Alternatives to Openlayer

Compare Openlayer alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Openlayer in 2026. Compare features, ratings, user reviews, pricing, and more from Openlayer competitors and alternatives in order to make an informed decision for your business.

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    New Relic

    New Relic

    New Relic

    There are an estimated 25 million engineers in the world across dozens of distinct functions. As every company becomes a software company, engineers are using New Relic to gather real-time insights and trending data about the performance of their software so they can be more resilient and deliver exceptional customer experiences. Only New Relic provides an all-in-one platform that is built and sold as a unified experience. With New Relic, customers get access to a secure telemetry cloud for all metrics, events, logs, and traces; powerful full-stack analysis tools; and simple, transparent usage-based pricing with only 2 key metrics. New Relic has also curated one of the industry’s largest ecosystems of open source integrations, making it easy for every engineer to get started with observability and use New Relic alongside their other favorite applications.
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    Gemini Enterprise Agent Platform
    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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    Orq.ai

    Orq.ai

    Orq.ai

    Orq.ai is the #1 platform for software teams to operate agentic AI systems at scale. Optimize prompts, deploy use cases, and monitor performance, no blind spots, no vibe checks. Experiment with prompts and LLM configurations before moving to production. Evaluate agentic AI systems in offline environments. Roll out GenAI features to specific user groups with guardrails, data privacy safeguards, and advanced RAG pipelines. Visualize all events triggered by agents for fast debugging. Get granular control on cost, latency, and performance. Connect to your favorite AI models, or bring your own. Speed up your workflow with out-of-the-box components built for agentic AI systems. Manage core stages of the LLM app lifecycle in one central platform. Self-hosted or hybrid deployment with SOC 2 and GDPR compliance for enterprise security.
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    Braintrust

    Braintrust

    Braintrust Data

    Braintrust is an AI observability and evaluation platform designed to help teams build, monitor, and improve AI systems in production. It enables users to capture and inspect real-time traces of AI interactions, including prompts, responses, and tool usage. The platform allows teams to measure performance using automated and human evaluations to ensure output quality. Braintrust helps identify issues such as hallucinations, regressions, and performance drops before they impact users. It supports prompt and model comparisons, making it easier to optimize AI workflows over time. With scalable trace ingestion and real-time monitoring, teams gain full visibility into how their AI systems behave. The platform integrates with multiple programming languages and tools, allowing developers to work within their existing tech stack. Overall, Braintrust provides a comprehensive solution for maintaining and improving AI quality at scale.
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    Maxim

    Maxim

    Maxim

    Maxim is an agent simulation, evaluation, and observability platform that empowers modern AI teams to deploy agents with quality, reliability, and speed. Maxim's end-to-end evaluation and data management stack covers every stage of the AI lifecycle, from prompt engineering to pre & post release testing and observability, data-set creation & management, and fine-tuning. Use Maxim to simulate and test your multi-turn workflows on a wide variety of scenarios and across different user personas before taking your application to production. Features: Agent Simulation Agent Evaluation Prompt Playground Logging/Tracing Workflows Custom Evaluators- AI, Programmatic and Statistical Dataset Curation Human-in-the-loop Use Case: Simulate and test AI agents Evals for agentic workflows: pre and post-release Tracing and debugging multi-agent workflows Real-time alerts on performance and quality Creating robust datasets for evals and fine-tuning Human-in-the-loop workflows
    Starting Price: $29/seat/month
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    Arize Phoenix
    Phoenix is an open-source observability library designed for experimentation, evaluation, and troubleshooting. It allows AI engineers and data scientists to quickly visualize their data, evaluate performance, track down issues, and export data to improve. Phoenix is built by Arize AI, the company behind the industry-leading AI observability platform, and a set of core contributors. Phoenix works with OpenTelemetry and OpenInference instrumentation. The main Phoenix package is arize-phoenix. We offer several helper packages for specific use cases. Our semantic layer is to add LLM telemetry to OpenTelemetry. Automatically instrumenting popular packages. Phoenix's open-source library supports tracing for AI applications, via manual instrumentation or through integrations with LlamaIndex, Langchain, OpenAI, and others. LLM tracing records the paths taken by requests as they propagate through multiple steps or components of an LLM application.
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    Respan

