizable charts, you can analyze usage metrics in fine detail. Furthermore, notifications can be sent to your email or Slack when approaching usage caps or billing thresholds, ensuring you remain informed. You can trace costs and policy breaches back to individual application users, enabling the establishment of user-specific rate limits to manage resource allocation effectively. This comprehensive approach not only secures your operations but also enhances your overall management of OpenAI API usage.

Surf.new is a free and open-source platform designed for experimenting with AI agents that can navigate the web. These agents mimic human behavior while browsing and interacting with websites, simplifying tasks such as automation and online research. Whether you are a developer assessing web agents for potential deployment or an individual seeking to streamline repetitive activities like monitoring flight prices, gathering product data, or making reservations, Surf.new offers an easy-to-use environment for testing and evaluating the performance of web agents. Highlighted Features: Effortless AI Agent Framework Switching: With a simple button click, users can toggle between various frameworks, including a Browser-use option, an experimental Claude Computer-use-based agent, and seamless integration with LangChain, facilitating diverse experimentation methods. Wide Range of AI Model Support: This platform is compatible with renowned models such as Claude 3.7, DeepSeek R1, OpenAI models, and Gemini 2.0 Flash, enabling users to select the most suitable option for their needs. Additionally, the user-friendly interface of Surf.new encourages exploration and innovation, making it an ideal choice for anyone interested in the capabilities of AI-driven web agents.

Higson is an advanced business rules engine that empowers organizations to efficiently handle intricate decision-making processes and streamline rule-based operations with rapid execution speeds and a user-friendly interface tailored for business users. By decoupling business rules from application code, it enables users to easily configure products, pricing structures, and decision logic via a web-based Studio without needing extensive programming skills, thereby minimizing dependence on developers and expediting the time to market. Features such as sophisticated version control, a user-friendly tree-structured rule editor, and validation tools like the tester and mass tester ensure that changes can be rigorously tested before they go live. Higson also includes capabilities for visual rule modeling, integration with AI models, decision tables, and Groovy functions, while supporting import/export functionalities with Excel. Furthermore, it facilitates integration with existing systems using REST or Java APIs, and it securely stores configurations in widely-used SQL databases. The runtime engine is specifically engineered for real-time decision-making, adeptly processing thousands of API calls per second along with managing extensive datasets, ensuring that organizations can respond swiftly to evolving business needs. Ultimately, Higson enhances operational efficiency and agility, enabling organizations to thrive in a rapidly changing environment.

All your customer management needs can be met with a fast and flexible decision engine. Paris is easy to use and adopt due to its intuitive user interface. Paris is a highly configurable and flexible decision engine system that allows for maximum flexibility and growth. You can implement models, both machine learning and traditional, across multiple products and decision science applications. These include marketing, credit scoring, customer management, collections, and marketing. It can be audited with all input, derived, and output variables available to any reporting suite. Software that is flexible and business-oriented Visualization and interaction with decision trees Analysis and design of an 'open box strategy'. Continuous improvement and strategy testing Route planning and decision making that is reliable and accurate. Multi-bureau and open bank support.

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.

The Decisions Platform is a no code business automation solution that focuses primarily on data handling, process automation and business rule execution. The Decisions Platform includes a workflow engine, a form designer, form designer, report/or dashboard builder and an open API and SDK. It offers a complete business process management solution for large companies and software company partners. Decisions is a visual, drag-and-drop, no-code design technology that was built and tested to help organizations automate a variety of business processes.

Emly Labs, an AI framework, is designed to make AI accessible to users of all technical levels via a user-friendly interface. It offers AI project-management with tools that automate workflows for faster execution. The platform promotes team collaboration, innovation, and data preparation without code. It also integrates external data to create robust AI models. Emly AutoML automates model evaluation and data processing, reducing the need for human input. It prioritizes transparency with AI features that are easily explained and robust auditing to ensure compliance. Data isolation, role-based accessibility, and secure integrations are all security measures. Emly's cost effective infrastructure allows for on-demand resource provisioning, policy management and risk reduction.

