Alternatives to Braintrust

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

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    Google AI Studio
    Google AI Studio is a unified development platform that helps teams explore, build, and deploy applications using Google’s most advanced AI models, including Gemini 3. It brings text, image, audio, and video models together in one interactive playground. With vibe coding, developers can use natural language to quickly turn ideas into working AI applications. The platform reduces friction by generating functional apps that are ready for deployment with minimal setup. Built-in integrations like Google Search enhance real-world use cases. Google AI Studio also centralizes API key management, usage monitoring, and billing. It offers a fast, intuitive path from prompt to production powered by vibe coding workflows.
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  • 2
    Langfuse

    Langfuse

    Langfuse

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

    Maxim

    Maxim

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

    Adaline

    Adaline

    Iterate quickly and ship confidently. Confidently ship by evaluating your prompts with a suite of evals like context recall, llm-rubric (LLM as a judge), latency, and more. Let us handle intelligent caching and complex implementations to save you time and money. Quickly iterate on your prompts in a collaborative playground that supports all the major providers, variables, automatic versioning, and more. Easily build datasets from real data using Logs, upload your own as a CSV, or collaboratively build and edit within your Adaline workspace. Track usage, latency, and other metrics to monitor the health of your LLMs and the performance of your prompts using our APIs. Continuously evaluate your completions in production, see how your users are using your prompts, and create datasets by sending logs using our APIs. The single platform to iterate, evaluate, and monitor LLMs. Easily rollbacks if your performance regresses in production, and see how your team iterated the prompt.
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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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    Latitude

    Latitude

    Latitude

    Latitude is an open-source prompt engineering platform designed to help product teams build, evaluate, and deploy AI models efficiently. It allows users to import and manage prompts at scale, refine them with real or synthetic data, and track the performance of AI models using LLM-as-judge or human-in-the-loop evaluations. With powerful tools for dataset management and automatic logging, Latitude simplifies the process of fine-tuning models and improving AI performance, making it an essential platform for businesses focused on deploying high-quality AI applications.
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    Weavel

    Weavel

    Weavel

    Meet Ape, the first AI prompt engineer. Equipped with tracing, dataset curation, batch testing, and evals. Ape achieves an impressive 93% on the GSM8K benchmark, surpassing both DSPy (86%) and base LLMs (70%). Continuously optimize prompts using real-world data. Prevent performance regression with CI/CD integration. Human-in-the-loop with scoring and feedback. Ape works with the Weavel SDK to automatically log and add LLM generations to your dataset as you use your application. This enables seamless integration and continuous improvement specific to your use case. Ape auto-generates evaluation code and uses LLMs as impartial judges for complex tasks, streamlining your assessment process and ensuring accurate, nuanced performance metrics. Ape is reliable, as it works with your guidance and feedback. Feed in scores and tips to help Ape improve. Equipped with logging, testing, and evaluation for LLM applications.
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    Hamming

    Hamming

    Hamming

    Prompt optimization, automated voice testing, monitoring, and more. Test your AI voice agent against 1000s of simulated users in minutes. AI voice agents are hard to get right. A small change in prompts, function call definitions or model providers can cause large changes in LLM outputs. We're the only end-to-end platform that supports you from development to production. You can store, manage, version, and keep your prompts synced with voice infra providers from Hamming. This is 1000x more efficient than testing your voice agents by hand. Use our prompt playground to test LLM outputs on a dataset of inputs. Our LLM judges the quality of generated outputs. Save 80% of manual prompt engineering effort. Go beyond passive monitoring. We actively track and score how users are using your AI app in production and flag cases that need your attention using LLM judges. Easily convert calls and traces into test cases and add them to your golden dataset.
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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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    Vellum

    Vellum

    Vellum AI

    Bring LLM-powered features to production with tools for prompt engineering, semantic search, version control, quantitative testing, and performance monitoring. Compatible across all major LLM providers. Quickly develop an MVP by experimenting with different prompts, parameters, and even LLM providers to quickly arrive at the best configuration for your use case. Vellum acts as a low-latency, highly reliable proxy to LLM providers, allowing you to make version-controlled changes to your prompts – no code changes needed. Vellum collects model inputs, outputs, and user feedback. This data is used to build up valuable testing datasets that can be used to validate future changes before they go live. Dynamically include company-specific context in your prompts without managing your own semantic search infra.
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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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    Freeplay

    Freeplay

    Freeplay

    Freeplay gives product teams the power to prototype faster, test with confidence, and optimize features for customers, take control of how you build with LLMs. A better way to build with LLMs. Bridge the gap between domain experts & developers. Prompt engineering, testing & evaluation tools for your whole team.
  • 15
    Entry Point AI