    Respan

    Respan

    Respan is a self-driving observability and evaluation platform built specifically for AI agents. It enables teams to trace full execution flows, including messages, tool calls, routing decisions, memory usage, and outcomes. The platform connects observability, evaluations, and optimization into a continuous improvement loop. Metric-first evaluations allow teams to define performance standards such as accuracy, cost, reliability, and safety. Respan also includes capability and regression testing to protect stable behaviors while improving new ones. An AI-powered evaluation agent analyzes failures, identifies root causes, and recommends next steps automatically. With compliance certifications including ISO 27001, SOC 2, GDPR, and HIPAA, Respan supports secure, large-scale AI deployments across industries.
    Starting Price: $0/month
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    Athina AI

    Athina AI

    Athina AI

    Athina is a collaborative AI development platform that enables teams to build, test, and monitor AI applications efficiently. It offers features such as prompt management, evaluation tools, dataset handling, and observability, all designed to streamline the development of reliable AI systems. Athina supports integration with various models and services, including custom models, and ensures data privacy through fine-grained access controls and self-hosted deployment options. The platform is SOC-2 Type 2 compliant, providing a secure environment for AI development. Athina's user-friendly interface allows both technical and non-technical team members to collaborate effectively, accelerating the deployment of AI features.
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    Langfuse

    Langfuse

    Langfuse

    Langfuse is an open source LLM engineering platform to help teams collaboratively debug, analyze and iterate on their LLM Applications. Observability: Instrument your app and start ingesting traces to Langfuse Langfuse UI: Inspect and debug complex logs and user sessions Prompts: Manage, version and deploy prompts from within Langfuse Analytics: Track metrics (LLM cost, latency, quality) and gain insights from dashboards & data exports Evals: Collect and calculate scores for your LLM completions Experiments: Track and test app behavior before deploying a new version Why Langfuse? - Open source - Model and framework agnostic - Built for production - Incrementally adoptable - start with a single LLM call or integration, then expand to full tracing of complex chains/agents - Use GET API to build downstream use cases and export data
    Starting Price: $29/month
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    Fiddler AI

    Fiddler AI

    Fiddler AI

    Fiddler is a pioneer in Model Performance Management for responsible AI. The Fiddler platform’s unified environment provides a common language, centralized controls, and actionable insights to operationalize ML/AI with trust. Model monitoring, explainable AI, analytics, and fairness capabilities address the unique challenges of building in-house stable and secure MLOps systems at scale. Unlike observability solutions, Fiddler integrates deep XAI and analytics to help you grow into advanced capabilities over time and build a framework for responsible AI practices. Fortune 500 organizations use Fiddler across training and production models to accelerate AI time-to-value and scale, build trusted AI solutions, and increase revenue.
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    Dynamiq

    Dynamiq

    Dynamiq

    Dynamiq is a platform built for engineers and data scientists to build, deploy, test, monitor and fine-tune Large Language Models for any use case the enterprise wants to tackle. Key features: 🛠️ Workflows: Build GenAI workflows in a low-code interface to automate tasks at scale 🧠 Knowledge & RAG: Create custom RAG knowledge bases and deploy vector DBs in minutes 🤖 Agents Ops: Create custom LLM agents to solve complex task and connect them to your internal APIs 📈 Observability: Log all interactions, use large-scale LLM quality evaluations 🦺 Guardrails: Precise and reliable LLM outputs with pre-built validators, detection of sensitive content, and data leak prevention 📻 Fine-tuning: Fine-tune proprietary LLM models to make them your own
    Starting Price: $125/month
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    Scorable

    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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    RagMetrics

    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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    Vivgrid

    Vivgrid

    Vivgrid

    Vivgrid is a development platform for AI agents that emphasizes observability, debugging, safety, and global deployment infrastructure. It gives you full visibility into agent behavior, logging prompts, memory fetches, tool usage, and reasoning chains, letting developers trace where things break or deviate. You can test, evaluate, and enforce safety policies (like refusal rules or filters), and incorporate human-in-the-loop checks before going live. Vivgrid supports the orchestration of multi-agent systems with stateful memory, routing tasks dynamically across agent workflows. On the deployment side, it operates a globally distributed inference network to ensure low-latency (sub-50 ms) execution and exposes metrics like latency, cost, and usage in real time. It aims to simplify shipping resilient AI systems by combining debugging, evaluation, safety, and deployment into one stack, so you're not stitching together observability, infrastructure, and orchestration.
    Starting Price: $25 per month
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    Lucidic AI

