Alternatives to Netra
Compare Netra alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Netra in 2026. Compare features, ratings, user reviews, pricing, and more from Netra competitors and alternatives in order to make an informed decision for your business.
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1
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
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. -
3
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.Starting Price: $99/month -
4
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 -
5
LangChain
LangChain
LangChain is a powerful, composable framework designed for building, running, and managing applications powered by large language models (LLMs). It offers an array of tools for creating context-aware, reasoning applications, allowing businesses to leverage their own data and APIs to enhance functionality. LangChain’s suite includes LangGraph for orchestrating agent-driven workflows, and LangSmith for agent observability and performance management. Whether you're building prototypes or scaling full applications, LangChain offers the flexibility and tools needed to optimize the LLM lifecycle, with seamless integrations and fault-tolerant scalability. -
6
HumanLayer
HumanLayer
HumanLayer is an API and SDK that enables AI agents to contact humans for feedback, input, and approvals. It guarantees human oversight of high-stakes function calls with approval workflows across Slack, email, and more. By integrating with your preferred Large Language Model (LLM) and framework, HumanLayer empowers AI agents with safe access to the world. The platform supports various frameworks and LLMs, including LangChain, CrewAI, ControlFlow, LlamaIndex, Haystack, OpenAI, Claude, Llama3.1, Mistral, Gemini, and Cohere. HumanLayer offers features such as approval workflows, human-as-tool integration, and custom responses with escalations. Pre-fill response prompts for seamless human-agent interactions. Route to specific individuals or teams, and control which users can approve or respond to LLM requests. Invert the flow of control, from human-initiated to agent-initiated. Add a variety of human contact channels to your agent toolchain.Starting Price: $500 per month -
7
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. -
8
Crewship
Crewship
Crewship is the developer-first platform for deploying AI agent workflows. Deploy your CrewAI, LangGraph, and LangGraph.js agents with a single command and watch them execute in real-time. Key features include one-command deployment, real-time execution streaming, artifact management, auto-scaling, version control, and encrypted secrets management. Crewship handles infrastructure so developers can focus on building great AI agents. Multi-framework support with AutoGen, Pydantic AI, smolagents, OpenAI Agents, Mastra, and Agno coming soon.Starting Price: Free -
9
Lunary
Lunary
Lunary is an AI developer platform designed to help AI teams manage, improve, and protect Large Language Model (LLM) chatbots. It offers features such as conversation and feedback tracking, analytics on costs and performance, debugging tools, and a prompt directory for versioning and team collaboration. Lunary supports integration with various LLMs and frameworks, including OpenAI and LangChain, and provides SDKs for Python and JavaScript. Guardrails to deflect malicious prompts and sensitive data leaks. Deploy in your VPC with Kubernetes or Docker. Allow your team to judge responses from your LLMs. Understand what languages your users are speaking. Experiment with prompts and LLM models. Search and filter anything in milliseconds. Receive notifications when agents are not performing as expected. Lunary's core platform is 100% open-source. Self-host or in the cloud, get started in minutes.Starting Price: $20 per month -
10
Agency
Agency
Agency helps enterprises build, evaluate, and monitor AI agents. From the team at AgentOps.ai. Agen.cy (Agency AI) develops cutting edge AI agents using CrewAI, AutoGen, CamelAI, LLamaIndex, Langchain, Cohere, MultiOn + many more. -
11
LangGraph
LangChain
Gain precision and control with LangGraph to build agents that reliably handle complex tasks. Build and scale agentic applications with LangGraph Platform. LangGraph's flexible framework supports diverse control flows – single agent, multi-agent, hierarchical, sequential – and robustly handles realistic, complex scenarios. Ensure reliability with easy-to-add moderation and quality loops that prevent agents from veering off course. Use LangGraph Platform to templatize your cognitive architecture so that tools, prompts, and models are easily configurable with LangGraph Platform Assistants. With built-in statefulness, LangGraph agents seamlessly collaborate with humans by writing drafts for review and awaiting approval before acting. Easily inspect the agent’s actions and "time-travel" to roll back and take a different action to correct course.Starting Price: Free -
