Alternatives to KYDE
Compare KYDE alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to KYDE in 2026. Compare features, ratings, user reviews, pricing, and more from KYDE competitors and alternatives in order to make an informed decision for your business.
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Gemini Enterprise Agent Platform is a comprehensive solution from Google Cloud designed to help organizations build, scale, govern, and optimize AI agents. It represents the evolution of Vertex AI, combining advanced model development with new capabilities for agent orchestration and integration. The platform provides access to over 200 leading AI models, including Google’s Gemini series and third-party options like Anthropic’s Claude. It enables teams to create intelligent agents using both low-code and code-first development environments. With features like Agent Runtime and Memory Bank, businesses can deploy long-running agents that retain context and perform complex workflows. The platform emphasizes security and governance through tools like Agent Identity, Agent Registry, and Agent Gateway. It also includes optimization tools such as simulation, evaluation, and observability to ensure consistent agent performance.
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BAND
BAND.ai
BAND builds enterprise-grade interaction infrastructure for distributed AI agents. Its platform enables real-time, multi-peer collaboration across agents and humans, while providing a runtime control plane that enforces policy, authority boundaries, and visibility across heterogeneous systems. BAND supports developers, engineering teams, and enterprise platform leaders operating multi-agent ecosystems across internal systems, SaaS platforms, and partner environments. -
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asqav
asqav
asqav is an AI governance and security platform designed to make AI agents audit-ready by providing real-time monitoring, enforcement, and verifiable proof of every action taken by an agent. It introduces a lightweight SDK that allows developers to integrate governance directly into their agents in just a few lines of code, enabling continuous oversight across the full lifecycle of AI operations. It includes behavioral monitoring to detect issues such as drift, rate limits, and scope violations, along with advanced threat detection that identifies prompt injections, exposure of sensitive data, toxic outputs, and other risks. It enforces policy through configurable “policy gates,” which apply per-agent rules, preflight checks, and dynamic approvals before actions are executed, ensuring that agents operate within defined boundaries. asqav also provides automated incident response capabilities, including the ability to suspend, quarantine, or escalate risky agents.Starting Price: $39 per month -
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OpenBox
OpenBox
OpenBox is an enterprise-grade AI governance platform designed to make AI systems transparent, auditable, and safe to deploy at scale by enforcing real-time oversight across every agent action and system interaction. It provides a unified governance layer that connects identity, policy, risk, and compliance into a single runtime system, eliminating the fragmentation typically found across multiple tools and enabling organizations to standardize control over AI behavior. It integrates directly into existing AI workflows through a lightweight SDK, requiring no architectural changes, and immediately delivers full visibility into how AI agents operate, make decisions, and interact with other systems. OpenBox monitors and evaluates every action before execution, applying policy enforcement and regulatory checks in real time to prevent non-compliant or risky behavior rather than reacting after errors occur.Starting Price: Free -
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JetStream Security
JetStream
JetStream Security is a security-first AI governance platform designed to give enterprises full visibility, control, and accountability over their AI systems by turning them from opaque, fragmented tools into managed, traceable infrastructure. It acts as a centralized control plane that connects identity, runtime governance, observability, and financial oversight into a single system, allowing organizations to “see every AI action, tie actions to accountable owners, [and] keep workflows inside approved boundaries” while enforcing policy at runtime. It introduces agentic identity, binding human, agentic, and non-human identities to specific actions and access permissions, ensuring every invocation, tool call, or workflow can be traced and governed through least-privilege access principles. Through continuous runtime governance, JetStream compares live AI behavior against approved blueprints, using immutable logging and real-time observability to detect drift. -
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OpenWeave
Seven Olives
OpenWeave is execution governance for AI agents and autonomous systems — a server-enforced state machine that controls what AI agents can do and when. You define workflows as states, transitions, and who may trigger them; the backend enforces every transition with a hard 403, and critical states sit behind human approval gates that block bots until a human signs off. Monitoring tells you what agents did; OpenWeave prevents what they shouldn't do, before it happens. Agents discover allowed transitions from the API instead of hardcoding them, every bot has a verifiable identity, and every change is written to an immutable audit trail. Integrates over a REST API and a remote MCP server. Built for AI-agent developers, AgentOps/MLOps and platform teams.Starting Price: $29/month -
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Prisma AIRS
Palo Alto Networks
Prisma AIRS AI Runtime Security is a purpose-built solution designed to protect LLM-powered applications, agents, models, and data during live operation, delivering real-time visibility, assurance, and governance across the entire AI lifecycle. It monitors AI behavior continuously, enforcing safeguards that detect and block threats traditional security tools cannot see, such as prompt injection, malicious code, toxic outputs, data leakage, and unsafe or unauthorized actions. It enables organizations to discover all AI assets in use, including shadow AI, and understand how agents, apps, and models interact across environments. It continuously assesses risk by testing AI systems, controlling permissions, and tracking security posture in real time, while integrating controls that prevent manipulation and exposure during runtime interactions. With adaptive protection, it defends against evolving and zero-day threats, using real-time analysis of inputs, outputs, and execution. -