    Lucidic AI

    Lucidic AI

    Lucidic AI is a specialized analytics and simulation platform built for AI agent development that brings much-needed transparency, interpretability, and efficiency to often opaque workflows. It provides developers with visual, interactive insights, including searchable workflow replays, step-by-step video, and graph-based replays of agent decisions, decision tree visualizations, and side‑by‑side simulation comparisons, that enable you to observe exactly how your agent reasons and why it succeeds or fails. The tool dramatically reduces iteration time from weeks or days to mere minutes by streamlining debugging and optimization through instant feedback loops, real‑time “time‑travel” editing, mass simulations, trajectory clustering, customizable evaluation rubrics, and prompt versioning. Lucidic AI integrates seamlessly with major LLMs and frameworks and offers advanced QA/QC mechanisms like alerts, workflow sandboxing, and more.
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    Portkey

    Portkey

    Portkey.ai

    Launch production-ready apps with the LMOps stack for monitoring, model management, and more. Replace your OpenAI or other provider APIs with the Portkey endpoint. Manage prompts, engines, parameters, and versions in Portkey. Switch, test, and upgrade models with confidence! View your app performance & user level aggregate metics to optimise usage and API costs Keep your user data secure from attacks and inadvertent exposure. Get proactive alerts when things go bad. A/B test your models in the real world and deploy the best performers. We built apps on top of LLM APIs for the past 2 and a half years and realised that while building a PoC took a weekend, taking it to production & managing it was a pain! We're building Portkey to help you succeed in deploying large language models APIs in your applications. Regardless of you trying Portkey, we're always happy to help!
    Starting Price: $49 per month
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    Traceloop

    Traceloop

    Traceloop

    Traceloop is a comprehensive observability platform designed to monitor, debug, and test the quality of outputs from Large Language Models (LLMs). It offers real-time alerts for unexpected output quality changes, execution tracing for every request, and the ability to gradually roll out changes to models and prompts. Developers can debug and re-run issues from production directly in their Integrated Development Environment (IDE). Traceloop integrates seamlessly with the OpenLLMetry SDK, supporting multiple programming languages including Python, JavaScript/TypeScript, Go, and Ruby. The platform provides a range of semantic, syntactic, safety, and structural metrics to assess LLM outputs, such as QA relevancy, faithfulness, text quality, grammar correctness, redundancy detection, focus assessment, text length, word count, PII detection, secret detection, toxicity detection, regex validation, SQL validation, JSON schema validation, and code validation.
    Starting Price: $59 per month
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    OpenLIT

    OpenLIT

    OpenLIT

    OpenLIT is an OpenTelemetry-native application observability tool. It's designed to make the integration process of observability into AI projects with just a single line of code. Whether you're working with popular LLM libraries such as OpenAI and HuggingFace. OpenLIT's native support makes adding it to your projects feel effortless and intuitive. Analyze LLM and GPU performance, and costs to achieve maximum efficiency and scalability. Streams data to let you visualize your data and make quick decisions and modifications. Ensures that data is processed quickly without affecting the performance of your application. OpenLIT UI helps you explore LLM costs, token consumption, performance indicators, and user interactions in a straightforward interface. Connect to popular observability systems with ease, including Datadog and Grafana Cloud, to export data automatically. OpenLIT ensures your applications are monitored seamlessly.
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    WhyLabs

    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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    Taam Cloud

    Taam Cloud

    Taam Cloud

    Taam Cloud is a powerful AI API platform designed to help businesses and developers seamlessly integrate AI into their applications. With enterprise-grade security, high-performance infrastructure, and a developer-friendly approach, Taam Cloud simplifies AI adoption and scalability. Taam Cloud is an AI API platform that provides seamless integration of over 200 powerful AI models into applications, offering scalable solutions for both startups and enterprises. With products like the AI Gateway, Observability tools, and AI Agents, Taam Cloud enables users to log, trace, and monitor key AI metrics while routing requests to various models with one fast API. The platform also features an AI Playground for testing models in a sandbox environment, making it easier for developers to experiment and deploy AI-powered solutions. Taam Cloud is designed to offer enterprise-grade security and compliance, ensuring businesses can trust it for secure AI operations.
    Starting Price: $10/month
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    Overseer AI