12
DeepEval
Confident AI
DeepEval is a simple-to-use, open source LLM evaluation framework, for evaluating and testing large-language model systems. It is similar to Pytest but specialized for unit testing LLM outputs. DeepEval incorporates the latest research to evaluate LLM outputs based on metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., which uses LLMs and various other NLP models that run locally on your machine for evaluation. Whether your application is implemented via RAG or fine-tuning, LangChain, or LlamaIndex, DeepEval has you covered. With it, you can easily determine the optimal hyperparameters to improve your RAG pipeline, prevent prompt drifting, or even transition from OpenAI to hosting your own Llama2 with confidence. The framework supports synthetic dataset generation with advanced evolution techniques and integrates seamlessly with popular frameworks, allowing for efficient benchmarking and optimization of LLM systems.Starting Price: Free -
13
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. -
14
Literal AI
Literal AI
Literal AI is a collaborative platform designed to assist engineering and product teams in developing production-grade Large Language Model (LLM) applications. It offers a suite of tools for observability, evaluation, and analytics, enabling efficient tracking, optimization, and integration of prompt versions. Key features include multimodal logging, encompassing vision, audio, and video, prompt management with versioning and AB testing capabilities, and a prompt playground for testing multiple LLM providers and configurations. Literal AI integrates seamlessly with various LLM providers and AI frameworks, such as OpenAI, LangChain, and LlamaIndex, and provides SDKs in Python and TypeScript for easy instrumentation of code. The platform also supports the creation of experiments against datasets, facilitating continuous improvement and preventing regressions in LLM applications. -
15
Chainlit
Chainlit
Chainlit is an open-source Python package designed to expedite the development of production-ready conversational AI applications. With Chainlit, developers can build and deploy chat-based interfaces in minutes, not weeks. The platform offers seamless integration with popular AI tools and frameworks, including OpenAI, LangChain, and LlamaIndex, allowing for versatile application development. Key features of Chainlit include multimodal capabilities, enabling the processing of images, PDFs, and other media types to enhance productivity. It also provides robust authentication options, supporting integration with providers like Okta, Azure AD, and Google. The Prompt Playground feature allows developers to iterate on prompts in context, adjusting templates, variables, and LLM settings for optimal results. For observability, Chainlit offers real-time visualization of prompts, completions, and usage metrics, ensuring efficient and trustworthy LLM operations. -
16
LangMem
LangChain
LangMem is a lightweight, flexible Python SDK from LangChain that equips AI agents with long-term memory capabilities, enabling them to extract, store, update, and retrieve meaningful information from past interactions to become smarter and more personalized over time. It supports three memory types and offers both hot-path tools for real-time memory management and background consolidation for efficient updates beyond active sessions. Through a storage-agnostic core API, LangMem integrates seamlessly with any backend and offers native compatibility with LangGraph’s long-term memory store, while also allowing type-safe memory consolidation using schemas defined in Pydantic. Developers can incorporate memory tools into agents using simple primitives to enable seamless memory creation, retrieval, and prompt optimization within conversational flows. -
17
Cognee
Cognee
Cognee is an open source AI memory engine that transforms raw data into structured knowledge graphs, enhancing the accuracy and contextual understanding of AI agents. It supports various data types, including unstructured text, media files, PDFs, and tables, and integrates seamlessly with several data sources. Cognee employs modular ECL pipelines to process and organize data, enabling AI agents to retrieve relevant information efficiently. It is compatible with vector and graph databases and supports LLM frameworks like OpenAI, LlamaIndex, and LangChain. Key features include customizable storage options, RDF-based ontologies for smart data structuring, and the ability to run on-premises, ensuring data privacy and compliance. Cognee's distributed system is scalable, capable of handling large volumes of data, and is designed to reduce AI hallucinations by providing AI agents with a coherent and interconnected data landscape.Starting Price: $25 per month -
