Alternatives to LangWatch

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

  • 1
    Vertex AI
    Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection. Vertex AI Agent Builder enables developers to create and deploy enterprise-grade generative AI applications. It offers both no-code and code-first approaches, allowing users to build AI agents using natural language instructions or by leveraging frameworks like LangChain and LlamaIndex.
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  • 2
    StackAI

    StackAI

    StackAI

    StackAI is an enterprise AI automation platform to build end-to-end internal tools and processes with AI agents in a fully compliant and secure way. Designed for large organizations, it enables teams to automate complex workflows across operations, compliance, finance, IT, and support without heavy engineering. With StackAI you can: • Connect knowledge bases (SharePoint, Confluence, Notion, Google Drive, databases) with versioning, citations, and access controls. • Deploy AI agents as chat assistants, advanced forms, or APIs integrated into Slack, Teams, Salesforce, HubSpot, or ServiceNow. • Govern usage with enterprise security: SSO (Okta, Azure AD, Google), RBAC, audit logs, PII masking, data residency, and cost controls. • Route across OpenAI, Anthropic, Google, or local LLMs with guardrails, evaluations, and testing. • Start fast with templates for Contract Analyzer, Support Desk, RFP Response, Investment Memo Generator, and more.
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  • 3
    NVIDIA NeMo Guardrails
    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.
  • 4
    Lunary

    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
  • 5
    LangSmith

    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.
  • 6
    Amazon Bedrock Guardrails
    Amazon Bedrock Guardrails is a configurable safeguard system designed to enhance the safety and compliance of generative AI applications built on Amazon Bedrock. It enables developers to implement customized safety, privacy, and truthfulness controls across various foundation models, including those hosted within Amazon Bedrock, fine-tuned models, and self-hosted models. Guardrails provide a consistent approach to enforcing responsible AI policies by evaluating both user inputs and model responses based on defined policies. These policies include content filters for harmful text and image content, denial of specific topics, word filters for undesirable terms, sensitive information filters to redact personally identifiable information, and contextual grounding checks to detect and filter hallucinations in model responses.
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    LangChain

    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.
  • 8
    Orq.ai

    Orq.ai

    Orq.ai

    Orq.ai is the #1 platform for software teams to operate agentic AI systems at scale. Optimize prompts, deploy use cases, and monitor performance, no blind spots, no vibe checks. Experiment with prompts and LLM configurations before moving to production. Evaluate agentic AI systems in offline environments. Roll out GenAI features to specific user groups with guardrails, data privacy safeguards, and advanced RAG pipelines. Visualize all events triggered by agents for fast debugging. Get granular control on cost, latency, and performance. Connect to your favorite AI models, or bring your own. Speed up your workflow with out-of-the-box components built for agentic AI systems. Manage core stages of the LLM app lifecycle in one central platform. Self-hosted or hybrid deployment with SOC 2 and GDPR compliance for enterprise security.
  • 9
    Chainlit

    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.
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    Dynamiq

    Dynamiq

    Dynamiq

    Dynamiq is a platform built for engineers and data scientists to build, deploy, test, monitor and fine-tune Large Language Models for any use case the enterprise wants to tackle. Key features: 🛠️ Workflows: Build GenAI workflows in a low-code interface to automate tasks at scale 🧠 Knowledge & RAG: Create custom RAG knowledge bases and deploy vector DBs in minutes 🤖 Agents Ops: Create custom LLM agents to solve complex task and connect them to your internal APIs 📈 Observability: Log all interactions, use large-scale LLM quality evaluations 🦺 Guardrails: Precise and reliable LLM outputs with pre-built validators, detection of sensitive content, and data leak prevention 📻 Fine-tuning: Fine-tune proprietary LLM models to make them your own
    Starting Price: $125/month
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    Tenable AI Exposure
    Tenable AI Exposure is an agentless, enterprise-grade solution embedded within the Tenable One exposure management platform that provides visibility, context, and control over how teams use generative AI tools like ChatGPT Enterprise and Microsoft Copilot. It enables organizations to monitor user interactions with AI platforms, including who is using them, what data is involved, and how workflows are executed, while detecting and remediating risks such as misconfigurations, unsafe integrations, and exposure of sensitive information (like PII, PCI, or proprietary enterprise data). It also defends against prompt injections, jailbreak attempts, policy violations, and other advanced threats by enforcing security guardrails without disrupting operations. Supported across major AI platforms and deployed in minutes with no downtime, Tenable AI Exposure helps organizations govern AI usage as a core part of their cyber risk strategy.
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    WebOrion Protector Plus
    WebOrion Protector Plus is a GPU-powered GenAI firewall engineered to provide mission-critical protection for generative AI applications. It offers real-time defenses against evolving threats such as prompt injection attacks, sensitive data leakage, and content hallucinations. Key features include prompt injection attack protection, safeguarding intellectual property and personally identifiable information (PII) from exposure, content moderation and validation to ensure accurate and on-topic LLM responses, and user input rate limiting to mitigate risks of security vulnerability exploitation and unbounded consumption. At the core of its capabilities is ShieldPrompt, a multi-layered defense system that utilizes context evaluation through LLM analysis of user prompts, canary checks by embedding fake prompts to detect potential data leaks, pand revention of jailbreaks using Byte Pair Encoding (BPE) tokenization with adaptive dropout.
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    Langdock