    Overseer AI

    Overseer AI

    Overseer AI is a platform designed to ensure AI-generated content is safe, accurate, and aligned with user-defined policies. It offers compliance enforcement by automating adherence to regulatory standards through custom policy rules, real-time content moderation to block harmful, toxic, or biased outputs from AI, debugging AI outputs by testing and monitoring responses against custom safety policies, policy-driven AI governance by applying centralized safety rules across all AI interactions, and trust-building for AI by guaranteeing safe, accurate, and brand-compliant outputs. The platform caters to various industries, including healthcare, finance, legal technology, customer support, education technology, and ecommerce & retail, providing tailored solutions to ensure AI responses align with industry-specific regulations and standards. Developers can access comprehensive guides and API references to integrate Overseer AI into their applications.
    Starting Price: $99 per month
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    Alice

    Alice

    Alice

    Alice (formerly ActiveFence) is a security, safety, and trust platform built to protect AI systems and online platforms in the GenAI era. Powered by the world’s largest adversarial intelligence dataset, Alice safeguards over 3 billion users across more than 120 languages. Its Rabbit Hole intelligence engine continuously analyzes billions of toxic and manipulative data samples to detect emerging threats in real time. The WonderSuite platform includes tools like WonderBuild for pre-launch stress testing, WonderFence for runtime guardrails, and WonderCheck for automated red-teaming. By defending against prompt injection, jailbreaks, governance gaps, and harmful AI behavior, Alice enables enterprises and foundation model labs to innovate with confidence.
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    Cisco AI Defense
    Cisco AI Defense is a comprehensive security solution designed to enable enterprises to safely develop, deploy, and utilize AI applications. It addresses critical security challenges such as shadow AI—unauthorized use of third-party generative AI apps—and application security by providing full visibility into AI assets and enforcing controls to prevent data leakage and mitigate threats. Key components include AI Access, which offers control over third-party AI applications; AI Model and Application Validation, which conducts automated vulnerability assessments; AI Runtime Protection, which implements real-time guardrails against adversarial attacks; and AI Cloud Visibility, which inventories AI models and data sources across distributed environments. Leveraging Cisco's network-layer visibility and continuous threat intelligence updates, AI Defense ensures robust protection against evolving AI-related risks.
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    Tumeryk

    Tumeryk

    Tumeryk

    Tumeryk Inc. specializes in advanced generative AI security solutions, offering tools like the AI trust score for real-time monitoring, risk management, and compliance. Our platform empowers organizations to secure AI systems, ensuring reliable, trustworthy, and policy-aligned deployments. The AI Trust Score quantifies the risk of using generative AI systems, enabling compliance with regulations like the EU AI Act, ISO 42001, and NIST RMF 600.1. This score evaluates and scores the trustworthiness of generated prompt responses, accounting for risks including bias, jailbreak propensity, off-topic responses, toxicity, Personally Identifiable Information (PII) data leakage, and hallucinations. It can be integrated into business processes to help determine whether content should be accepted, flagged, or blocked, thus allowing organizations to mitigate risks associated with AI-generated content.
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    Future AGI

    Future AGI

    Future AGI

    Future AGI is an open-source, end-to-end AI agent engineering platform that covers the full lifecycle: simulate, evaluate, optimize, monitor, protect, gateway, and guardrail - all from one place. It helps teams ship self-improving AI agents by collapsing fragmented tooling into one platform and one feedback loop: simulate edge cases before launch, evaluate what happens in production, protect users in real time, and turn every trace into signal for the next version. Key capabilities include 70+ built-in evaluation templates covering quality, safety, factuality, RAG retrieval, bias, audio, and image evaluation, OpenTelemetry-native tracing, agent optimization, and real-time guardrails (PII detection, prompt injection blocking). SDKs are available in Python, TypeScript, Java, and C#, with integrations for OpenAI, LangChain, LlamaIndex, and 30+ frameworks. Apache 2.0 licensed, self-hostable or cloud-managed.
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    Galileo

    Galileo

    Galileo

    Models can be opaque in understanding what data they didn’t perform well on and why. Galileo provides a host of tools for ML teams to inspect and find ML data errors 10x faster. Galileo sifts through your unlabeled data to automatically identify error patterns and data gaps in your model. We get it - ML experimentation is messy. It needs a lot of data and model changes across many runs. Track and compare your runs in one place and quickly share reports with your team. Galileo has been built to integrate with your ML ecosystem. Send a fixed dataset to your data store to retrain, send mislabeled data to your labelers, share a collaborative report, and a lot more! Galileo is purpose-built for ML teams to build better quality models, faster.
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    Weights & Biases