Galileo is an AI observability and eval engineering platform designed to help teams evaluate, monitor, guardrail, and improve AI agents and applications. The platform connects the offline testing process with production governance, turning evals into guardrails that can control agent actions, tool access, escalation paths, and safety behavior. Galileo helps teams capture ground truth from synthetic data, development data, live production data, and subject matter expert annotations. Its evaluation capabilities include RAG evals, agent evals, safety evals, security evals, and custom evals that can be tuned to specific environments. Galileo’s Luna models distill optimized LLM-as-judge evaluators into compact models that run at lower cost and latency for production-scale monitoring. The insights engine analyzes traces, prompts, functions, context, datasets, models, and agent behavior to identify failure modes and recommend fixes. Teams can use Galileo to detect hallucinations, tool-selection failures, drift, bias, unsafe outputs, and other reliability issues before they harm production experiences. Deployment options include SaaS, virtual private cloud, and on-premises environments. By combining observability, eval engineering, production guardrails, ground-truth datasets, Luna models, insights, and enterprise deployment options, Galileo helps organizations build more reliable AI systems.

Utilize BenchLLM for real-time code evaluation, allowing you to create comprehensive test suites for your models while generating detailed quality reports. You can opt for various evaluation methods, including automated, interactive, or tailored strategies to suit your needs. Our passionate team of engineers is dedicated to developing AI products without sacrificing the balance between AI's capabilities and reliable outcomes. We have designed an open and adaptable LLM evaluation tool that fulfills a long-standing desire for a more effective solution. With straightforward and elegant CLI commands, you can execute and assess models effortlessly. This CLI can also serve as a valuable asset in your CI/CD pipeline, enabling you to track model performance and identify regressions during production. Test your code seamlessly as you integrate BenchLLM, which readily supports OpenAI, Langchain, and any other APIs. Employ a range of evaluation techniques and create insightful visual reports to enhance your understanding of model performance, ensuring quality and reliability in your AI developments.

SignaKit serves as a comprehensive platform for engineering teams, providing features like feature flags, A/B testing, and experimentation, which empower them to manage software releases effectively without the constraints of per-seat fees or vendor lock-in. The evaluation of flags takes place locally within the application process, utilizing a cached configuration delivered via AWS CloudFront, ensuring swift sub-millisecond evaluations that eliminate the need for network roundtrips during critical operations. Additionally, the bucketing mechanism is deterministic through the use of MurmurHash3, guaranteeing that users consistently receive the same variant across different sessions and devices. Teams have the capability to implement both boolean and multivariate flags, configure percentage rollouts, target audiences based on various user attributes, and activate instant kill switches for immediate rollbacks in urgent situations. The integrated A/B testing feature assesses statistical significance with customizable experiment snapshot intervals, while the multi-armed bandit optimization feature adeptly directs traffic towards the winning variant as data is gathered — all of these functionalities are available on every plan, including the Free option. This makes SignaKit an ideal solution for teams seeking flexibility and reliability in their software release processes.

doteval serves as an AI-driven evaluation workspace that streamlines the development of effective evaluations, aligns LLM judges, and establishes reinforcement learning rewards, all integrated into one platform. This tool provides an experience similar to Cursor, allowing users to edit evaluations-as-code using a YAML schema, which makes it possible to version evaluations through various checkpoints, substitute manual tasks with AI-generated differences, and assess evaluation runs in tight execution loops to ensure alignment with proprietary datasets. Additionally, doteval enables the creation of detailed rubrics and aligned graders, promoting quick iterations and the generation of high-quality evaluation datasets. Users can make informed decisions regarding model updates or prompt enhancements, as well as export specifications for reinforcement learning training purposes. By drastically speeding up the evaluation and reward creation process by a factor of 10 to 100, doteval proves to be an essential resource for advanced AI teams working on intricate model tasks. In summary, doteval not only enhances efficiency but also empowers teams to achieve superior evaluation outcomes with ease.

Amazon Bedrock Guardrails is a flexible safety system aimed at improving the compliance and security of generative AI applications developed on the Amazon Bedrock platform. This system allows developers to set up tailored controls for safety, privacy, and accuracy across a range of foundation models, which encompasses models hosted on Amazon Bedrock, as well as those that have been fine-tuned or are self-hosted. By implementing Guardrails, developers can uniformly apply responsible AI practices by assessing user inputs and model outputs according to established policies. These policies encompass various measures, such as content filters to block harmful text and images, restrictions on specific topics, word filters aimed at excluding inappropriate terms, and sensitive information filters that help in redacting personally identifiable information. Furthermore, Guardrails include contextual grounding checks designed to identify and manage hallucinations in the responses generated by models, ensuring a more reliable interaction with AI systems. Overall, the implementation of these safeguards plays a crucial role in fostering trust and responsibility in AI development.

