Alternatives to Kayba
Compare Kayba alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Kayba in 2026. Compare features, ratings, user reviews, pricing, and more from Kayba competitors and alternatives in order to make an informed decision for your business.
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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. -
2
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. -
3
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 workflowsStarting Price: $29/seat/month -
4
Netra
Netra
AI agents fail silently in production. Wrong answers, broken loops, cost spikes, behavior drift after a prompt change, and no stack trace to explain why. Netra gives engineering teams full visibility into every agent decision. Trace every LLM call, evaluate quality automatically, simulate edge cases before launch, and manage prompts with complete version history. Built on OpenTelemetry so setup takes minutes, not days. SOC2 Type II certified. GDPR and HIPAA compliant. US and EU data residency. Integrates with: LangChain, LangGraph, CrewAI, LlamaIndex, OpenAI, Anthropic, Gemini, AWS Bedrock, and 30+ more.Starting Price: $39/month -
5
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. -
6
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 -
7
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 dataStarting Price: $29/month -
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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 -
9
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 -
10
Convo
Convo
Kanvo provides a drop‑in JavaScript SDK that adds built‑in memory, observability, and resiliency to LangGraph‑based AI agents with zero infrastructure overhead. Without requiring databases or migrations, it lets you plug in a few lines of code to enable persistent memory (storing facts, preferences, and goals), threaded conversations for multi‑user interactions, and real‑time agent observability that logs every message, tool call, and LLM output. Its time‑travel debugging features let you checkpoint, rewind, and restore any agent run state instantly, making workflows reproducible and errors easy to trace. Designed for speed and simplicity, Convo’s lightweight interface and MIT‑licensed SDK deliver production‑ready, debuggable agents out of the box while keeping full control of your data.Starting Price: $29 per month -
11
Laminar
Laminar
Laminar is an open source all-in-one platform for engineering best-in-class LLM products. Data governs the quality of your LLM application. Laminar helps you collect it, understand it, and use it. When you trace your LLM application, you get a clear picture of every step of execution and simultaneously collect invaluable data. You can use it to set up better evaluations, as dynamic few-shot examples, and for fine-tuning. All traces are sent in the background via gRPC with minimal overhead. Tracing of text and image models is supported, audio models are coming soon. You can set up LLM-as-a-judge or Python script evaluators to run on each received span. Evaluators label spans, which is more scalable than human labeling, and especially helpful for smaller teams. Laminar lets you go beyond a single prompt. You can build and host complex chains, including mixtures of agents or self-reflecting LLM pipelines.Starting Price: $25 per month -
12
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 -
13
Voker
Voker
Voker is an Agent Analytics Platform for monitoring and improving AI agents in the wild, helping teams make sure their agents are helping, not just responding. It gives builders a way to track what AI agents are saying, identify knowledge gaps, detect abnormalities, and measure improvement over time without digging through logs or waiting for users to complain. Voker connects agent metrics to business outcomes by correlating conversational data with user data that teams are already collecting, making it easier to understand whether an agent is actually improving activation, retention, conversion, support quality, or other product goals. Its self-service analytics are designed for PMs, analysts, and business teams, giving them digestible insights without tickets, bottlenecks, or delays. Developers can install Voker through the SDK, including pip install voker, or use an AI coding tool to scaffold the SDK, add an API key, and instrument an agent in minutes.Starting Price: $80 per month -
14
AgentHub
AgentHub
AgentHub is a staging environment to simulate, trace, and evaluate AI agents in a private, sandboxed space that lets you ship with confidence, speed, and precision. With easy setup, you can onboard agents in minutes; a robust evaluation infrastructure provides multi-step trace logging, LLM graders, and fully customizable evaluations. Realistic user simulation employs configurable personas to model diverse behaviors and stress scenarios, and dataset enhancement synthetically expands test sets for comprehensive coverage. Prompt experimentation enables dynamic multi-prompt testing at scale, while side-by-side trace analysis lets you compare decisions, tool invocations, and outcomes across runs. A built-in AI Copilot analyzes traces, interprets results, and answers questions grounded in your own code and data, turning agent runs into clear, actionable insights. Combined human-in-the-loop and automated feedback options, along with white-glove onboarding and best-practice guidance. -