    Weights & Biases

    Weights & Biases

    Experiment tracking, hyperparameter optimization, model and dataset versioning with Weights & Biases (WandB). Track, compare, and visualize ML experiments with 5 lines of code. Add a few lines to your script, and each time you train a new version of your model, you'll see a new experiment stream live to your dashboard. Optimize models with our massively scalable hyperparameter search tool. Sweeps are lightweight, fast to set up, and plug in to your existing infrastructure for running models. Save every detail of your end-to-end machine learning pipeline — data preparation, data versioning, training, and evaluation. It's never been easier to share project updates. Quickly and easily implement experiment logging by adding just a few lines to your script and start logging results. Our lightweight integration works with any Python script. W&B Weave is here to help developers build and iterate on their AI applications with confidence.
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    Trusys AI
    Trusys.ai is a unified AI assurance platform that helps organizations evaluate, secure, monitor, and govern artificial intelligence systems across their full lifecycle, from early testing to production deployment. It offers a suite of tools: TRU SCOUT for automated security and compliance scanning against global standards and adversarial vulnerabilities, TRU EVAL for comprehensive functional evaluation of AI applications (text, voice, image, and agent) assessing accuracy, bias, and safety, and TRU PULSE for real-time production monitoring with alerts for drift, performance degradation, policy violations, and anomalies. It provides end-to-end observability and performance tracking, enabling teams to catch unreliable output, compliance gaps, and production issues early. Trusys supports model-agnostic evaluation with a no-code, intuitive interface and integrates human-in-the-loop reviews and custom scoring metrics to blend expert judgment with automated metrics.
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    Enkrypt AI

    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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    LangProtect

    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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    Plurai

    Plurai

    Plurai

    Plurai is the real-world trust platform for AI agents, built for simulation-driven evaluation, protection, and optimization that turns agents into trusted, continuously improving production systems. It helps teams train evals and guardrails tailored to their use case, bridging the gap from prototype to reliable production at scale. Plurai’s simulation platform prepares agents for the real world, not the lab, with hyper-realistic, product-tailored experimentation and evaluation that covers production complexity. It generates authentic multi-turn scenarios, personas, required artifacts, and tool mocking, using organizational PRDs, relevant sources, and policies to build a knowledge graph and expand edge-case coverage. Instead of relying on static datasets, manual test creation, or inconsistent LLM-as-a-judge methods, Plurai groups evaluations into structured, runnable experiments so teams can test new versions, measure regressions, and validate improvements before release.
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    Helicone

    Helicone

    Helicone

    Track costs, usage, and latency for GPT applications with one line of code. Trusted by leading companies building with OpenAI. We will support Anthropic, Cohere, Google AI, and more coming soon. Stay on top of your costs, usage, and latency. Integrate models like GPT-4 with Helicone to track API requests and visualize results. Get an overview of your application with an in-built dashboard, tailor made for generative AI applications. View all of your requests in one place. Filter by time, users, and custom properties. Track spending on each model, user, or conversation. Use this data to optimize your API usage and reduce costs. Cache requests to save on latency and money, proactively track errors in your application, handle rate limits and reliability concerns with Helicone.
    Starting Price: $1 per 10,000 requests
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    Prisma AIRS

    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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    asqav

    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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    elsai Foundry
    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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    White Circle

    White Circle

    White Circle

    White Circle is a unified AI control platform designed to provide end-to-end visibility, safety, and performance optimization for AI systems by combining testing, protection, monitoring, and improvement into a single integrated layer. It acts as a centralized control system that sits between AI models and users, analyzing every input and output in real time to ensure compliance with safety, security, and quality standards. It includes automated stress-testing capabilities that simulate risky prompts and real-world attack scenarios, allowing teams to detect vulnerabilities such as hallucinations, prompt injections, data leaks, and policy violations before deployment. It also features a protection layer that enforces custom rules through low-latency guardrails, blocking, rewriting, or flagging unsafe outputs instantly while preventing misuse of tools, unauthorized actions, or exposure of sensitive information.
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    UpTrain