18
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 -
19
Kayba
Kayba
Kayba makes AI agents self-improve from experience. It learns from an agent’s execution traces to detect failures, fix them, and measure whether the fix actually worked. Instead of relying on generic evals that cannot explain why an agent failed, Kayba derives failure modes from the agent’s own traces and builds custom benchmarks for the user’s domain, so teams can measure improvement against real production failure patterns. Kayba wires tracing into an agent with one line of setup, watches it around the clock, and flags the moment a step stops being recorded. Even good tracing rots as teams ship changes, and steps can quietly stop being captured; Kayba checks the tracing users already have, shows exactly what is broken, points to the file that needs attention, and sends the gap to a coding agent through MCP. The coding agent patches the issue, and Kayba verifies that the trace is actually closed.Starting Price: Free -
20
Agent Communication Protocol (ACP)
The Linux Foundation
The Agent Communication Protocol (ACP) is an open interoperability standard designed to enable seamless communication between AI agents, applications, and human users. It provides a standardized RESTful API that supports synchronous and asynchronous interactions, streaming communication, long-running tasks, and both stateful and stateless operations. ACP is framework-agnostic, allowing agents built with technologies such as BeeAI, LangChain, CrewAI, or custom solutions to work together without requiring changes to their internal architecture. The protocol supports all content modalities through MimeTypes, making it flexible enough to handle text, images, audio, video, and custom data formats. ACP also includes capabilities for online and offline agent discovery, helping organizations find and connect compatible agents across different environments.Starting Price: Free -
21
PromptLayer
PromptLayer
The first platform built for prompt engineers. Log OpenAI requests, search usage history, track performance, and visually manage prompt templates. manage Never forget that one good prompt. GPT in prod, done right. Trusted by over 1,000 engineers to version prompts and monitor API usage. Start using your prompts in production. To get started, create an account by clicking “log in” on PromptLayer. Once logged in, click the button to create an API key and save this in a secure location. After making your first few requests, you should be able to see them in the PromptLayer dashboard! You can use PromptLayer with LangChain. LangChain is a popular Python library aimed at assisting in the development of LLM applications. It provides a lot of helpful features like chains, agents, and memory. Right now, the primary way to access PromptLayer is through our Python wrapper library that can be installed with pip.Starting Price: Free -
22
FastAgency
FastAgency
FastAgency is an open source framework designed to accelerate the deployment of multi-agent AI workflows from prototype to production. It provides a unified programming interface compatible with various agentic AI frameworks, enabling developers to deploy agentic workflows in both development and production settings. With features like multi-runtime support, seamless external API integration, and a command-line interface for orchestration, FastAgency simplifies the creation of scalable, production-ready architectures for serving AI workflows. Currently, it supports the AutoGen framework, with plans to extend support to CrewAI, Swarm, and LangGraph in the future. Developers can easily switch between frameworks, choosing the best one for their project's specific needs. FastAgency also features a common programming interface that enables the development of core workflows once and reuse them across various user interfaces without rewriting code.Starting Price: Free -
23
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 -
24
RA.Aid
RA.Aid
RA.Aid is an open source AI assistant that autonomously handles research, planning, and implementation to expedite software development processes. Built on LangGraph's agent-based task execution framework, RA.Aid operates through a three-stage architecture. RA.Aid supports multiple AI providers, including Anthropic's Claude, OpenAI, OpenRouter, and Gemini, allowing users to select models that best fit their requirements. It also features web research capabilities, enabling the agent to pull real-time information from the internet to enhance its understanding and execution of tasks. It offers an interactive chat mode, allowing users to guide the agent directly, ask questions, or redirect tasks as needed. Additionally, RA.Aid integrates with 'aider' via the '--use-aider' flag to leverage specialized code editing capabilities. It is designed with a human-in-the-loop interaction mode, enabling the agent to seek user input during task execution to ensure higher accuracy.Starting Price: Free -