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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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Agenta
Agenta
Agenta is an open-source LLMOps platform designed to help teams build reliable AI applications with integrated prompt management, evaluation workflows, and system observability. It centralizes all prompts, experiments, traces, and evaluations into one structured hub, eliminating scattered workflows across Slack, spreadsheets, and emails. With Agenta, teams can iterate on prompts collaboratively, compare models side-by-side, and maintain full version history for every change. Its evaluation tools replace guesswork with automated testing, LLM-as-a-judge, human annotation, and intermediate-step analysis. Observability features allow developers to trace failures, annotate logs, convert traces into tests, and monitor performance regressions in real time. Agenta helps AI teams transition from siloed experimentation to a unified, efficient LLMOps workflow for shipping more reliable agents and AI products.Starting Price: Free -
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TraceRoot.AI
TraceRoot.AI
TraceRoot.AI is an open source, AI-native observability and debugging platform designed to help engineering teams resolve production issues faster. It consolidates telemetry into a single correlated execution tree that provides causal context for failures. AI agents operate over this structured view to summarize issues, pinpoint likely root causes, and even suggest actionable fixes or draft GitHub issues and pull requests. It offers interactive trace exploration with zoomable log clusters, span and latency views, and code-linked insights. Lightweight SDKs for Python and TypeScript enable seamless instrumentation using OpenTelemetry, with support for both self-hosted and cloud deployment. Human-in-the-loop interaction is central: developers can guide reasoning by selecting relevant spans or logs, then verify agent reasoning through traceable context.Starting Price: $49 per month -
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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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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 -
20
LayerLens
LayerLens
LayerLens is an independent AI model evaluation platform for understanding how models perform through verified results across benchmarks, prompt-level results, agentic benchmarks, and audit-ready comparisons across vendors. It helps teams compare more than 200 AI models side by side, with transparent benchmarks, model comparison tools, and consistent evaluation methods for accuracy, latency, behavior, and real-world applicability. LayerLens is built for deep model analysis through Spaces, where teams can group benchmarks and evaluations, explore task strengths, and track performance patterns in context. It supports continuous evaluation by running ongoing evals across model versions, prompt changes, judge updates, and live traces, helping teams detect quality regressions, drift, silent failures, contamination, and policy issues before they affect production. -
21
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.Starting Price: Free -
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Arize Phoenix
Arize AI
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.Starting Price: Free -
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Forsy
Forsy
Forsy is built around authentic human signal from real agent workflows, helping teams capture, understand, and trade agent trajectory data across the agent stack. It tracks agent work in real time as it happens, rather than reconstructing activity afterward, creating native capture for traces, tasks, and toolchain activity. It is designed for full coverage across everyday tasks, specialized workflows, and different domains, giving teams one engine for trajectory data across the agents they already use. Forsy turns AI agents into strategic assets by making authentic workflow data discoverable, licensable, and sellable through a market for agent data. Its high-fidelity data is purpose-built for teams building more capable and reliable agents, helping them access the kinds of real workflow traces needed to improve agent behavior, reliability, and evaluation. -
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Trace
Trace
Trace is a workflow automation platform that intelligently maps your existing business processes by connecting with tools like Slack, Jira, and Notion to build a unified context of data, activity, and users. It helps you visualize, design, and replicate multi-step workflows using either community-curated templates or custom paths you build. Once workflows are identified, Trace assigns repetitive or routine tasks, whether they require human attention or AI execution, to the right agent, all while keeping you in control, preserving permissions, and maintaining full audit logs. The platform also supports chat, search, and API interfaces to interact with tasks, high-context knowledge indexing across your organization, and seamless switching between projects or teams via dedicated workspaces. Together, these features allow organizations to automate busywork without changing how they work, unlocking productivity by orchestrating AI and human agents across workflows intelligently.Starting Price: $45 per month -