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Barndoor.ai
Barndoor.ai
Barndoor is a data and access management layer designed to secure how artificial intelligence systems interact with enterprise data and infrastructure. It acts as a centralized control plane that governs AI agents and applications, allowing organizations to define policies, enforce access rules automatically, and maintain full visibility over how AI tools operate across business systems. Instead of relying only on traditional identity-based permissions, Barndoor introduces context-aware governance, enabling administrators to control what actions an AI agent can perform based on factors such as the user operating the agent, the system being accessed, the type of data involved, and the specific task being attempted. It evaluates every AI request in real time and enforces policies before an action is executed, preventing unsafe or unauthorized operations from reaching internal systems or modifying sensitive information.Starting Price: $500 per month -
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MintMCP
MintMCP
MintMCP is an enterprise-grade Model Context Protocol (MCP) gateway and governance platform that provides centralized security, observability, authentication, and compliance controls for AI tools and agents connecting to internal data, systems, and services. It lets organizations deploy, monitor, and govern MCP infrastructure at scale, giving real-time visibility into every MCP tool call, enforcing role-based access control and enterprise authentication, and maintaining complete audit trails that meet regulatory and compliance needs. Built as a proxy gateway, MintMCP consolidates connections from AI assistants like ChatGPT, Claude, Cursor, and others to MCP servers and tools, enabling unified monitoring, blocking of risky behavior, secure credential management, and fine-grained policy enforcement without requiring each tool to implement security individually. -
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Preloop
Preloop
Preloop is the open source AI agent control plane for agents that take real actions. It combines an MCP firewall for tool access, an AI model gateway for cost, safety, and attribution, policy-as-code with human approvals, runtime session observability, and audit trails in a single self-hostable platform. AI agents can deploy code, change infrastructure, move money, touch production data, and burn model spend in seconds, so Preloop helps teams control what agents can do, how much they spend, and which actions require human approval. It works with OpenClaw, Hermes, Claude Code, Codex CLI, Cursor, Gemini CLI, Windsurf, Cline, OpenCode, and any MCP-compatible agent or managed runtime. Access rules can inspect arguments and context, not just tool names, with CEL expressions for fine-grained conditions. Teams can start with observability, then layer in approvals and deny rules without SDKs or invasive app changes.Starting Price: $290 per month -
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Enkrypt AI
Enkrypt AI
Enkrypt AI is an enterprise AI security, compliance, and governance platform purpose-built to secure LLMs, AI agents, multimodal systems, and MCP workflows. Serving enterprises in finance, healthcare, insurance, and government, Enkrypt AI helps organizations ship fast, ship safe, and stay ahead. The platform covers the full AI security lifecycle: Guardrails: Ultra-low latency (sub-50ms) policy-based guardrails prevent prompt injection, sensitive data exposure, unsafe outputs, and non-compliant agent behavior in real time. Red Teaming: Policy-driven, multimodal attack simulation across LLMs and AI agents before deployment. MCP Security: MCP Scan Hub and Secure MCP Gateway protect MCP servers, tools, and agent toolchains end-to-end. Compliance: Continuous monitoring against NIST AI RMF, OWASP LLM Top 10, EU AI Act, HIPAA, and FINRA. ISO 27001 & SOC 2 Type II certified. Gartner Cool Vendor 2025. -
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Token Security
Token Security
Token Security accelerates secure enterprise adoption of Agentic AI by discovering, managing, and governing every AI agent and non-human identity across the organization. From continuous visibility to least-privilege enforcement and lifecycle management, Token Security provides complete control over AI and machine identities, eliminating blind spots, reducing risk, and ensuring compliance at scale. -
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elsai Foundry
elsai
elsai Foundry is a governance-first platform to design, deploy, and operate AI agents for regulated enterprise workflows. It embeds compliance guardrails, PHI/PII redaction, prompt management, and real-time ARMS observability into every workflow. Its architecture spans multi-agent orchestration, policy and approvals enforcement, human-in-the-loop controls, domain intelligence, and pre-built agents across healthcare, life sciences, insurance, procurement, and supply chain. -
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Emdash
Emdash
Emdash is an orchestration layer that lets you run multiple coding agents in parallel, each in its own isolated Git worktree, so you can simultaneously spin up different agents to tackle independent subtasks or experiments without interference. It’s provider-agnostic, meaning you can pick from various AI models and CLIs (for example, Claude Code, Codex, and others) to fit your workflow. With Emdash, you can assign issues or tickets (from Linear, GitHub, or Jira) directly to a chosen agent, then watch multiple agents operate side by side in real time. The UI shows live agent status and activity, and once agents generate code, you can review diffs, comment, and open pull requests, all without leaving Emdash. Because every agent runs in a separate worktree, changes stay sandboxed and comparable, enabling you to test different implementations or strategies side-by-side safely.Starting Price: Free -