25
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 -
26
EarlyCore
EarlyCore
EarlyCore is a security platform built for AI agents. It automates pre-production attack testing, real-time monitoring, and compliance reporting across the full agent lifecycle. Scans agents against thousands of attack scenarios covering prompt injection, jailbreaking, data exfiltration, tool misuse, and supply chain threats. In production, tracks every agent action, establishes behavioral baselines, and flags anomalies in real time. Alerts push to Slack, email, or webhooks. Compliance docs generate automatically, mapped to ISO 42001, NIST AI RMF, EU AI Act, SOC 2, and GDPR. Always audit-ready. Deploys in 15 minutes with zero code changes. Integrates with AWS Bedrock, Gemini Enterprise Agent Platform, LangChain, and more. Multi-tenant support for agencies and MSSPs. Built for security teams, agencies, and MSSPs securing AI agents at scale.Starting Price: $100/month -
27
AI Autopilot
AI Autopilot
AI Autopilot is an advanced agentic AI automation platform designed specifically for MSPs to streamline IT operations with intelligent automation. It provides specialized AI agents that handle ticket triage, prioritization, routing, escalation, and SLA monitoring with MSP-grade accuracy. The system integrates natively with major PSA, RMM, documentation, and automation tools like ConnectWise, Autotask, Ninja RMM, IT Glue, Liongard, and Rewst. By automating repetitive tasks, AI Autopilot helps MSPs resolve tickets faster, reduce labor costs, and deliver 24/7 support coverage. Users can even enable ticket creation directly from Microsoft Teams and Slack for a frictionless support experience. With upcoming integrations like MCP, CrewAI, LangChain, and deep RPA orchestration, the platform continues to evolve into a next-generation multi-agent AI infrastructure for MSPs.Starting Price: $99/month -
28
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 -
29
Naptha
Naptha
Naptha is a modular AI platform for autonomous agents that empowers developers and researchers to build, deploy, and scale cooperative multi‑agent systems on the agentic web. Its core innovations include Agent Diversity, which continuously upgrades performance by orchestrating diverse models, tools, and architectures; Horizontal Scaling, which supports collaborative networks of millions of AI agents; Self‑Evolved AI, where agents learn and optimize themselves beyond human‑designed capabilities; and AI Agent Economies, which enable autonomous agents to generate useful goods and services. Naptha integrates seamlessly with popular frameworks and infrastructure, LangChain, AgentOps, CrewAI, IPFS, NVIDIA stacks, and more, via a Python SDK that upgrades existing agent frameworks with next‑generation enhancements. Developers can extend or publish reusable components on the Naptha Hub, run full agent stacks anywhere a container can execute on Naptha Nodes. -
30
AgentSea
AgentSea
AgentSea is an open source platform designed to build, deploy, and share AI agents with ease. It delivers a collection of libraries and tools for building AI agent apps, favoring the UNIX philosophy of doing one thing well. Tools can be used individually or stacked together into a single agent app, and are compatible with frameworks like LlamaIndex and LangChain. Key components include SurfKit, a Kubernetes-style orchestrator for agents; DeviceBay, offering pluggable devices like file systems and desktops; ToolFuse, a library that wraps scripts, third-party apps, and APIs as Tool implementations; AgentD, a daemon making a Linux desktop OS accessible to bots; AgentDesk, a library for running AgentD-powered VMs; Taskara, for task management; ThreadMem, for building multi-role persistent threads; and MLLM, simplifying communication with multiple LLMs and multimodal LLMs. AgentSea also offers alpha agents like SurfPizza and SurfSlicer, which navigate GUIs using multimodal approaches.Starting Price: Free -
31
NVIDIA NeMo Guardrails
NVIDIA
NVIDIA NeMo Guardrails is an open-source toolkit designed to enhance the safety, security, and compliance of large language model-based conversational applications. It enables developers to define, orchestrate, and enforce multiple AI guardrails, ensuring that generative AI interactions remain accurate, appropriate, and on-topic. The toolkit leverages Colang, a specialized language for designing flexible dialogue flows, and integrates seamlessly with popular AI development frameworks like LangChain and LlamaIndex. NeMo Guardrails offers features such as content safety, topic control, personal identifiable information detection, retrieval-augmented generation enforcement, and jailbreak prevention. Additionally, the recently introduced NeMo Guardrails microservice simplifies rail orchestration with API-based interaction and tools for enhanced guardrail management and maintenance. -