    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.
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    iLangL Cloud
    iLangL Cloud is a middleware that is aimed to safely transfer content between content management systems and translation tools. iLangL serves as a bridge between a CMS and the following translation tools - Memsource, memoQ, and MultiTrans - helping users to easily transfer content between CMS and a translation tool. By using iLangL Cloud, you can be sure that all the content will go through safely to a translation tool and back, without damage to any sensitive data.
    Starting Price: $125 per month
  • 15
    Lanai

    Lanai

    Lanai

    Lanai is an AI empowerment platform designed to help enterprises navigate the complexities of AI adoption by providing visibility into AI interactions, safeguarding sensitive data, and accelerating successful AI initiatives. The platform offers features such as AI visibility to discover prompt interactions across applications and teams, risk monitoring to track compliance and identify potential exposures, and progress tracking to measure adoption against strategic targets. Additionally, Lanai provides policy intelligence and guardrails to proactively safeguard sensitive data and ensure compliance, as well as in-context protection and guidance to help users route queries appropriately while maintaining document integrity. To enhance AI interactions, the platform includes smart prompt coaching for real-time guidance, personalized insights into top use cases and applications, and manager and user reports to accelerate enterprise usage and return on investment.
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    Atla

    Atla

    Atla

    Atla is the agent observability and evaluation platform that dives deeper to help you find and fix AI agent failures. It provides real‑time visibility into every thought, tool call, and interaction so you can trace each agent run, understand step‑level errors, and identify root causes of failures. Atla automatically surfaces recurring issues across thousands of traces, stops you from manually combing through logs, and delivers specific, actionable suggestions for improvement based on detected error patterns. You can experiment with models and prompts side by side to compare performance, implement recommended fixes, and measure how changes affect completion rates. Individual traces are summarized into clean, readable narratives for granular inspection, while aggregated patterns give you clarity on systemic problems rather than isolated bugs. Designed to integrate with tools you already use, OpenAI, LangChain, Autogen AI, Pydantic AI, and more.
  • 17
    LangGraph

    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.
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    Maxim

    Maxim

    Maxim

    Maxim is an agent simulation, evaluation, and observability platform that empowers modern AI teams to deploy agents with quality, reliability, and speed. Maxim's end-to-end evaluation and data management stack covers every stage of the AI lifecycle, from prompt engineering to pre & post release testing and observability, data-set creation & management, and fine-tuning. Use Maxim to simulate and test your multi-turn workflows on a wide variety of scenarios and across different user personas before taking your application to production. Features: Agent Simulation Agent Evaluation Prompt Playground Logging/Tracing Workflows Custom Evaluators- AI, Programmatic and Statistical Dataset Curation Human-in-the-loop Use Case: Simulate and test AI agents Evals for agentic workflows: pre and post-release Tracing and debugging multi-agent workflows Real-time alerts on performance and quality Creating robust datasets for evals and fine-tuning Human-in-the-loop workflows
    Starting Price: $29/seat/month
  • 19
    Prompt flow

    Prompt flow

    Microsoft

    Prompt Flow is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, and evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality. With Prompt Flow, you can create flows that link LLMs, prompts, Python code, and other tools together in an executable workflow. It allows for debugging and iteration of flows, especially tracing interactions with LLMs with ease. You can evaluate your flows, calculate quality and performance metrics with larger datasets, and integrate the testing and evaluation into your CI/CD system to ensure quality. Deployment of flows to the serving platform of your choice or integration into your app’s code base is made easy. Additionally, collaboration with your team is facilitated by leveraging the cloud version of Prompt Flow in Azure AI.
  • 20
    SciPhi