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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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RevDeBug
RevDeBug
Out-of-the-box debugging for microservices. Instantly find the code that broke your service, even for hard to reproduce errors. Understand every request, every outlier, every problem without additional logging and error reproduction. See the root causes for each error with full context from logs, metrics, traces and failed code execution. End-to-end tracing with automatic instrumentation – see logs, metrics, traces and failed code execution history. In-depth performance monitoring. Quickly identify and remove application bottlenecks. Real-time topology discovery with full dependency visibility across all services. Highly customizable dashboards and notifications to spot problems before users report them. Automatically document failed tests and errors. Make every failure actionable and easy to debug. Create a fast feedback loop between testers and dev teams throughout development cycle. -
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Plumbr
Plumbr
Expose metrics and set up alerts for ops. Detect and prioritize root causes for dev. Complete the devops feedback loop. Configure your application to send traces using Plumbr Agents. Capture end-to-end traces from user interaction throughout the microservices in the back-end. No code changes, no sampling, pure joy! Plumbr APM uses tracing to provide insights into your application’s performance. Plumbr has deep expertise in APM technology including Java profiling, byte code instrumentation (BCI), database monitoring and real user monitoring. Plumbr will help us equip customers with the power of Java Profiling and BCI, which is critical for deep visibility into traditional Java and .Net enterprise applications.Starting Price: $84 per month -
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Activeloop
Activeloop
Activeloop provides a continuous learning infrastructure for teams building software, agents, and data pipelines. Its core product, Deeplake, is the GPU database for agents, built around the idea that if your AI is on a GPU, your data should be too. Deeplake is designed to keep AI agents grounded, versioned, queryable, and GPU-native by combining vector and tensor data in one store, with GPU streaming to fine-tuning and a serverless Postgres interface. It gives teams a data engine for multimodal AI, allowing them to store, index, search, and stream data to models and agents. Instead of treating AI data as scattered files, embeddings, metadata, and traces across disconnected systems, Activeloop brings them into an infrastructure that can support retrieval, model development, fine-tuning, and agent memory workflows. It also includes Hivemind, where agent traces become team skills, so work solved once can be shared across the organization through trajectory capture. -
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Enter Code
Converge AI
Enter Code is a local AI super agent that runs in the terminal and is built for real engineering work across any stack, any project, and any output. It reads the relevant files, plans changes, writes code, runs tests, and helps users debug through natural language conversation. Short prompts can become concrete edits, verified answers, and fixes users can trust, with Enter Code analyzing the codebase, making implementation changes, checking results, and handing work back only after verification. It can answer architecture, data-flow, and side-effect questions with full project context by following request paths, related mutations, and async logic before responding. For debugging, Enter Code traces failures, patches code, adds regression coverage, and proves the issue stays fixed. It works across Go, Python, Rust, Java, TypeScript, backend services, CLI tools, mobile apps, data pipelines, and infrastructure code.Starting Price: $12 per month -
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Deductive AI
Deductive AI
Deductive AI is a cutting-edge platform that redefines how organizations handle complex system failures. By connecting your entire codebase with telemetry data, encompassing metrics, events, logs, and traces, Deductive AI empowers teams to pinpoint the root cause of issues with unprecedented precision and speed. It streamlines the process of debugging, significantly reducing downtime and improving overall system reliability. Deductive AI integrates with your codebase and observability tools, creating a unified knowledge graph powered by a code-aware reasoning engine to diagnose root causes like an expert engineer. It builds a knowledge graph with millions of nodes in seconds, uncovering deep relationships between codebase and telemetry data. It orchestrates hundreds of specialized AI agents to search, discover, and analyze breadcrumbs of root cause spread across all connected sources. -
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Origon
Origon