    UpTrain

    UpTrain

    Get scores for factual accuracy, context retrieval quality, guideline adherence, tonality, and many more. You can’t improve what you can’t measure. UpTrain continuously monitors your application's performance on multiple evaluation criterions and alerts you in case of any regressions with automatic root cause analysis. UpTrain enables fast and robust experimentation across multiple prompts, model providers, and custom configurations, by calculating quantitative scores for direct comparison and optimal prompt selection. Hallucinations have plagued LLMs since their inception. By quantifying degree of hallucination and quality of retrieved context, UpTrain helps to detect responses with low factual accuracy and prevent them before serving to the end-users.
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    Arthur AI
    Track model performance to detect and react to data drift, improving model accuracy for better business outcomes. Build trust, ensure compliance, and drive more actionable ML outcomes with Arthur’s explainability and transparency APIs. Proactively monitor for bias, track model outcomes against custom bias metrics, and improve the fairness of your models. See how each model treats different population groups, proactively 
identify bias, and use Arthur's proprietary bias mitigation techniques. Arthur scales up and down to ingest up to 1MM transactions 
per second and deliver insights quickly. Actions can only be performed by authorized users. Individual teams/departments can have isolated environments with specific access control policies. Data is immutable once ingested, which prevents manipulation of metrics/insights.
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    JetStream Security
    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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    Opik

    Opik

    Comet

    Confidently evaluate, test, and ship LLM applications with a suite of observability tools to calibrate language model outputs across your dev and production lifecycle. Log traces and spans, define and compute evaluation metrics, score LLM outputs, compare performance across app versions, and more. Record, sort, search, and understand each step your LLM app takes to generate a response. Manually annotate, view, and compare LLM responses in a user-friendly table. Log traces during development and in production. Run experiments with different prompts and evaluate against a test set. Choose and run pre-configured evaluation metrics or define your own with our convenient SDK library. Consult built-in LLM judges for complex issues like hallucination detection, factuality, and moderation. Establish reliable performance baselines with Opik's LLM unit tests, built on PyTest. Build comprehensive test suites to evaluate your entire LLM pipeline on every deployment.
    Starting Price: $39 per month
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    Atla

    Atla

    Atla

    Atla is the agent observability and evaluation platform that dives deeper to help you find and fix AI agent failures. It provides real‑time visibility into every thought, tool call, and interaction so you can trace each agent run, understand step‑level errors, and identify root causes of failures. Atla automatically surfaces recurring issues across thousands of traces, stops you from manually combing through logs, and delivers specific, actionable suggestions for improvement based on detected error patterns. You can experiment with models and prompts side by side to compare performance, implement recommended fixes, and measure how changes affect completion rates. Individual traces are summarized into clean, readable narratives for granular inspection, while aggregated patterns give you clarity on systemic problems rather than isolated bugs. Designed to integrate with tools you already use, OpenAI, LangChain, Autogen AI, Pydantic AI, and more.
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    AgentOps

    AgentOps

    AgentOps

    Industry-leading developer platform to test and debug AI agents. We built the tools so you don't have to. Visually track events such as LLM calls, tools, and multi-agent interactions. Rewind and replay agent runs with point-in-time precision. Keep a full data trail of logs, errors, and prompt injection attacks from prototype to production. Native integrations with the top agent frameworks. Track, save, and monitor every token your agent sees. Manage and visualize agent spending with up-to-date price monitoring. Fine-tune specialized LLMs up to 25x cheaper on saved completions. Build your next agent with evals, observability, and replays. With just two lines of code, you can free yourself from the chains of the terminal and instead visualize your agents’ behavior in your AgentOps dashboard. After setting up AgentOps, each execution of your program is recorded as a session and the data is automatically recorded for you.
    Starting Price: $40 per month
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    Fluq

    Fluq

    Fluq

    Fluq is an AI agent observability and orchestration platform designed to give teams full visibility and control over how their AI agents operate in real time. It acts as a centralized “single pane of glass” where every agent action, LLM calls, tool usage, file operations, token consumption, and associated costs are tracked and visualized through detailed waterfall traces. By routing all agent requests through a lightweight proxy, Fluq requires minimal setup and works with any LLM provider or agent framework, allowing organizations to integrate it into existing systems without modifying code. It enables teams to inspect each decision an agent makes, drill into execution steps, and understand exactly how outcomes are generated, improving transparency and debuggability. It also includes governance features such as policy enforcement, spend limits, approval gates, and access controls, helping prevent issues like runaway costs, misuse of tools, or inaccurate outputs.
    Starting Price: $29 per month
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    HoneyHive