    SciPhi

    SciPhi

    Intuitively build your RAG system with fewer abstractions compared to solutions like LangChain. Choose from a wide range of hosted and remote providers for vector databases, datasets, Large Language Models (LLMs), application integrations, and more. Use SciPhi to version control your system with Git and deploy from anywhere. The platform provided by SciPhi is used internally to manage and deploy a semantic search engine with over 1 billion embedded passages. The team at SciPhi will assist in embedding and indexing your initial dataset in a vector database. The vector database is then integrated into your SciPhi workspace, along with your selected LLM provider.
    Starting Price: $249 per month
  • 21
    Mistral AI Studio
    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
  • 22
    LangFast

    LangFast

    Langfa.st

    LangFast is a lightweight prompt testing platform designed for product teams, prompt engineers, and developers working with LLMs. It offers instant access to a customizable prompt playground—no signup required. Users can build, test, and share prompt templates using Jinja2 syntax with real-time raw outputs directly from the LLM, without any API abstractions. LangFast eliminates the friction of manual testing by letting teams validate prompts, iterate faster, and collaborate more effectively. Built by a team with experience scaling AI SaaS to 15M+ users, LangFast gives you full control over the prompt development process—while keeping costs predictable through a simple pay-as-you-go model.
    Starting Price: $60 one time
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    FinetuneDB

    FinetuneDB

    FinetuneDB

    Capture production data, evaluate outputs collaboratively, and fine-tune your LLM's performance. Know exactly what goes on in production with an in-depth log overview. Collaborate with product managers, domain experts and engineers to build reliable model outputs. Track AI metrics such as speed, quality scores, and token usage. Copilot automates evaluations and model improvements for your use case. Create, manage, and optimize prompts to achieve precise and relevant interactions between users and AI models. Compare foundation models, and fine-tuned versions to improve prompt performance and save tokens. Collaborate with your team to build a proprietary fine-tuning dataset for your AI models. Build custom fine-tuning datasets to optimize model performance for specific use cases.
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    LangMem

    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.
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    ZenGuard AI

    ZenGuard AI

    ZenGuard AI

    ZenGuard AI is a security platform designed to protect AI-driven customer experience agents from potential threats, ensuring they operate safely and effectively. Developed by experts from leading tech companies like Google, Meta, and Amazon, ZenGuard provides low-latency security guardrails that mitigate risks associated with large language model-based AI agents. Safeguards AI agents against prompt injection attacks by detecting and neutralizing manipulation attempts, ensuring secure LLM operation. Identifies and manages sensitive information to prevent data leaks and ensure compliance with privacy regulations. Enforces content policies by restricting AI agents from discussing prohibited subjects, maintaining brand integrity and user safety. The platform also provides a user-friendly interface for policy configuration, enabling real-time updates to security settings.
    Starting Price: $20 per month
  • 26
    Braintrust

    Braintrust

    Braintrust Data

    Braintrust is the enterprise-grade stack for building AI products. From evaluations, to prompt playground, to data management, we take uncertainty and tedium out of incorporating AI into your business. Compare multiple prompts, benchmarks, and respective input/output pairs between runs. Tinker ephemerally, or turn your draft into an experiment to evaluate over a large dataset. Leverage Braintrust in your continuous integration workflow so you can track progress on your main branch, and automatically compare new experiments to what’s live before you ship. Easily capture rated examples from staging & production, evaluate them, and incorporate them into “golden” datasets. Datasets reside in your cloud and are automatically versioned, so you can evolve them without the risk of breaking evaluations that depend on them.
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    UpTrain

    UpTrain

    UpTrain

    Get scores for factual accuracy, context retrieval quality, guideline adherence, tonality, and many more. You can’t improve what you can’t measure. UpTrain continuously monitors your application's performance on multiple evaluation criterions and alerts you in case of any regressions with automatic root cause analysis. UpTrain enables fast and robust experimentation across multiple prompts, model providers, and custom configurations, by calculating quantitative scores for direct comparison and optimal prompt selection. Hallucinations have plagued LLMs since their inception. By quantifying degree of hallucination and quality of retrieved context, UpTrain helps to detect responses with low factual accuracy and prevent them before serving to the end-users.
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    Literal AI

    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.
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    mcp-use

    mcp-use

    mcp-use

    mcp-use is an open source development platform offering SDKs, cloud infrastructure, and a developer-friendly control plane for building, managing, and deploying AI agents that leverage the Model Context Protocol (MCP). It enables connection to multiple MCP servers, each exposing specific tool capabilities like browsing, file operations, or specialized integrations, through a unified MCPClient. Developers can create custom agents (via MCPAgent) that dynamically select the most appropriate server for each task using configurable pipelines or a built-in server manager. It simplifies authentication, access control, audit logging, observability, sandboxed runtime environments, and deployment workflows, whether self-hosted or managed, making MCP development production-ready. With integrations for popular frameworks like LangChain (Python) and LangChain.js (TypeScript), mcp-use accelerates the creation of tool-enabled AI agents.
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    Convo