Origon is a full-stack AI agent development and operations platform engineered as a unified “Agentic Operating System” that supports the entire lifecycle of autonomous AI systems from design to deployment and observability. It offers an intuitive Studio for visual, drag-and-drop agent creation and configuration, Sessions for real-time observation, behavior tracing, and debugging, and Insights dashboards for performance analytics, reliability tracking, and outcome measurement in one place. Origon runs natively on dedicated infrastructure optimized for low-latency performance and security, avoiding dependency on external cloud APIs, and includes a built-in knowledge engine that connects agents to contextual memory and domain data so responses stay grounded and consistent. It supports hundreds of connectors and APIs, including chat, voice, WhatsApp, SMS, email, and telephony, and lets agents execute code and interact with real systems with a single click.Starting Price: $200 per month -
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LangSmith
LangChain
Unexpected results happen all the time. With full visibility into the entire chain sequence of calls, you can spot the source of errors and surprises in real time with surgical precision. Software engineering relies on unit testing to build performant, production-ready applications. LangSmith provides that same functionality for LLM applications. Spin up test datasets, run your applications over them, and inspect results without having to leave LangSmith. LangSmith enables mission-critical observability with only a few lines of code. LangSmith is designed to help developers harness the power–and wrangle the complexity–of LLMs. We’re not only building tools. We’re establishing best practices you can rely on. Build and deploy LLM applications with confidence. Application-level usage stats. Feedback collection. Filter traces, cost and performance measurement. Dataset curation, compare chain performance, AI-assisted evaluation, and embrace best practices. -
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Cortex AgentiX
Palo Alto Networks
Cortex AgentiX is the next-generation evolution of Cortex XSOAR®, designed by Palo Alto Networks to securely build, deploy, and govern AI-powered security agents. It enables organizations to unleash agentic AI that acts as intelligent teammates, capable of planning and executing complex workflows around the clock. Cortex AgentiX is powered by over 1.2 billion real-world playbook executions, providing agents with proven operational intelligence. The platform offers a rich library of ready-to-use agents while also supporting custom, no-code agent creation tailored to specific security needs. With built-in guardrails, Cortex AgentiX ensures agents operate with the appropriate level of autonomy, including human-in-the-loop approvals for critical actions. Full transparency allows teams to trace every agent decision, action, and outcome for audit and compliance purposes. Cortex AgentiX integrates seamlessly across the Cortex ecosystem to help organizations stay ahead of evolving threats. -
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Kloudfuse
Kloudfuse
Kloudfuse is an AI‑powered unified observability platform that scales cost‑effectively, combining metrics, logs, traces, events, and digital experience monitoring into a single observability data lake. It integrates with over 700 sources, agent‑based or open source, without re‑instrumentation, and supports open query languages like PromQL, LogQL, TraceQL, GraphQL, and SQL while enabling custom workflows through webhooks and notifications. Organizations can deploy Kloudfuse within their VPC using a simple single‑command install and manage it centrally via a control plane. It automatically ingests and indexes telemetry data with intelligent facets, enabling fast search, context‑aware ML‑based alerts, and SLOs with reduced false positives. Users gain full‑stack visibility, from frontend RUM and session replays to backend profiling, traces, and metrics, allowing navigation from user experience down to code‑level issues. -
35
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. -
36
Agent Builder
OpenAI
Agent Builder is part of OpenAI’s tooling for constructing agentic applications, systems that use large language models to perform multi-step tasks autonomously, with governance, tool integration, memory, orchestration, and observability baked in. The platform offers a composable set of primitives—models, tools, memory/state, guardrails, and workflow orchestration- that developers assemble into agents capable of deciding when to call a tool, when to act, and when to halt and hand off control. OpenAI provides a new Responses API that combines chat capabilities with built-in tool use, along with an Agents SDK (Python, JS/TS) that abstracts the control loop, supports guardrail enforcement (validations on inputs/outputs), handoffs between agents, session management, and tracing of agent executions. Agents can be augmented with built-in tools like web search, file search, or computer use, or custom function-calling tools. -
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potpie
potpie