    Entry Point AI

    Entry Point AI

    Entry Point AI is the modern AI optimization platform for proprietary and open source language models. Manage prompts, fine-tunes, and evals all in one place. When you reach the limits of prompt engineering, it’s time to fine-tune a model, and we make it easy. Fine-tuning is showing a model how to behave, not telling. It works together with prompt engineering and retrieval-augmented generation (RAG) to leverage the full potential of AI models. Fine-tuning can help you to get better quality from your prompts. Think of it like an upgrade to few-shot learning that bakes the examples into the model itself. For simpler tasks, you can train a lighter model to perform at or above the level of a higher-quality model, greatly reducing latency and cost. Train your model not to respond in certain ways to users, for safety, to protect your brand, and to get the formatting right. Cover edge cases and steer model behavior by adding examples to your dataset.
    Starting Price: $49 per month
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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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    PromptHub

    PromptHub

    PromptHub

    Test, collaborate, version, and deploy prompts, from a single place, with PromptHub. Put an end to continuous copy and pasting and utilize variables to simplify prompt creation. Say goodbye to spreadsheets, and easily compare outputs side-by-side when tweaking prompts. Bring your datasets and test prompts at scale with batch testing. Make sure your prompts are consistent by testing with different models, variables, and parameters. Stream two conversations and test different models, system messages, or chat templates. Commit prompts, create branches, and collaborate seamlessly. We detect prompt changes, so you can focus on outputs. Review changes as a team, approve new versions, and keep everyone on the same page. Easily monitor requests, costs, and latencies. PromptHub makes it easy to test, version, and collaborate on prompts with your team. Our GitHub-style versioning and collaboration makes it easy to iterate your prompts with your team, and store them in one place.
  • 18
    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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    Airtrain

    Airtrain

    Airtrain

    Query and compare a large selection of open-source and proprietary models at once. Replace costly APIs with cheap custom AI models. Customize foundational models on your private data to adapt them to your particular use case. Small fine-tuned models can perform on par with GPT-4 and are up to 90% cheaper. Airtrain’s LLM-assisted scoring simplifies model grading using your task descriptions. Serve your custom models from the Airtrain API in the cloud or within your secure infrastructure. Evaluate and compare open-source and proprietary models across your entire dataset with custom properties. Airtrain’s powerful AI evaluators let you score models along arbitrary properties for a fully customized evaluation. Find out what model generates outputs compliant with the JSON schema required by your agents and applications. Your dataset gets scored across models with standalone metrics such as length, compression, coverage.
  • 20
    Agenta

    Agenta

    Agenta

    Agenta is an open-source LLMOps platform designed to help teams build reliable AI applications with integrated prompt management, evaluation workflows, and system observability. It centralizes all prompts, experiments, traces, and evaluations into one structured hub, eliminating scattered workflows across Slack, spreadsheets, and emails. With Agenta, teams can iterate on prompts collaboratively, compare models side-by-side, and maintain full version history for every change. Its evaluation tools replace guesswork with automated testing, LLM-as-a-judge, human annotation, and intermediate-step analysis. Observability features allow developers to trace failures, annotate logs, convert traces into tests, and monitor performance regressions in real time. Agenta helps AI teams transition from siloed experimentation to a unified, efficient LLMOps workflow for shipping more reliable agents and AI products.
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    LastMile AI

    LastMile AI

    LastMile AI

    Prototype and productionize generative AI apps, built for engineers, not just ML practitioners. No more switching between platforms or wrestling with different APIs, focus on creating, not configuring. Use a familiar interface to prompt engineer and work with AI. Use parameters to easily streamline your workbooks into reusable templates. Create workflows by chaining model outputs from LLMs, image, and audio models. Create organizations to manage workbooks amongst your teammates. Share your workbook to the public or specific organizations you define with your team. Comment on workbooks and easily review and compare workbooks with your team. Develop templates for yourself, your team, or the broader developer community, get started quickly with templates to see what people are building.
    Starting Price: $50 per month
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    DagsHub

    DagsHub

    DagsHub

    DagsHub is a collaborative platform designed for data scientists and machine learning engineers to manage and streamline their projects. It integrates code, data, experiments, and models into a unified environment, facilitating efficient project management and team collaboration. Key features include dataset management, experiment tracking, model registry, and data and model lineage, all accessible through a user-friendly interface. DagsHub supports seamless integration with popular MLOps tools, allowing users to leverage their existing workflows. By providing a centralized hub for all project components, DagsHub enhances transparency, reproducibility, and efficiency in machine learning development. DagsHub is a platform for AI and ML developers that lets you manage and collaborate on your data, models, and experiments, alongside your code. DagsHub was particularly designed for unstructured data for example text, images, audio, medical imaging, and binary files.
    Starting Price: $9 per month
  • 23
    PromptPoint