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elsai
elsai
elsai is a purpose-built agentic operations platform that gives regulated enterprises the infrastructure to run AI at production scale — not just in pilots. The platform combines three integrated layers: a domain intelligence layer trained to comprehend patient records, financial instruments, and regulatory documents; a multi-agent orchestration engine that sequences specialized agents across complex workflows; and ARMS, a full-observability governance framework that tracks every token, decision, and cost in real time. With 200+ pre-built enterprise integrations and a structured six-stage deployment path, elsai is production-ready for healthcare, BFSI, life sciences, and logistics — governed, auditable, and built on 16 years of enterprise delivery. -
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Lunar.dev
Lunar.dev
Lunar.dev is an AI gateway and API consumption management platform that gives engineering teams a single, unified control plane to monitor, govern, secure, and optimize all outbound API and AI agent traffic, including calls to large language models, Model Context Protocol tools, and third-party services, across distributed applications and workflows. It provides real-time visibility into usage, latency, errors, and costs so teams can observe every model, API, and agent interaction live, and apply policy enforcement such as role-based access control, rate limiting, quotas, and cost guards to maintain security and compliance while preventing overuse or unexpected bills. Lunar.dev's AI Gateway centralizes control of outbound API traffic with identity-aware routing, traffic inspection, data redaction, and governance, while its MCPX gateway consolidates multiple MCP servers under one secure endpoint with full observability and permission management for AI tools.Starting Price: Free -
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AGAT Secure AI Platform
AGAT Software
AGAT Secure AI Platform is a security-first AI platform designed to provide enterprise-grade generative AI capabilities while ensuring full data protection and governance. It supports deployment either on-premises (including air-gapped environments) or in the cloud, enabling zero-data-exposure use cases and strong enterprise control. It comprises two main components: an AI Suite and an AI Firewall. The AI Suite offers a private-AI environment with modules including a knowledge assistant (answers from company data), data-analysis agent (natural-language analytics on spreadsheets and databases), smart search (meaning-based content discovery), AI code assistant (code completion, generation and error detection), and AI agents that can plan and execute tasks via file creation/modification and internet search. The AI Firewall acts as a real-time proxy for public AI services, enforcing risk-based policies, and more. -
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Golf
Golf
GolfMCP is an open source framework designed to streamline the creation and deployment of production-ready Model Context Protocol (MCP) servers, enabling organizations to build secure, scalable AI-agent infrastructure without worrying about boilerplate. It allows developers to define tools, prompts, and resources as simple Python files, after which Golf handles routing, authentication, telemetry, and observability, so you focus on logic, not plumbing. The platform supports enterprise authentication (JWT, OAuth Server, API key), automatic telemetry, and a file-based structure that eliminates decorators or manual schema wiring. With built-in utilities for LLM interactions, error logging, OpenTelemetry integration, and deployment tools (such as a CLI with golf init, golf build dev, golf run), Golf provides a full stack for agent-native services. Included also is the Golf Firewall, an enterprise-grade security layer for MCP servers that enforces token validation.Starting Price: Free -
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AvonAI
AvonAI
AvonAI keeps your AI agents aligned with your business by monitoring every customer conversation, controlling every interaction, and helping teams trust every outcome at scale. Your agents are live, handling real conversations with real customers, but agents do not manage themselves: they go off-script, drift from policies, and cannot keep up with business changes on their own. AvonAI reads every interaction and surfaces only the ones that matter, including policy violations, hallucinations, missing disclaimers, and other behavioral drift, so teams can find and fix risks in hours instead of weeks. It lets operations teams update agent knowledge and steer behavior in plain language, with no code and no developer ticket, while showing exactly what will change and allowing validation before anything goes live. AvonAI continuously tests agents against business directives, so the moment a model, prompt, or knowledge source changes, teams know whether the agent still behaves as intended. -
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LangProtect
LangProtect
LangProtect is an AI-native security and governance platform that protects LLM and Generative AI applications from prompt injection, jailbreaks, sensitive data leakage, and unsafe or non-compliant outputs. Built for production GenAI, it enforces real-time runtime controls at the AI execution layer by inspecting prompts, model responses, and tool/function calls as they happen. This allows teams to block high-risk behavior before it reaches end users, triggers downstream actions, or exposes confidential data. LangProtect integrates into existing LLM stacks via an API-first approach with minimal latency and supports cloud, hybrid, and on-prem deployments for enterprise security and data residency needs. It also secures modern architectures such as RAG pipelines and agentic workflows with policy-driven enforcement, continuous visibility, and audit-ready governance. -
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Scorable
Scorable