    HoneyHive

    HoneyHive

    AI engineering doesn't have to be a black box. Get full visibility with tools for tracing, evaluation, prompt management, and more. HoneyHive is an AI observability and evaluation platform designed to assist teams in building reliable generative AI applications. It offers tools for evaluating, testing, and monitoring AI models, enabling engineers, product managers, and domain experts to collaborate effectively. Measure quality over large test suites to identify improvements and regressions with each iteration. Track usage, feedback, and quality at scale, facilitating the identification of issues and driving continuous improvements. HoneyHive supports integration with various model providers and frameworks, offering flexibility and scalability to meet diverse organizational needs. It is suitable for teams aiming to ensure the quality and performance of their AI agents, providing a unified platform for evaluation, monitoring, and prompt management.
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    Teammately

    Teammately

    Teammately

    Teammately is an autonomous AI agent designed to revolutionize AI development by self-iterating AI products, models, and agents to meet your objectives beyond human capabilities. It employs a scientific approach, refining and selecting optimal combinations of prompts, foundation models, and knowledge chunking. To ensure reliability, Teammately synthesizes fair test datasets and constructs dynamic LLM-as-a-judge systems tailored to your project, quantifying AI capabilities and minimizing hallucinations. The platform aligns with your goals through Product Requirement Docs (PRD), enabling focused iteration towards desired outcomes. Key features include multi-step prompting, serverless vector search, and deep iteration processes that continuously refine AI until objectives are achieved. Teammately also emphasizes efficiency by identifying the smallest viable models, reducing costs, and enhancing performance.
    Starting Price: $25 per month
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    Solo Enterprise

    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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    Klu

    Klu

    Klu

    Klu.ai is a Generative AI platform that simplifies the process of designing, deploying, and optimizing AI applications. Klu integrates with your preferred Large Language Models, incorporating data from varied sources, giving your applications unique context. Klu accelerates building applications using language models like Anthropic Claude, Azure OpenAI, GPT-4, and over 15 other models, allowing rapid prompt/model experimentation, data gathering and user feedback, and model fine-tuning while cost-effectively optimizing performance. Ship prompt generations, chat experiences, workflows, and autonomous workers in minutes. Klu provides SDKs and an API-first approach for all capabilities to enable developer productivity. Klu automatically provides abstractions for common LLM/GenAI use cases, including: LLM connectors, vector storage and retrieval, prompt templates, observability, and evaluation/testing tooling.
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    DueDel

    DueDel

    DueDel

    DueDel is an enterprise-grade intelligence platform that unifies AI risk assessment, AI guardrails, and data protection into one secure, compliant ecosystem. The AI Risk Assessment Tool converts complex data into decision-ready summaries, detects early risk signals, uncovers market trends, and delivers predictive insights for investors, executives, and compliance teams. The Data Protection Fabric ensures no sensitive data ever reaches AI models by applying encryption, tokenization, and redaction—maintaining full compliance with RBI, SEBI, DPDP, and internal policies. The AI Guardrail Gateway gives complete control over what AI sees and generates, blocking harmful prompts, preventing hallucinations, enforcing policy-based routing, and securing external LLM usage with audit-grade logs. Together, DueDel enables regulated enterprises to govern AI safely while making faster, smarter, and fully compliant financial decisions.
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    Tuning Engines

    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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    Traccia

    Traccia

    Algen AI

    Traccia is an OpenTelemetry-native observability, governance, and policy enforcement platform for production AI agents. It gives engineering teams complete visibility into every LLM call, tool invocation, decision, token, and dollar spent across frameworks like LangChain, CrewAI, OpenAI Agents SDK, AutoGen, and LlamaIndex. Beyond tracing, Traccia helps organizations govern AI systems with runtime policies that can detect and block unsafe behavior, runaway costs, restricted model usage, and PII exposure before incidents reach production. Accurate cost attribution, agent health monitoring, a unified agent registry, and EU AI Act evidence generation make it suitable for enterprise deployments. With a lightweight open-source SDK and managed platform, Traccia enables teams to build, debug, monitor, and govern AI agents at scale without vendor lock-in, using standard OpenTelemetry instrumentation.