Shieldstral is an innovative multimodal safety classifier with a 3B parameter open-weight structure, adept at assessing text, images, and combined text-plus-image content based on dynamically defined policies during inference. Rather than adhering to a static set of harm categories, it approaches moderation as a binary question-and-answer format: users submit a contextual instruction outlining the evaluation criteria and strictness, pose a yes-or-no safety inquiry, and present the content for assessment. The model processes the “yes” and “no” logits to generate a continuous, calibrated safety score, enabling applications to prioritize or rank outcomes based on confidence levels instead of relying on a single categorical label. This design effectively integrates prompt classification, response moderation, refusal detection, toxicity assessment, and multimodal safety evaluation into a singular interface, empowering teams to modify policies without the need for model retraining. Shieldstral's versatility allows it to analyze prompts, responses, pairs of prompts and responses, images, and images paired with text, making it a comprehensive tool for safety evaluation. As such, it represents a significant advancement in the field of content moderation.

FlowCentric Processware allows businesses to quickly create process-driven applications using a business process management system. FlowCentric Processware allows users to manage complex business processes across multiple devices, systems, departments. FlowCentric Processware offers activity monitoring dashboards, which allow users to gain greater insight into their processes. FlowCentric Processware is the ideal tool for organisations looking to embrace digital transformation, innovate quickly and achieve results quickly. FlowCentric Processware is used by companies to create flexible process-driven solutions, extend the life of ERP systems, and add meaningful action to data collected from IoT devices. This software is ideal for companies with 100+ employees who want to digitize unlimited processes, increase operational efficiency, and enforce regulatory controls.

LogicGem, an AI-enabled logic processer and decision table analysis software, is a tool that analyzes decision tables. It is designed for software developers to create and verify rules using decision table methodology. LogicGem allows you to easily fix any rules that are missing, ambiguous or contradictory. LogicGem allows programmers to convert business rules in a programming language, which is then integrated into the software application. Business analysts can use LogicGem for the development of concise business rules that represent actual or proposed business processes.

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.

Create business applications with unparalleled agility and revolutionize your organization. iLeap is a Low-Code Application Development Platform tailored for multinational consumer electronics manufacturers and distributors, empowering enterprises to quickly develop top-tier cloud-based applications with remarkable speed and effectiveness. Our goal at iLeap is to equip companies with the tools to foster innovation internally, enabling them to lead the charge in digital transformation instead of being guided solely by technologists. By utilizing intuitive drag-and-drop editors, iLeap significantly boosts developer productivity and reduces the need for rework. You can easily customize various modules, business rules, and data sets without starting from scratch. From the moment your technical leaders approve the project, you can create applications that are responsive and adaptable. Furthermore, applications built with iLeap are device-agnostic, allowing business users to work effortlessly and efficiently at any time and from anywhere. This flexibility enhances collaboration and ensures that teams remain connected and productive, regardless of their location.

Progress Corticon enhances your current applications by streamlining intricate decision-making processes, potentially decreasing development and modification cycles by as much as 90%. It offers a user-friendly interface that allows both IT professionals and business specialists to handle their digital decision-making complexities without the need for programming. By leveraging Progress Corticon, organizations can create a more efficient digital landscape, automating sophisticated decisions without any coding requirements. Tailoring experiences for individual customers ensures that their unique needs are addressed effectively. For instance, a healthcare provider could utilize Corticon to automate the process of applying for healthcare benefits or to assist in customizing a diet plan following a cardiac incident. By personalizing the customer journey, you not only simplify their access to relevant information but also enhance their overall decision-making experience while navigating available options. This approach ultimately fosters greater customer satisfaction and loyalty.

ML Junction provides developers with a unified API to interface with various AI model providers seamlessly. It accommodates compatibility with SDKs from OpenAI and Anthropic, features capability-aware routing, and includes mechanisms for retries and fallbacks, along with controls for cost and privacy at the request level. Each request generates a detailed receipt outlining the chosen route, the alternatives that were taken into account, the policies applied, and the total cost incurred. In addition, ML Junction facilitates model evaluations, enhances agent observability, and offers seamless integration with LangChain. Its pricing structure is based on usage through prepaid credits, which can either include the provider’s rates plus an additional routing fee or allow users to utilize their own provider keys. Specifically designed for teams engaged in developing AI applications, it ensures a streamlined and efficient workflow. Furthermore, ML Junction aims to simplify the integration process for developers, making it easier to leverage the power of multiple AI models in their projects.

