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Evertune is the Generative Engine Optimization (GEO) platform that helps brands improve visibility in AI search across ChatGPT, AI Overview, AI Mode, Gemini, Claude, Perplexity, Meta, DeepSeek and Copilot. We're building the first marketing platform for AI search as a channel. We show enterprise brands exactly where they stand when customers discover them through AI — then give them the precise playbook to show up stronger. This is Generative Engine Optimization, also known as AI SEO. Using applied AI and data science at scale, we give brands statistical confidence in our actionable insights. We decode what gets brands mentioned more and ranked higher, provide reliable brand monitoring and competitive intelligence, then deliver actionable content strategies that move the needle. Our AI SEO and AI search engine optimization tools are built for how LLMs actually work. Why Leading Enterprise Marketers Choose Evertune: Data Science at Scale: We prompt across every major LLM at volumes that capture response variations and ensure statistical significance for comprehensive brand monitoring and competitive intelligence. Actionable Strategy, Not Just Dashboards: Specific content, messaging and distribution tactics that increase your AI search visibility. Dedicated Customer Success: Hands-on training and strategic guidance to turn insights into improved performance in AI search. Built for AI search as a channel: Organic visibility today, paid advertising and commerce tomorrow. Proven Leadership: Founded by The Trade Desk veterans who pioneered data-driven digital advertising. Backed by data scientists from OpenAI, Meta and other AI leaders.

HubSpot AEO is a specialized optimization tool designed to help businesses increase their visibility in AI-generated search results. It focuses on how brands are represented in answers provided by AI platforms such as ChatGPT, Gemini, and Perplexity. The platform provides a visibility score that measures how frequently a business appears in AI responses and evaluates the sentiment of those mentions. It also identifies and tracks relevant prompts that potential customers are using when interacting with AI tools. HubSpot AEO analyzes the sources, domains, and content types that influence AI-generated answers. This allows businesses to understand what drives their presence in AI search results. The platform provides clear, prioritized recommendations to improve visibility and performance. Integration with HubSpot’s CRM enhances insights by using customer data to refine optimization strategies. The tool simplifies the process of adapting to AI-driven search trends without requiring deep technical expertise. Overall, HubSpot AEO helps businesses stay competitive as AI becomes a primary discovery channel.

AthenaHQ is a powerful platform focused on Generative Engine Optimization (GEO), helping brands improve their AI search visibility and brand perception across AI-powered search engines. It offers tools to track brand mentions, identify gaps in AI-generated content, and enhance content to align with AI’s evolving preferences. With features like daily tracking, competitor analysis, and source intelligence, AthenaHQ provides actionable insights to help businesses stay relevant in an AI-dominated search landscape. The platform's AI-powered capabilities enable businesses to optimize content and drive more meaningful engagement through generative search.

AuthorityTech is the world’s first AI-native Machine Relations agency and platform, engineered to position ambitious brands inside the Tier-1 publications that AI search engines inherently trust, retrieve, and cite. While conventional PR convinces humans through retainer-based effort, AuthorityTech optimizes for the new primary reader—the machine—through a 100% outcome-based, pay-per-placement model. This ensures leading answer engines, including ChatGPT, Perplexity, Gemini, and Google AI Overviews, can seamlessly index the brand, map it to its rightful category, and cite it when buyers ask high-intent questions. Coined in 2024 by Founder and CEO Jaxon Parrott, Machine Relations is the discipline of making a brand discoverable and citable by AI systems. Parrott built AuthorityTech to execute the five-layer Machine Relations stack: Earned Authority, Entity Clarity, Citation Architecture, Distribution, and Measurement. This unifies GEO, AEO, AI SEO, and digital PR into a single ecosystem for building machine trust. Cofounder and Chief Growth Officer Christian Lehman operationalizes this strategy, deploying the methodology at scale. Leveraging a direct network of over 1,600 Tier-1 publications, AuthorityTech has secured thousands of AI-cited articles for 200+ clients, including 27 unicorn startups, to guarantee sustainable AI visibility and measurable share of citation. The agency executes this via a three-part framework: Map: Analyzing target categories and competitor LLM prompts. Match: Aligning brand narratives with authoritative outlets. Place: Securing guaranteed placements through relationship-led outreach.

Concord Horizon is an AI native contract platform built from a complete rewrite of Concord’s technology, applying ten years of experience to a modern architecture for faster and more accurate contract work. The redesigned interface offers light and dark mode, collapsible navigation, full screen focus, custom columns, advanced filtering, and consistent tables across modules. AI Copilot supports natural language questions, contract summaries, key point extraction, and fast portfolio insights, while AI Search adds lexical and semantic search with improved performance and multi actions on results. MCP brings contract intelligence into AI tools like ChatGPT and Claude for summaries, tables, or automated monitoring. Concord applies a strict zero data retention policy with AI partners and never uses customer data to train AI models .

Engineering teams shipping with AI have a new bottleneck: validation. Code output has accelerated. Quality hasn't. Checksum closes the gap. Checksum is a continuous quality platform with a suite of AI agents that handle testing end-to-end, at every stage of the development lifecycle. Where most tools wait for a human to trigger them, Checksum runs autonomously in the background, generating tests, executing them, and repairing failures without manual intervention. Seventy percent of test failures are resolved automatically through real-time auto-recovery. The platform covers every layer: end-to-end UI flows via Playwright, API endpoint chains, and targeted CI tests scoped to exactly what changed in a PR. All tests land as real code in your repository and are delivered as standard Playwright, owned by your team. Checksum is fine-tuned on 1.5+ million test runs and integrates natively with Cursor, Claude Code, and 100+ AI coding agents. Type /checksum and your coding agent's output gets tested before it ever reaches review. Generation and healing happen on Checksum's cloud infrastructure which means no LLM tokens consumed, no local resources required. The result: test suites that stay green as the product evolves, fewer regressions reaching production, and release confidence that scales alongside AI output.