    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
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    Tumeryk

    Tumeryk

    Tumeryk

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

    Basalt

    Basalt

    Basalt is an AI-building platform that helps teams quickly create, test, and launch better AI features. With Basalt, you can prototype quickly using our no-code playground, allowing you to draft prompts with co-pilot guidance and structured sections. Iterate efficiently by saving and switching between versions and models, leveraging multi-model support and versioning. Improve your prompts with recommendations from our co-pilot. Evaluate and iterate by testing with realistic cases, upload your dataset, or let Basalt generate it for you. Run your prompt at scale on multiple test cases and build confidence with evaluators and expert evaluation sessions. Deploy seamlessly with the Basalt SDK, abstracting and deploying prompts in your codebase. Monitor by capturing logs and monitoring usage in production, and optimize by staying informed of new errors and edge cases.
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    Handit

    Handit

    Handit

    Handit.ai is an open source engine that continuously auto-improves your AI agents by monitoring every model, prompt, and decision in production, tagging failures in real time, and generating optimized prompts and datasets. It evaluates output quality using custom metrics, business KPIs, and LLM-as-judge grading, then automatically AB-tests each fix and presents versioned pull-request-style diffs for you to approve. With one-click deployment, instant rollback, and dashboards tying every merge to business impact, such as saved costs or user gains, Handit removes manual tuning and ensures continuous improvement on autopilot. Plugging into any environment, it delivers real-time monitoring, automatic evaluation, self-optimization through AB testing, and proof-of-effectiveness reporting. Teams have seen accuracy increases exceeding 60 %, relevance boosts over 35 %, and thousands of evaluations within days of integration.
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    Klu

    Klu

    Klu

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

    Flowise

    Flowise AI

    Flowise is an open-source, low-code platform that enables developers to create customized Large Language Model (LLM) applications through a user-friendly drag-and-drop interface. It supports integration with various LLMs, including LangChain and LlamaIndex, and offers over 100 integrations to facilitate the development of AI agents and orchestration flows. Flowise provides APIs, SDKs, and embedded widgets for seamless incorporation into existing systems, and is platform-agnostic, allowing deployment in air-gapped environments with local LLMs and vector databases.
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    PromptLayer

    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.
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    DeepEval

    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.
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    Parea

    Parea

    Parea

    The prompt engineering platform to experiment with different prompt versions, evaluate and compare prompts across a suite of tests, optimize prompts with one-click, share, and more. Optimize your AI development workflow. Key features to help you get and identify the best prompts for your production use cases. Side-by-side comparison of prompts across test cases with evaluation. CSV import test cases, and define custom evaluation metrics. Improve LLM results with automatic prompt and template optimization. View and manage all prompt versions and create OpenAI functions. Access all of your prompts programmatically, including observability and analytics. Determine the costs, latency, and efficacy of each prompt. Start enhancing your prompt engineering workflow with Parea today. Parea makes it easy for developers to improve the performance of their LLM apps through rigorous testing and version control.
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    DataLang

    DataLang

    DataLang

    Connect your data sources, configure some data views (i.e. SQL scripts), configure a GPT Wizard, create a custom GPT, and share it with your users, employees, or clients. Expose a specific set of data (using SQL) to train GPT, and then chat with it in natural language. Data insights just got a whole lot easier, you can follow simple steps and let DataLang do the heavy lifting. Configure your connection string and give it a name. Use SQL to train GPT with your own data rows, select the data sources to train GPT with, and leverage GPT to talk to your data in real time. Create custom GPT Assistants to chat with your data. Configure a GPT to share it with your users, or customers. Your connection string credentials are securely encrypted in our system and only decrypted when necessary for data operations. We are committed to the security and confidentiality of your information. You can ask DataLang almost any question you would ask a data analyst.
    Starting Price: $19 per month
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    DueDel

    DueDel

    DueDel

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

    OpenPipe

    OpenPipe

    OpenPipe provides fine-tuning for developers. Keep your datasets, models, and evaluations all in one place. Train new models with the click of a button. Automatically record LLM requests and responses. Create datasets from your captured data. Train multiple base models on the same dataset. We serve your model on our managed endpoints that scale to millions of requests. Write evaluations and compare model outputs side by side. Change a couple of lines of code, and you're good to go. Simply replace your Python or Javascript OpenAI SDK and add an OpenPipe API key. Make your data searchable with custom tags. Small specialized models cost much less to run than large multipurpose LLMs. Replace prompts with models in minutes, not weeks. Fine-tuned Mistral and Llama 2 models consistently outperform GPT-4-1106-Turbo, at a fraction of the cost. We're open-source, and so are many of the base models we use. Own your own weights when you fine-tune Mistral and Llama 2, and download them at any time.
    Starting Price: $1.20 per 1M tokens
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    Athina AI