Scorable is an AI evaluation and monitoring platform designed to help developers measure, control, and improve the behavior of applications built with large language models. It enables teams to create customized automated evaluators, sometimes referred to as AI “judges”, that assess how an AI system responds to users and whether its outputs meet defined quality standards such as accuracy, relevance, helpfulness, tone, and policy compliance. Developers can describe what they want to measure in plain language, and the platform generates a tailored evaluation stack that tests AI outputs against context-specific criteria rather than generic benchmarks. These evaluators can be embedded directly into application code, allowing AI systems such as chatbots, retrieval-augmented generation (RAG) systems, or autonomous agents to be continuously monitored in production environments.Starting Price: $19 per month -
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Snapper
Snapper
Snapper is an AI agent security platform designed to provide end-to-end governance and protection for organizations deploying AI agents across applications, networks, and systems. It delivers runtime enforcement by evaluating every agent action, including tool calls, API requests, and data access, before execution through a policy-driven rule engine with multiple enforcement layers. It offers unified visibility into AI usage by monitoring network traffic, browser activity, DNS, and processes to detect unauthorized tools and “shadow AI,” while also intercepting outbound LLM requests through SDK wrappers and a network proxy to evaluate, redact, and log sensitive data in real time. Snapper includes advanced threat detection capabilities that identify prompt injection, exploit chains, anomalous behavior, and multi-step attack patterns using behavioral baselines, kill chain tracking, and composite trust scoring. -
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Tuning Engines
CerebrixOS
Tuning Engines is a unified AI control and governance layer for teams building production intelligence across models, agents, tools, and fine-tuned systems. It brings together the full AI lifecycle in one governed platform: inference, model routing, fallback policies, fine-tuning jobs, datasets, evaluations, model imports and exports, custom models, agents, MCP servers, reusable skills, guardrails, AGT YAML policies, data capture, runtime traces, usage analytics, API keys, billing, team roles, and integrations. Developers get OpenAI-compatible APIs, Anthropic-compatible routes, CLI workflows, MCP access, coding-agent integrations, and resource catalogs for models, agents, tools, and skills. Teams can connect Claude Code, OpenCode, Aider, Cline, Roo, Continue.dev, Cursor, VS Code, Windsurf, and other AI workflows through a single governed platform. -
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WhyLabs
WhyLabs
Enable observability to detect data and ML issues faster, deliver continuous improvements, and avoid costly incidents. Start with reliable data. Continuously monitor any data-in-motion for data quality issues. Pinpoint data and model drift. Identify training-serving skew and proactively retrain. Detect model accuracy degradation by continuously monitoring key performance metrics. Identify risky behavior in generative AI applications and prevent data leakage. Protect your generative AI applications are safe from malicious actions. Improve AI applications through user feedback, monitoring, and cross-team collaboration. Integrate in minutes with purpose-built agents that analyze raw data without moving or duplicating it, ensuring privacy and security. Onboard the WhyLabs SaaS Platform for any use cases using the proprietary privacy-preserving integration. Security approved for healthcare and banks. -
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blankspace
blankspace
blankspace is a platform built to help publishers monitor, measure, and monetize the “invisible audience” of AI agents that crawl and consume website content to fuel answers on AI services, giving publishers insight into how their content is being used and how much influence they hold in the emerging “answer economy.” It provides a real-time analytics layer that identifies AI agents visiting a site, tracks consumption patterns across pages and topics, and reveals AI traffic volumes and agent-specific behaviors that traditional analytics tools don’t capture. With a marketplace for AI impressions, publishers can set floor prices by page or category and activate campaigns that monetize AI agent views alongside their existing human-focused ad stack, turning unseen bot traffic into revenue opportunities. blankspace also offers measurement tools that quantify brand uplift and citation rates from AI-driven campaigns, so teams can prove impact and optimize strategies. -
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Claw Code
Claw Code
Claw Code is an open-source AI coding agent framework designed to replicate and expand upon modern AI-assisted development architectures. Built using a combination of Python and Rust, it delivers a modular and high-performance system for coding automation. The framework features a plugin-based tool system, allowing developers to execute tasks like file operations, shell commands, and web interactions with permission controls. Its core query engine manages LLM interactions, enabling intelligent code generation, analysis, and multi-step task execution. Claw Code supports multi-agent orchestration, allowing complex tasks to be broken down into parallel workflows. It is provider-agnostic, meaning it can integrate with multiple AI models rather than being limited to a single ecosystem. Overall, Claw Code offers developers a flexible, transparent, and customizable foundation for building advanced AI coding agents.Starting Price: Free -
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Google’s Agent Payments Protocol (AP2) is an open protocol designed together with over 60 payments, fintech, and tech companies (e.g., Mastercard, PayPal, Adyen, Coinbase, Etsy) to enable secure, agent-led transactions across platforms. It builds on earlier open standards like Agent2Agent (A2A) and the Model Context Protocol (MCP) to ensure that when an AI agent initiates or completes a payment on behalf of a user, three core requirements are met: authorization (proving the user explicitly gave permission for that specific purchase), authenticity (ensuring the agent’s intended purchase matches what the user meant), and accountability (clear audit trails and responsibility in case of errors or fraud). The protocol uses mandates, which are cryptographically signed digital contracts backed by verifiable credentials.