Kitecyber: Data & Gen AI Security, Built on the Endpoint Your most sensitive data leaves through browsers, Gen AI prompts, SaaS uploads, and clipboards — faster than any network tool can catch it. Kitecyber stops that at the source, with a single lightweight agent that runs directly on the endpoint and acts the instant data is touched, not after it's already gone. Because it lives on the device, Kitecyber has full context — device, OS, process, data, user, and network activity together, in real time. That's the vantage point network- and cloud-only tools simply don't have. Data security that keeps up with your data. Kitecyber classifies sensitive information with LLM-powered, context-aware intelligence across 80+ categories — PII, PHI, PCI, source code, IP — at over 90% accuracy, not brittle keyword matching. It tracks data lineage through screenshots, encoding, and file conversion that defeat traditional scanners, and blocks policy violations inline, before data ever leaves the endpoint. Gen AI security for the age of AI agents. Kitecyber tracks sensitive data pasted or uploaded into tools like ChatGPT, Claude, and Gemini and stops it in real time. It discovers shadow AI reaching your devices and extends visibility to the AI agents now acting on your users' behalf — the blind spot identity- and network-based tools were never built to see. Trusted and proven. Kitecyber secures fast-growing fintech, BFSI, and SMB organizations in highly regulated environments, partnering with GRC leaders like Scrut Automation to unify security and compliance. It's SOC 2 Type II compliant, deploys in about a day, and delivers enterprise-grade protection without enterprise complexity. See what full-context data and Gen AI security looks like. Learn more at kitecyber.com.

Gemini Enterprise Agent Platform is Google Cloud’s next-generation system for designing and managing advanced AI agents across the enterprise. Built as the successor to Vertex AI, it unifies model selection, development, and deployment into a single scalable environment. The platform supports a vast ecosystem of over 200 AI models, including Google’s latest Gemini innovations and popular third-party models. It offers flexible development tools like Agent Studio for visual workflows and the Agent Development Kit for deeper customization. Businesses can deploy agents that operate continuously, maintain long-term memory, and handle multi-step processes with high efficiency. Security and governance are central, with features such as agent identity verification, centralized registries, and controlled access through gateways. The platform also enables seamless integration with enterprise systems, allowing agents to interact with data, applications, and workflows securely. Advanced monitoring tools provide real-time insights into agent behavior and performance. Optimization features help refine agent logic and improve accuracy over time. By combining automation, intelligence, and governance, the platform helps organizations transition to autonomous, AI-driven operations. It ultimately supports faster innovation while maintaining enterprise-grade reliability and control.

Fathom is an AI meeting assistant that helps users capture, summarize, search, and act on meetings with less manual work. The platform creates accurate transcripts, instant summaries, action items, and follow-up notes so users can focus on live conversations instead of taking notes. Fathom supports both traditional meeting capture and bot-free capture through its desktop app. Teams can use Fathom as a shared source of truth across customer calls, internal meetings, strategy sessions, and project conversations. Ask Fathom lets users search across meetings and ask questions about conversations, decisions, commitments, risks, and next steps. The platform also supports topic monitoring so important moments and signals are easier to find. Fathom syncs meeting notes, insights, and action items into tools such as Slack, Salesforce, HubSpot, Notion, Asana, Gmail, Zoom, Google Meet, Microsoft Teams, ChatGPT, Claude, Zapier, and API or MCP workflows. It supports security and compliance needs with SOC 2 Type II, GDPR, HIPAA compliance, SSO, and SCIM. By combining AI notetaking, bot-free capture, transcripts, summaries, integrations, search, and workflow automation, Fathom helps teams move from meetings to execution faster.

Most enterprises can report what AI cost them. Far fewer can say which team owns it, whether it was approved, or what it returned. FinOpsly closes that gap. The platform governs AI spend on the same cost model that carries the cloud, data platform and SaaS an AI workload consumes, so a business unit sees the full cost of an AI initiative instead of four disconnected bills. Capabilities include: Cost estimation before deployment. Model an architecture and get a priced workload across model APIs, GPU capacity, warehouse consumption and storage, with the assumptions on screen. Weigh model choices against consumption you have actually measured. Attribution that holds up in a chargeback cycle. Spend resolves to owners, teams, applications, business units and customers through hierarchies nine or more levels deep. Tagging is standardized across providers, keys and resources are labeled in bulk from plain-language rules, and whatever remains unattributed is published as a number, not absorbed. Guardrails that act. Set budgets by project, team or API key. Catch anomalies with root cause and route them to whoever owns the resource. Surface waste that provider tooling misses, using FinOpsly's own detection models. Plan commitments across AWS, Azure and Google Cloud. Park idle compute on approved schedules, reversibly. Financial results you can defend. Automated chargeback in a single cycle. Savings measured as what reached run-rate against a no-action baseline. Unit economics down to cost per call, per active user and per customer served. For technology and finance leaders accountable for what AI spend returns.