    Athina AI

    Athina AI

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

    Multilith

    Multilith

    Multilith gives AI coding tools a persistent memory so they understand your entire codebase, architecture decisions, and team conventions from the very first prompt. With a single configuration line, Multilith injects organizational context into every AI interaction using the Model Context Protocol. This eliminates repetitive explanations and ensures AI suggestions align with your actual stack, patterns, and constraints. Architectural decisions, historical refactors, and documented tradeoffs become permanent guardrails rather than forgotten notes. Multilith helps teams onboard faster, reduce mistakes, and maintain consistent code quality across contributors. It works seamlessly with popular AI coding tools while keeping your data secure and fully under your control.
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    AgentKit

    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.
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    Llama Guard
    Llama Guard is an open-source safeguard model developed by Meta AI to enhance the safety of large language models in human-AI conversations. It functions as an input-output filter, classifying both prompts and responses into safety risk categories, including toxicity, hate speech, and hallucinations. Trained on a curated dataset, Llama Guard achieves performance on par with or exceeding existing moderation tools like OpenAI's Moderation API and ToxicChat. Its instruction-tuned architecture allows for customization, enabling developers to adapt its taxonomy and output formats to specific use cases. Llama Guard is part of Meta's broader "Purple Llama" initiative, which combines offensive and defensive security strategies to responsibly deploy generative AI models. The model weights are publicly available, encouraging further research and adaptation to meet evolving AI safety needs.
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    Oracle AI Agent Platform
    Oracle AI Agent Platform is a fully-managed service that enables the creation, deployment, and management of intelligent virtual agents powered by large language models and integrated AI technologies. Agents can be set up through a simple few-step process, and can orchestrate tools such as natural‐language-to‐SQL conversion, retrieval-augmented generation from enterprise knowledge bases, custom function or API calling, and even the ability to coordinate sub-agents. They support multi-turn conversational experiences with context retention across sessions, enabling agents to handle follow‐up questions and maintain personalised, consistent interactions. Built-in guardrails help enforce content moderation, prompt-injection prevention, and protection of PII (personally identifiable information), while optional human-in-the-loop workflows allow real-time supervision and escalation.
    Starting Price: $0.003 per 10,000 transactions
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    Guardrails AI

    Guardrails AI

    Guardrails AI

    With our dashboard, you are able to go deeper into analytics that will enable you to verify all the necessary information related to entering requests into Guardrails AI. Unlock efficiency with our ready-to-use library of pre-built validators. Optimize your workflow with robust validation for diverse use cases. Empower your projects with a dynamic framework for creating, managing, and reusing custom validators. Where versatility meets ease, catering to a spectrum of innovative applications easily. By verifying and indicating where the error is, you can quickly generate a second output option. Ensures that outcomes are in line with expectations, precision, correctness, and reliability in interactions with LLMs.
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    Langtail

    Langtail

    Langtail

    Langtail is a cloud-based application development tool designed to help companies debug, test, deploy, and monitor LLM-powered apps with ease. The platform offers a no-code playground for debugging prompts, fine-tuning model parameters, and running LLM tests to prevent issues when models or prompts change. Langtail specializes in LLM testing, including chatbot testing and ensuring robust AI LLM test prompts. With its comprehensive features, Langtail enables teams to: • Test LLM models thoroughly to catch potential issues before they affect production environments. • Deploy prompts as API endpoints for seamless integration. • Monitor model performance in production to ensure consistent outcomes. • Use advanced AI firewall capabilities to safeguard and control AI interactions. Langtail is the ideal solution for teams looking to ensure the quality, stability, and security of their LLM and AI-powered applications.
    Starting Price: $99/month/unlimited users
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    Prompt Mixer

    Prompt Mixer

    Prompt Mixer

    Use Prompt Mixer to create prompts and chains. Combinе your chains with datasets and improve with AI. Develop a comprehensive set of test scenarios to assess various prompt and model pairings, determining the optimal combination for diverse use cases. Incorporate Prompt Mixer into your everyday tasks, from creating content to conducting R&D. Prompt Mixer can streamline your workflow and boost productivity. Use Prompt Mixer to efficiently create, assess, and deploy content generation models for various applications such as blog posts and emails. Use Prompt Mixer to extract or merge data in a completely secure manner and easily monitor it after deployment.
    Starting Price: $29 per month
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    Laminar

    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