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Openlayer
Openlayer
Openlayer is the AI governance and observability platform that accelerates the evaluation and observability of agentic systems through 100+ automated tests and real-time guardrails that prevent prompt injections, PII leakage, bias, toxicity, and hallucinations, powering secure enterprise innovation. Designed to support both traditional ML and GenAI systems, Openlayer helps teams seamlessly handle everything from data-quality detection to automating comprehensive model evaluations, with full traceability across RAG, agents, and complex multi-step workflows. Trusted by Fortune 500 companies from early experimentation through production deployment and automated governance capabilities (NIST, EU AI Act, etc.)., Openlayer enables safe, reliable, and responsible AI operations. -
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Dymium
Dymium
Dymium is the real-time data governance layer that ensures AI agents, applications, and analytics only access the precise information they’re permitted to see. Powered by its Ghost Layer architecture, Dymium evaluates every request as it happens, enforcing identity-, role-, and context-aware policies instantly. Sensitive data never needs to be copied, staged, or broadly exposed—access is governed directly at the source through GhostDB, GhostAPI, and GhostMCP. This enables teams to work at inference speed without creating compliance or security risk. Every interaction is logged and auditable in real time, supporting GDPR, HIPAA, and AI Act requirements by default. With Dymium, organizations unlock more data safely while eliminating over-permissioning, data duplication, and operational bottlenecks. -
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AgentMonk
TechMonk
AgentMonk is an agentic AI customer engagement and automation platform that lets businesses build, deploy, and manage portfolios of AI agents that perceive, decide, and act across customer workflows to attract, interact, convert, and retain customers with personalized experiences powered by rich customer intelligence. It includes pre-built and custom AI agents for sales, support, reporting, segmentation, and more, plus a no-code agent builder and agentic workflows that automate complex tasks and unify customer data, segmentation, journey orchestration, and omnichannel engagement (Web, WhatsApp, Instagram, voice, email) in one full-stack toolkit. It provides enterprise-grade features such as strict guardrails, workflow observability, performance tracking, and security and compliance measures, enabling teams to test, observe, and optimize AI agent behavior and ensure high-quality interactions. -
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AIVM Brain
ChainGPT AI S.A.