32
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 -
33
NotiLens
NotiLens
NotiLens is a real-time alerting and monitoring platform that notifies founders and dev teams when critical events fail, spike, or go unexpectedly silent. Core functionality includes real-time push alerts, ML-powered anomaly detection that learns your baseline automatically, and silence detection that alerts when expected activity stops arriving. On-call scheduling with rotating shifts, escalation policies that auto-page the next person on no acknowledgement, and per-user DND with timezone-aware quiet hours ensure alerts always reach the right person. Broken flow detection monitors multi-step event sequences and alerts when they don't complete. AI agent monitoring tracks token usage, API response times, and cost spikes. Automation monitoring covers n8n, Zapier, and Make for silent failures. 40+ integrations: Stripe, Shopify, GitHub, Vercel, Sentry, Datadog, AWS, LangChain. SDKs for Python, Node.js, Go, Rust, Ruby, PHP, Java. MCP support for Claude and GPT. iOS and Android appsStarting Price: $29/month -
34
AvonAI
AvonAI
AvonAI keeps your AI agents aligned with your business by monitoring every customer conversation, controlling every interaction, and helping teams trust every outcome at scale. Your agents are live, handling real conversations with real customers, but agents do not manage themselves: they go off-script, drift from policies, and cannot keep up with business changes on their own. AvonAI reads every interaction and surfaces only the ones that matter, including policy violations, hallucinations, missing disclaimers, and other behavioral drift, so teams can find and fix risks in hours instead of weeks. It lets operations teams update agent knowledge and steer behavior in plain language, with no code and no developer ticket, while showing exactly what will change and allowing validation before anything goes live. AvonAI continuously tests agents against business directives, so the moment a model, prompt, or knowledge source changes, teams know whether the agent still behaves as intended. -
35
Cake AI
Cake AI
Cake AI is a comprehensive AI infrastructure platform that enables teams to build and deploy AI applications using hundreds of pre-integrated open source components, offering complete visibility and control. It provides a curated, end-to-end selection of fully managed, best-in-class commercial and open source AI tools, with pre-built integrations across the full breadth of components needed to move an AI application into production. Cake supports dynamic autoscaling, comprehensive security measures including role-based access control and encryption, advanced monitoring, and infrastructure flexibility across various environments, including Kubernetes clusters and cloud services such as AWS. Its data layer equips teams with tools for data ingestion, transformation, and analytics, leveraging tools like Airflow, DBT, Prefect, Metabase, and Superset. For AI operations, Cake integrates with model catalogs like Hugging Face and supports modular workflows using LangChain, LlamaIndex, and more. -
36
Agno
Agno
Agno is a lightweight framework for building agents with memory, knowledge, tools, and reasoning. Developers use Agno to build reasoning agents, multimodal agents, teams of agents, and agentic workflows. Agno also provides a beautiful UI to chat with agents and tools to monitor and evaluate their performance. It is model-agnostic, providing a unified interface to over 23 model providers, with no lock-in. Agents instantiate in approximately 2μs on average (10,000x faster than LangGraph) and use about 3.75KiB memory on average (50x less than LangGraph). Agno supports reasoning as a first-class citizen, allowing agents to "think" and "analyze" using reasoning models, ReasoningTools, or a custom CoT+Tool-use approach. Agents are natively multimodal and capable of processing text, image, audio, and video inputs and outputs. The framework offers an advanced multi-agent architecture with three modes, route, collaborate, and coordinate.Starting Price: Free -
37
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 -
38
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. -
39
PyGPT
PyGPT