Effective communication with customers is essential, not merely a luxury, as it directly influences your financial performance. When customers are happy, they tend to purchase more products and services, leading to enhanced business outcomes. Strategic customer decision-making serves as a significant catalyst for improving overall business performance. By implementing well-targeted decisions throughout the Customer Life Cycle, organizations can significantly boost their profitability. To expedite progress and enhance returns on investment, it is crucial to adopt efficient and impactful methods for crafting and implementing insightful decision strategies. In order to remain competitive and responsive to ever-changing business landscapes, businesses must embrace flexible approaches to drive transformation. PowerCurve's Strategy Management integrates the design and execution of strategy, enabling organizations to detect early indicators of shifts in market and customer behaviors, allowing for swift adjustments to decision-making strategies to mitigate risks and seize new opportunities. This proactive approach not only safeguards against potential setbacks but also positions businesses to thrive in a dynamic marketplace.

GxDash™ offers a centralized command control system designed for CxO-level decision making, featuring an integrated enterprise dashboard that spans all technology tiers. This solution is enhanced by our consultants who deliver a holistic approach to decision making, facilitating automation for tasks such as creating dependency maps, conducting predictive analysis, and generating code and test cases. By leveraging this enterprise dashboard, organizations benefit from reduced risks as it ensures thorough test case coverage and accelerates the software development timeline significantly. Additionally, we provide a comprehensive suite of resources, including process handbooks, training materials, marketing collateral, and models for engagement and deployment, to support our clients in fully optimizing the capabilities of GxDash®. This approach empowers businesses to enhance their operational efficiency while navigating the complexities of technology management.

Sapiens Decision for Consumer & Commercial Banking, previously known as Sapiens DECISION, focuses on minimizing the cost associated with change. This solution empowers banks to swiftly adjust their operations to meet the challenges of digital transformation, evolving regulations, customer expectations, and heightened competition through a model-driven development (MDD) framework. By utilizing the MDD methodology, Sapiens Decision allows business professionals to articulate business logic using intuitive models that are easy to understand. Before any logic is put into use, businesses can evaluate it, ensuring it meets their needs. Once the code is automatically generated in languages like Java, it can be seamlessly deployed into live production systems. With Sapiens Decision, the bank’s business domain plays a crucial role in shaping the design, execution, analysis, testing, and optimization of decision-making processes. This streamlined approach significantly reduces the timeframe for implementation from months or years to just days or weeks, ensuring that business logic is consistently enforced across all enterprise applications and enhancing overall operational efficiency. Furthermore, this capability supports ongoing adjustments, making it easier for banks to stay competitive in a fast-paced market.

As the premier rules authoring tool from FICO and the top decision rules management platform globally, FICO® Blaze Advisor® enhances management of high-volume operational decisions. This innovative solution offers businesses in various sectors a scalable approach that fosters unparalleled agility and effectiveness in making informed, transparent, and superior business choices. With Blaze Advisor, business users benefit from diverse techniques for authoring, testing, deploying, and managing rules, including decision trees, scorecards, decision tables, graphical decision flows, and tailored templates. Additionally, it allows for the monitoring of business performance through user-defined events, which lays the groundwork for strategic orchestration and champion/challenger scenarios. Its robust capabilities for impact and decision analysis not only provide clarity but also offer multiple avenues for developing and refining the strategies critical to achieving success. Ultimately, Blaze Advisor equips organizations with the tools they need to stay ahead in an ever-evolving marketplace.

Cloptima is an innovative platform that integrates AI and cloud FinOps, offering governance for LLM expenditures, insights into multicloud costs, optimization for Kubernetes, analysis of queries, and controls on engineering costs within a unified framework. Through its AI gateway, teams can securely utilize their own credentials from OpenAI, Anthropic, Gemini, Vertex AI, and Amazon Bedrock, applying a range of protections like encrypted controls, virtual keys, model policies, token limits, budgets, guardrails, and attribution before any requests are sent to the providers. The platform's spend analytics provide a comprehensive breakdown of usage categorized by provider, model, team, application, environment, user, agent session, tool, workflow, and other dimensions, while the agent controls monitor retries, loops, tool interactions, and the potential for runaway costs. Additionally, exact and semantic response caching can help minimize redundant usage, whereas intelligent routing capabilities allow for the redirection of eligible traffic to more cost-effective or faster models, with the option for canary rollout and rollback if there are regressions in quality, latency, or error rates. This holistic approach ensures that organizations can effectively manage their AI-related expenditures while maximizing efficiency and performance across their operations.