AIVM Brain is a governed, verifiable AI knowledge platform shared by a company's employees and its AI agents. It connects existing tools, Slack, Google Drive, Notion, GitHub, Box, Confluence, Salesforce, and Telegram, while preserving each source's original permissions, so users and agents only see what they're cleared to see. Every access is recorded in a tamper-evident, content-blind audit log proving who asked what and what was disclosed, without storing the content itself, and the log is independently verifiable by auditors. Agents query Brain through a governed MCP endpoint with mandates, human-in-the-loop controls, and a kill switch. Brain is model-agnostic, working with Claude, OpenAI, Gemini, or a customer's own model via bring-your-own-key, and never trains on customer data. Enterprise features include SSO, per-tenant isolation, real-time permission revocation, and SOC 2/ISO 42001 in progress. Delivered as hosted SaaS with MCP, SDK, REST API, and CLI access.Starting Price: $18/month -
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Hindsight
Vectorize
Hindsight is an agent memory system built to create smarter AI agents that learn over time instead of starting every conversation from zero. Most agent memory systems focus on recalling conversation history, but Hindsight is focused on making agents learn, not just remember. It gives AI agents persistent long-term memory using biomimetic data structures, helping them retain facts, recall relevant context, and reflect on experience as part of reasoning. Hindsight is designed for agents that need to understand who a user is, what has been discussed, what preferences have emerged, what decisions were made, and how behavior should adapt across sessions. It provides three core operations: retain, recall, and reflect. Retain stores new information, recall retrieves the right memories when needed, and reflect helps agents synthesize observations, form mental models, and learn from prior interactions.Starting Price: Free -
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condense.chat
condense.chat
condense.chat is an LLM input compression API and drop-in proxy that shrinks prompts, retrieved documents, tool outputs, and repeated agent context before they hit upstream models. Less context, same Claude Code; its harness intercepts an agent’s growing session history and passes it through compression models before it reaches the main model, helping long-running coding agents start each next turn with fewer tokens. Condense sits between an app and the upstream LLM provider, tracks the conversation as a content-addressed chain, and transparently compresses repeated context on the way upstream. Developers can point their SDK at the Condense provider route, add a Condense key, keep their existing provider key, and change nothing else. It supports Anthropic and OpenAI-compatible routes, plus pass-through behavior for other provider paths such as model lists and embeddings. -
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RagMetrics
RagMetrics
RagMetrics is a production-grade evaluation and trust platform for conversational GenAI, designed to assess AI chatbots, agents, and RAG systems before and after they go live. The platform continuously evaluates AI responses for accuracy, groundedness, hallucinations, reasoning quality, and tool-calling behavior across real conversations. RagMetrics integrates directly with existing AI stacks and monitors live interactions without disrupting user experience. It provides automated scoring, configurable metrics, and detailed diagnostics that explain when an AI response fails, why it failed, and how to fix it. Teams can run offline evaluations, A/B tests, and regression tests, as well as track performance trends in production through dashboards and alerts. The platform is model-agnostic and deployment-agnostic, supporting multiple LLMs, retrieval systems, and agent frameworks.Starting Price: $20/month -
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rawctx
rawctx
rawctx is an AI answer evidence layer for teams shipping customer-facing AI assistants, copilots, and agents. It records each answer with the approved meaning reference, source/context references, model-run metadata, trace IDs, correction history, and exportable proof bundles. Teams can audit why an AI answer was shown, which evidence and business definition it used, what changed after review, and whether trust proof status is anchored, pending, or local-only. rawctx supports answer audit logs, JSON/CSV/proof exports, source_ref evidence binding, and public or private verification workflows for high-stakes support, sales, finance, legal, and operations use cases.Starting Price: $9.99/1000logs -
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Warestack
Warestack
Warestack is an agentic AI–powered release protection platform that installs directly into your GitHub organization and enforces custom, context-aware guardrails across every stage of your development workflow. Users write protection rules in plain English, such as requiring approvals for non-hotfix PRs or blocking Friday deployments, and Warestack automatically flags or blocks risky operations, traces events like pull requests, issues, deployments, and workflow runs in real time, and centralizes visibility in a unified dashboard. It integrates seamlessly with tools like GitHub, Slack, and Linear to deliver smart alerts and notifications, while offering one-click audit logs and reports to support SOC-2 and compliance needs. Warestack scales effortlessly across teams and repositories with scoped rule application, role-based enforcement, and a transparent open source rule engine named Watchflow that powers its policy creation.Starting Price: $49 per month -
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Manifold Security
Manifold Security
Manifold Security is an AI Detection and Response platform built to secure autonomous AI agents operating on enterprise endpoints, addressing a critical gap in traditional cybersecurity approaches that focus primarily on user activity or model inputs and outputs. It provides runtime visibility into what AI agents actually do, capturing their behavior as they interact with systems, execute commands, access files, and call APIs across development environments and production infrastructure. Observing agent activity directly on endpoints without requiring additional infrastructure such as proxies or gateways, it enables organizations to monitor real actions rather than just prompts or responses. It maps relationships between agents, tools, and connected services, offering a clear view of which agents are active, what permissions they use, and how they interact with internal and external resources. -