Potpie is an open source platform that enables developers to create AI agents tailored to their codebases, automating tasks such as debugging, testing, system design, onboarding, code review, and documentation. By transforming your codebase into a comprehensive knowledge graph, Potpie's agents gain deep contextual understanding, allowing them to perform engineering tasks with high precision. It offers over five ready-to-use agents, including those specialized in stack trace analysis and integration test generation. Developers can also build custom agents using simple prompts, facilitating seamless integration into existing workflows. Potpie provides a user-friendly chat interface and supports a VS Code extension for direct integration into development environments. With features like multi-LLM support, developers can integrate various AI models to optimize performance and flexibility.Starting Price: $ 1 per month -
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ORION
ORION
ORION prevents data loss by analyzing data in motion with context-aware, proprietary AI agents, significantly reducing operational overhead and false positives while drastically increasing the number of real incidents detected and prevented. Our specialized agents understand the context behind every data trace in real-time, from classification, lineage, identity, environment, to external relations, analyze it for data loss indicators, detecting and preventing exfiltration. -
39
OpenAI Agents SDK
OpenAI
The OpenAI Agents SDK enables you to build agentic AI apps in a lightweight, easy-to-use package with very few abstractions. It's a production-ready upgrade of our previous experimentation for agents, Swarm. The Agents SDK has a very small set of primitives, agents, which are LLMs equipped with instructions and tools; handoffs, which allow agents to delegate to other agents for specific tasks; and guardrails, which enable the inputs to agents to be validated. In combination with Python, these primitives are powerful enough to express complex relationships between tools and agents, and allow you to build real-world applications without a steep learning curve. In addition, the SDK comes with built-in tracing that lets you visualize and debug your agentic flows, evaluate them, and even fine-tune models for your application.Starting Price: Free -
40
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 -
41
AgentKit
OpenAI
AgentKit is a unified suite of tools designed to streamline the process of building, deploying, and optimizing AI agents. It introduces Agent Builder, a visual canvas that lets developers compose multi-agent workflows via drag-and-drop nodes, set guardrails, preview runs, and version workflows. The Connector Registry centralizes the management of data and tool integrations across workspaces and ensures governance and access control. ChatKit enables frictionless embedding of agentic chat interfaces, customizable to match branding and experience, into web or app environments. To support robust performance and reliability, AgentKit enhances its evaluation infrastructure with datasets, trace grading, automated prompt optimization, and support for third-party models. It also supports reinforcement fine-tuning to push agent capabilities further.Starting Price: Free -
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Manufact
Manufact
Manufact is a platform to build and deploy MCP apps and servers, giving teams a fast path to the ChatGPT Apps Store, Claude Connectors, and every surface where users and agents already work. The mcp-use SDK is the full-stack MCP framework to develop MCP apps for ChatGPT and Claude, as well as MCP servers for AI agents. Manufact covers every step of the MCP lifecycle with no extra tools: build from an SDK, a skill, or a vibe; deploy with one push; publish with marketplace checklists and generated submission assets; iterate with Cloud Inspector; and monitor with analytics, session replay, traces, error rates, and alerts. Teams can scaffold with the MCP-use SDK, install a skill into a coding agent, describe an app and watch it scaffold, or drop in an existing MCP server unchanged. Manufact Cloud connects to a repo once, then every push auto-deploys, with preview URLs for pull requests, custom domains, and SSL handled.Starting Price: $25 per month -
43
Veriom
Veriom
Veriom is a security intelligence layer for architectural root cause analysis across the entire SDLC, built to show the misconfigured gateways, unsafe defaults, control failures, and structural weaknesses creating hundreds of vulnerabilities. It does not scan only for known vulnerabilities; it reasons about how the system is built and surfaces the risks the architecture is producing across code, cloud, CI/CD, production environments, trust boundaries, and delivery chains. Veriom builds a model of the actual environment, understands the architecture in under an hour, verifies findings against that environment, and traces every risk back to the control failure or architectural weakness that created it. Instead of leaving teams in an infinite patching loop with fragmented tools, generic risk scores, and individual fixes, Veriom focuses on why vulnerabilities exist and how one structural fix can close an entire risk class.Starting Price: $1,200 per month -
44
Mistral AI Studio
Mistral AI