    PromptPoint

    PromptPoint

    Turbocharge your team’s prompt engineering by ensuring high-quality LLM outputs with automatic testing and output evaluation. Make designing and organizing your prompts seamless, with the ability to template, save, and organize your prompt configurations. Run automated tests and get comprehensive results in seconds, helping you save time and elevate your efficiency. Structure your prompt configurations with precision, then instantly deploy them for use in your very own software applications. Design, test, and deploy prompts at the speed of thought. Unlock the power of your whole team, helping you bridge the gap between technical execution and real-world relevance. PromptPoint's natively no-code platform allows anyone and everyone in your team to write and test prompt configurations. Maintain flexibility in a many-model world by seamlessly connecting with hundreds of large language models.
    Starting Price: $20 per user per month
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    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.
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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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    Aim

    Aim

    AimStack

    Aim logs all your AI metadata (experiments, prompts, etc) enables a UI to compare & observe them and SDK to query them programmatically. Aim is an open-source, self-hosted AI Metadata tracking tool designed to handle 100,000s of tracked metadata sequences. Two most famous AI metadata applications are: experiment tracking and prompt engineering. Aim provides a performant and beautiful UI for exploring and comparing training runs, prompt sessions.
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    HoneyHive

    HoneyHive

    HoneyHive

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

    Promptmetheus

    Promptmetheus

    Compose, test, optimize, and deploy reliable prompts for the leading language models and AI platforms to supercharge your apps and workflows. Promptmetheus is an Integrated Development Environment (IDE) for LLM prompts, designed to help you automate workflows and augment products and services with the mighty capabilities of GPT and other cutting-edge AI models. With the advent of the transformer architecture, cutting-edge Language Models have reached parity with human capability in certain narrow cognitive tasks. But, to viably leverage their power, we have to ask the right questions. Promptmetheus provides a complete prompt engineering toolkit and adds composability, traceability, and analytics to the prompt design process to assist you in discovering those questions.
    Starting Price: $29 per month
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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
  • 30
    doteval

    doteval

    doteval

    doteval is an AI-assisted evaluation workspace that simplifies the creation of high-signal evaluations, alignment of LLM judges, and definition of rewards for reinforcement learning, all within a single platform. It offers a Cursor-like experience to edit evaluations-as-code against a YAML schema, enabling users to version evaluations across checkpoints, replace manual effort with AI-generated diffs, and compare evaluation runs on tight execution loops to align them with proprietary data. doteval supports the specification of fine-grained rubrics and aligned graders, facilitating rapid iteration and high-quality evaluation datasets. Users can confidently determine model upgrades or prompt improvements and export specifications for reinforcement learning training. It is designed to accelerate the evaluation and reward creation process by 10 to 100 times, making it a valuable tool for frontier AI teams benchmarking complex model tasks.
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    Pezzo

    Pezzo

    Pezzo

    Pezzo is the open-source LLMOps platform built for developers and teams. In just two lines of code, you can seamlessly troubleshoot and monitor your AI operations, collaborate and manage your prompts in one place, and instantly deploy changes to any environment.
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    LangWatch

    LangWatch

    LangWatch

    Guardrails are crucial in AI maintenance, LangWatch safeguards you and your business from exposing sensitive data, prompt injection and keeps your AI from going off the rails, avoiding unforeseen damage to your brand. Understanding the behaviour of both AI and users can be challenging for businesses with integrated AI. Ensure accurate and appropriate responses by constantly maintaining quality through oversight. LangWatch’s safety checks and guardrails prevent common AI issues including jailbreaking, exposing sensitive data, and off-topic conversations. Track conversion rates, output quality, user feedback and knowledge base gaps with real-time metrics — gain constant insights for continuous improvement. Powerful data evaluation allows you to evaluate new models and prompts, develop datasets for testing and run experimental simulations on tailored builds.
    Starting Price: €99 per month
  • 33
    Confident AI

    Confident AI

    Confident AI

    Confident AI offers an open-source package called DeepEval that enables engineers to evaluate or "unit test" their LLM applications' outputs. Confident AI is our commercial offering and it allows you to log and share evaluation results within your org, centralize your datasets used for evaluation, debug unsatisfactory evaluation results, and run evaluations in production throughout the lifetime of your LLM application. We offer 10+ default metrics for engineers to plug and use.
    Starting Price: $39/month
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    Narrow AI