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Notenic
Notenic
Notenic is a runtime orchestration and governance platform designed to control and secure autonomous AI agents (“digital labor”) in real time, particularly in environments where failure carries regulatory, legal, or operational consequences. It operates as an infrastructure layer that sits directly in the execution path of AI systems, enforcing deterministic governance before any action reaches systems of record, rather than relying on post-output filters or prompt-level controls. It introduces a zero-trust runtime architecture built on core principles such as zero-persistence (no data retained after each session), execution-path control (policy enforcement at the moment of action), and independence from model context, ensuring that adversarial inputs cannot override governed behavior. Notenic provides a unified control plane that includes agent workforce management (treating AI agents as operational units with defined roles and supervision). -
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HiClaw
AgentScope
HiClaw is an open source multi-agent OS powered by Matrix. It lets multiple AI agents collaborate in Matrix rooms, fully visible to humans, with real-time intervention capability. A Manager Agent coordinates multiple Worker Agents to complete complex tasks, intelligently decomposing work and enabling parallel execution for stronger complex task handling. Built for enterprise-grade security and multi-agent collaboration, HiClaw uses the open Matrix IM protocol so all agent communications remain transparent, auditable, and suitable for distributed deployment and federation. Humans can enter any Matrix room at any time to observe agent conversations, intervene, or correct agent behavior in real time, ensuring safety and control. It's clear that a two-tier Manager-Worker architecture gives each agent distinct responsibilities and makes it easier to extend the system with custom Worker Agents for different scenarios.Starting Price: Free -
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Swifter
Swifter.io
Swifter governs AI across the full software development lifecycle. Unlike code-only assistants that deliver ~10% productivity gains, Swifter's spec-driven agents cover the entire SDLC — from business requirements through design, code generation, testing, and delivery — achieving 25-30% gains. Built for enterprise: full traceability from requirement to delivered code, audit trails, compliance enforcement, and consistent output across hundreds of developers. Supports both greenfield and legacy modernization. Partnered with Tech Mahindra (1,100+ enterprise clients). -
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Solo Enterprise
Solo Enterprise
Solo Enterprise provides a unified cloud-native application networking and connectivity platform that helps enterprises securely connect, scale, manage, and observe APIs, microservices, and intelligent AI workloads across distributed environments, especially Kubernetes-based and multi-cluster infrastructures. Its core capabilities are built on open source technologies such as Envoy and Istio and include Gloo Gateway for omnidirectional API management (handling external, internal, and third-party traffic with security, authentication, traffic routing, observability, and analytics), Gloo Mesh for centralized multi-cluster service mesh control (simplifying service-to-service connectivity and security across clusters), and Agentgateway/Gloo AI Gateway for secure, governed LLM/AI agent traffic with guardrails and integration support. -
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Bold Security
Bold Security
Bold is an AI-driven endpoint security platform designed to protect enterprise devices such as laptops and workstations by deploying an autonomous security agent directly on the endpoint. It continuously monitors how users interact with applications, files, and data on the device, enabling it to detect unusual or risky behavior in real time rather than relying solely on traditional cloud-based monitoring tools. Because the AI agent runs locally on the device, it can observe every workflow and application activity without gaps caused by unsupported APIs or external integrations, providing full visibility into user actions and system behavior. When the platform detects a potential security risk, it does not simply generate an alert but can automatically enforce protective actions, turning threats into resolved incidents before they escalate into breaches. -
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GuardionAI
GuardionAI
GuardionAI is an Agent and MCP Security Gateway that provides unified security for AI agents and Model Context Protocol tools operating on enterprise data. It sits in the execution path to discover, redact sensitive data, enforce protection, and give teams visibility into actions that traditional SIEM, DLP, and identity layers cannot see. Every agent action is inspected, enforced, and logged at the protocol level across AI agents, LLM apps, RAG systems, chatbots, coding agents, MCP servers, internal tools, databases, operating systems, and cloud environments. GuardionAI protects against critical AI threats such as prompt injection, system override, web attacks, MCP tool poisoning, malicious code execution, NSFW content, PII and credential exposure, confidential data leakage, off-topic drift, and unauthorized access, mapped to OWASP LLM Top 10 and agentic AI threat frameworks. Its gateway provides four layers of protection. -
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EarlyCore
EarlyCore