PyGPT is an open source, personal desktop AI assistant for Linux, Windows, and Mac, written in Python. It works similarly to ChatGPT, but locally on a desktop computer, with chat, vision, agents, image and video generation, tools, voice control, and more. PyGPT supports multiple models, including OpenAI GPT-5, GPT-4, o1, o3, o4, Google Gemini, Anthropic Claude, xAI Grok, Perplexity Sonar, DeepSeek, Mistral AI, and models accessible through Ollama and LlamaIndex. It offers 12 modes of operation, including chat, chat with files, realtime + audio, research, completion, image and video generation, vision, assistants, experts, computer use, agents, and autonomous mode. Users can chat with their own files and data using integrated LlamaIndex support. PyGPT includes built-in vector database support, automated files and data embedding, full conversation context, short- and long-term memory, internet access through Google, Microsoft Bing, and DuckDuckGo, plus speech synthesis and recognition.Starting Price: Free -
40
Langdock
Langdock
Native support for ChatGPT and LangChain. Bing, HuggingFace and more coming soon. Add your API documentation manually or import an existing OpenAPI specification. Access the request prompt, parameters, headers, body and more. Inspect detailed live metrics about how your plugin is performing, including latencies, errors, and more. Configure your own dashboards, track funnels and aggregated metrics.Starting Price: Free -
41
DemoGPT
Melih Ünsal
DemoGPT is an open source platform that simplifies the creation of LLM (Large Language Model) agents by providing an all-in-one toolkit. It offers tools, frameworks, prompts, and models for rapid agent development. The platform automatically generates LangChain code, which can be used for creating interactive applications with Streamlit. DemoGPT translates user instructions into functional applications through a multi-step process: planning, task creation, and code generation. It supports a streamlined approach to building AI-powered agents, offering an accessible environment for developing sophisticated, production-ready solutions with GPT-3.5-turbo. Additionally, it integrates API usage and external API interaction in future updates.Starting Price: Free -
42
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 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.Starting Price: Free -
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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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TelemetryHub
TelemetryHub by Scout APM
Built on the open-source framework OpenTelemetry, TelemetryHub is the ultimate application monitoring tool with correlated logs and metrics. TelemetryHub provides a single pane of glass for all logs, metrics, and tracing data. A Simple, out-of-the-box observability tool that visualizes all your system telemetry data in a consumable format with no proprietary agent that results in vendor lock-in.Starting Price: Free -
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OpenTelemetry
OpenTelemetry
High-quality, ubiquitous, and portable telemetry to enable effective observability. OpenTelemetry is a collection of tools, APIs, and SDKs. Use it to instrument, generate, collect, and export telemetry data (metrics, logs, and traces) to help you analyze your software’s performance and behavior. OpenTelemetry is generally available across several languages and is suitable for use. Create and collect telemetry data from your services and software, then forward them to a variety of analysis tools. OpenTelemetry integrates with popular libraries and frameworks such as Spring, ASP.NET Core, Express, Quarkus, and more! Installation and integration can be as simple as a few lines of code. 100% Free and Open Source, OpenTelemetry is adopted and supported by industry leaders in the observability space. -
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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 -
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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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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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Mirascope
Mirascope
Mirascope is an open-source library built on Pydantic 2.0 for the most clean, and extensible prompt management and LLM application building experience. Mirascope is a powerful, flexible, and user-friendly library that simplifies the process of working with LLMs through a unified interface that works across various supported providers, including OpenAI, Anthropic, Mistral, Gemini, Groq, Cohere, LiteLLM, Azure AI, Gemini Enterprise Agent Platform, and Bedrock. Whether you're generating text, extracting structured information, or developing complex AI-driven agent systems, Mirascope provides the tools you need to streamline your development process and create powerful, robust applications. Response models in Mirascope allow you to structure and validate the output from LLMs. This feature is particularly useful when you need to ensure that the LLM's response adheres to a specific format or contains certain fields.