Mistral AI Studio is a unified builder-platform that enables organizations and development teams to design, customize, deploy, and manage advanced AI agents, models, and workflows from proof-of-concept through to production. The platform offers reusable blocks, including agents, tools, connectors, guardrails, datasets, workflows, and evaluations, combined with observability and telemetry capabilities so you can track agent performance, trace root causes, and govern production AI operations with visibility. With modules like Agent Runtime to make multi-step AI behaviors repeatable and shareable, AI Registry to catalogue and manage model assets, and Data & Tool Connections for seamless integration with enterprise systems, Studio supports everything from fine-tuning open source models to embedding them in your infrastructure and rolling out enterprise-grade AI solutions.Starting Price: $14.99 per month -
45
OMS Trace Analytics
Objective Medical Systems
Enhance value-based care with the OMS Trace Analytics® cloud platform for the analysis and reporting of critical cardiovascular metrics. Increasingly reimbursement is being tied to value. For example, for the performance year 2018, 60% of Medicare reimbursements are being linked to quality under the Quality Payment Program. The need for a discrete data and evidence-based quality reporting solution to measure, target and improve your quality program is more critical than ever. The OMS Trace Analytics® cloud platform is designed to deliver deep clinical insights for cardiovascular diseases with dedicated dashboards for leading cardiovascular diseases like Hypertension, Dyslipidemia, Atrial Fibrillation, Heart Failure, Coronary Artery Disease and Peripheral Artery Disease. -
46
FloTorch
FloTorch
FloTorch is an enterprise platform designed for teams to securely and rapidly build, deploy, and scale agentic workflows. It accelerates the journey from prototyping to production by providing highly scalable, pluggable endpoints. The platform incorporates built-in observability, evaluation, and automated request routing to ensure that agents are performant and optimized for cost, latency, and throughput. With FloTorch you can Evaluate and optimize your workflows against your own specific performance metrics for cost, latency, and throughput. Use agentic assets in multiple ways—from no-code interfaces to SDKs and assistants. Plug and play models seamlessly without changing your existing workflows Gain full visibility with built-in observability and tracing -
47
Trace
Tracework.ai
Struggling to onboard new team members or hand over tasks quickly? 🚀 Trace helps you document best-practice workflows and hack-arounds in seconds; making onboarding, async demos, and knowledge sharing seamless. Capture and share how-to guides in seconds. Instantly create step-by-step instructions for any task—so you can stop repeating yourself and focus on the work that matters. Trace records your process quietly in the background as you go. Just hit “Start Recording.” It automatically turns your actions into a clear, visual guide. Share it instantly with your team. The best part? The links always reflect the latest version. You’re great at what you do—now let others learn from you. With Trace, it only takes moments. Skip the manual documentation with guides that write themselves. Customize each guide with your own notes, images, and steps. Share knowledge effortlessly with one-click access. Cut down on repeat questions by embedding guides directly into your existing tools.Starting Price: $78 Lifetime deal -
48
TierZero
TierZero
TierZero Production Agents investigate incidents, triage alerts, and fix production problems automatically so your engineers can ship faster. When an incident fires, TierZero joins and starts investigating across your full stack: logs, traces, metrics, deploys, code changes, and past incidents. Unlike standalone AI SRE tools that stop at triage, Production Agents cover the full post-merge lifecycle including investigation, remediation, support Q&A, and proactive discovery. TierZero’s Context Engine synthesizes signals from code, infrastructure, conversations, and documents into a living knowledge graph that gets smarter with every issue resolved. Deploy in your environment in under an hour. Every AI investigation is auditable. Built for regulated industries (fintech, healthcare, crypto) where security isn’t optional. -
49
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. -
50
Hamming
Hamming
Prompt optimization, automated voice testing, monitoring, and more. Test your AI voice agent against 1000s of simulated users in minutes. AI voice agents are hard to get right. A small change in prompts, function call definitions or model providers can cause large changes in LLM outputs. We're the only end-to-end platform that supports you from development to production. You can store, manage, version, and keep your prompts synced with voice infra providers from Hamming. This is 1000x more efficient than testing your voice agents by hand. Use our prompt playground to test LLM outputs on a dataset of inputs. Our LLM judges the quality of generated outputs. Save 80% of manual prompt engineering effort. Go beyond passive monitoring. We actively track and score how users are using your AI app in production and flag cases that need your attention using LLM judges. Easily convert calls and traces into test cases and add them to your golden dataset.