EarlyCore is a security platform built for AI agents. It automates pre-production attack testing, real-time monitoring, and compliance reporting across the full agent lifecycle. Scans agents against thousands of attack scenarios covering prompt injection, jailbreaking, data exfiltration, tool misuse, and supply chain threats. In production, tracks every agent action, establishes behavioral baselines, and flags anomalies in real time. Alerts push to Slack, email, or webhooks. Compliance docs generate automatically, mapped to ISO 42001, NIST AI RMF, EU AI Act, SOC 2, and GDPR. Always audit-ready. Deploys in 15 minutes with zero code changes. Integrates with AWS Bedrock, Gemini Enterprise Agent Platform, LangChain, and more. Multi-tenant support for agencies and MSSPs. Built for security teams, agencies, and MSSPs securing AI agents at scale.Starting Price: $100/month -
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xpander.ai
xpander.ai
xpander.ai is a backend-as-a-service platform tailored for production-grade AI agents, offering developers a robust infrastructure that handles memory, tools, connectors, multi-agent workflows, triggering, state management, observability, and CI/CD pipelines without requiring infrastructure setup. Its visual AI agent workbench enables users to design, configure, simulate, test, and deploy agents interactively, complete with support for multi-agent collaboration, tool integrations, role-based access, and runtime governance. Developers can connect agents to SaaS or enterprise systems via AI-ready connectors, attach tool-compatible workflows, and monitor agent behavior with built-in observability and lifecycle tools. It supports deployment on hosted cloud infrastructure or within private VPCs, ensuring both agility and secure enterprise integration, and accelerates agent development from idea to production.Starting Price: $49 per month -
46
AgentScope
AgentScope
AgentScope is an AI-driven agent observability and operations platform that provides visibility, control, and performance analytics for autonomous AI agents across production workloads. It enables engineering and DevOps teams to monitor, diagnose, and optimize complex multi-agent applications in real time by capturing detailed telemetry on agent actions, decisions, resource usage, and outcome quality. With rich dashboards and timelines, AgentScope helps teams trace execution flows, identify bottlenecks, and understand how agents interact with external systems, APIs, and data sources, improving debugging and reliability for autonomous workflows. It supports customizable alerting, log aggregation, and structured event views so teams can quickly surface anomalous behavior or errors across distributed agent fleets. In addition to real-time monitoring, AgentScope provides historical analysis and reporting that help teams measure performance trends, model drift, etc.Starting Price: Free -
47
Telebroad ACD Panel
TeleBroad
The ACD Panel monitors all live calls and can control Agent(s) behavior, while supervising the answering of the calls waiting in queue. Once the Panel is set, it automatically identifies long wait times and takes the right action(s) to resolve any issues. Automatically distribute your calls that are 'On Hold' calls to agents located anywhere in the world with a simple drag and drop on the Panel's screen. The live Panel will show you many statistics including the average caller's 'wait time'. This allows you to choose the correct course of action so as not to allow any unnecessary build up or excess callers waiting. The ACD panel provides the analysis of data to provide business intelligence as never before been available. This allows users to view interactive charts, queuing solutions in addition to monitor Agent's behavior and all related Performance concerns. You can configure and customize the dashboard with your personal data values to get a clear understanding of call center. -
48
Convin
Convin
Convin is a conversation intelligence platform that integrates Generative AI to transform call center operations. It automates 100% of lead engagement using multilingual virtual agents and provides real-time assistance to agents during calls. By tracking and analyzing every interaction, Convin offers detailed insights into agent performance, customer sentiment, and key trends. The platform uses AI-powered quality assurance to ensure unbiased evaluations of all interactions, from calls to chats to emails. Convin’s deep analytics capabilities—such as conversation behavior analysis and customer intelligence—empower businesses to optimize agent-customer interactions, replicate successful behaviors, and identify opportunities for improvement. The platform seamlessly integrates with existing systems and supports 70+ languages, making it ideal for global organizations looking to scale their contact center operations effectively. -
49
Domino Enterprise AI Platform
Domino Data Lab
Domino is an enterprise AI platform designed to help organizations build, deploy, and scale AI systems that deliver real business outcomes. It provides end-to-end support for the AI lifecycle, from data science experimentation to production deployment and governance. The platform enables teams to access data, tools, and compute resources through a self-service environment with built-in IT controls. Domino supports the development of machine learning models, generative AI applications, and AI agents using preferred tools and frameworks. It also includes governance features such as model tracking, audit trails, and policy enforcement to ensure compliance and transparency. With hybrid and multi-cloud capabilities, organizations can run AI workloads across on-premises and cloud environments. Overall, Domino helps enterprises operationalize AI at scale while maintaining control, security, and efficiency. -
50
Singulr
Singulr
Singulr is an enterprise AI governance and security platform that provides a unified control plane to help organizations discover, secure, and optimize AI adoption at scale. It addresses the growing gap between rapid AI usage and limited governance by delivering complete visibility into all AI systems in use, including homegrown applications, embedded AI, public tools, and shadow AI that often remains invisible to security teams. It continuously discovers and inventories AI assets across the organization, creating a real-time map of agents, models, and services, while assessing their risk through contextual analysis of data handling, model lineage, vulnerabilities, and compliance implications. Through its Singulr Pulse intelligence layer, it evaluates millions of AI systems, assigns risk scores, and supports automated onboarding workflows that reduce approval cycles from weeks to hours without compromising security.