    Narrow AI

    Narrow AI

    Introducing Narrow AI: Take the Engineer out of Prompt Engineering Narrow AI autonomously writes, monitors, and optimizes prompts for any model - so you can ship AI features 10x faster at a fraction of the cost. Maximize quality while minimizing costs - Reduce AI spend by 95% with cheaper models - Improve accuracy through Automated Prompt Optimization - Achieve faster responses with lower latency models Test new models in minutes, not weeks - Easily compare prompt performance across LLMs - Get cost and latency benchmarks for each model - Deploy on the optimal model for your use case Ship LLM features 10x faster - Automatically generate expert-level prompts - Adapt prompts to new models as they are released - Optimize prompts for quality, cost and speed
    Starting Price: $500/month/team
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    Microsoft Foundry Models
    Microsoft Foundry Models is a unified model catalog that gives enterprises access to more than 11,000 AI models from Microsoft, OpenAI, Anthropic, Mistral AI, Meta, Cohere, DeepSeek, xAI, and others. It allows teams to explore, test, and deploy models quickly using a task-centric discovery experience and integrated playground. Organizations can fine-tune models with ready-to-use pipelines and evaluate performance using their own datasets for more accurate benchmarking. Foundry Models provides secure, scalable deployment options with serverless and managed compute choices tailored to enterprise needs. With built-in governance, compliance, and Azure’s global security framework, businesses can safely operationalize AI across mission-critical workflows. The platform accelerates innovation by enabling developers to build, iterate, and scale AI solutions from one centralized environment.
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    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.
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    Portkey

    Portkey

    Portkey.ai

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

    Prompteams

    Prompteams

    Develop and version control your prompts. Auto-generated API to retrieve prompts. Automatically run end-to-end LLM testing before making updates to your prompts on production. Let your industry specialists and engineers collaborate on the same platform. Let your industry specialists and prompt engineers test and iterate on the same platform without any programming knowledge. With our testing suite, you can create and run unlimited test cases to ensure the quality of your your your your your prompt. Check for hallucinations, issues, edge cases, and more. Our suite is the most complex of prompts. Use Git-like features to manage your prompts. Create a repository for each project, and create multiple branches to iterate on your prompts. Commit your changes and test them in a separate environment. Easily revert back to a previous version. With our real-time APIs, one single click, and your prompt is updated and live.
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    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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    PromptGround

    PromptGround

    PromptGround

    Simplify prompt edits, version control, and SDK integration in one place. No more scattered tools or waiting on deployments for changes. Explore features crafted to streamline your workflow and elevate prompt engineering. Manage your prompts and projects in a structured way, with tools designed to keep everything organized and accessible. Dynamically adapt your prompts to fit the context of your application, enhancing user experience with tailored interactions. Seamlessly incorporate prompt management into your current development environment with our user-friendly SDK, designed for minimal disruption and maximum efficiency. Leverage detailed analytics to understand prompt performance, user engagement, and areas for improvement, informed by concrete data. Invite team members to collaborate in a shared environment, where everyone can contribute, review, and refine prompts together. Control access and permissions within your team, ensuring members can work effectively.
    Starting Price: $4.99 per month
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    Athina AI

    Athina AI

    Athina AI

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

    Lisapet.ai

    Lisapet.ai

    Lisapet.ai is an advanced AI prompt testing platform that accelerates the development of AI features. Built by a team managing a AI-powered SaaS platform with over 15M users, it automates prompt testing, reducing manual effort and ensuring reliable results. Key features include a versatile AI Playground, parameterized prompts, structured outputs, and side-by-side editing. Collaborate seamlessly with automated test suites, detailed reports, and real-time analytics to optimize performance and cut costs. Ship AI features faster and with greater confidence using Lisapet.ai.
    Starting Price: $9/month
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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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    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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    Oumi

    Oumi

    Oumi

    Oumi is a fully open source platform that streamlines the entire lifecycle of foundation models, from data preparation and training to evaluation and deployment. It supports training and fine-tuning models ranging from 10 million to 405 billion parameters using state-of-the-art techniques such as SFT, LoRA, QLoRA, and DPO. The platform accommodates both text and multimodal models, including architectures like Llama, DeepSeek, Qwen, and Phi. Oumi offers tools for data synthesis and curation, enabling users to generate and manage training datasets effectively. For deployment, it integrates with popular inference engines like vLLM and SGLang, ensuring efficient model serving. The platform also provides comprehensive evaluation capabilities across standard benchmarks to assess model performance. Designed for flexibility, Oumi can run on various environments, from local laptops to cloud infrastructures such as AWS, Azure, GCP, and Lambda.
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    Azure Open Datasets
    Improve the accuracy of your machine learning models with publicly available datasets. Save time on data discovery and preparation by using curated datasets that are ready to use in machine learning workflows and easy to access from Azure services. Account for real-world factors that can impact business outcomes. By incorporating features from curated datasets into your machine learning models, improve the accuracy of predictions and reduce data preparation time. Share datasets with a growing community of data scientists and developers. Deliver insights at hyperscale using Azure Open Datasets with Azure’s machine learning and data analytics solutions. There's no additional charge for using most Open Datasets. Pay only for Azure services consumed while using Open Datasets, such as virtual machine instances, storage, networking resources, and machine learning. Curated open data made easily accessible on Azure.
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    Metatext

    Metatext

    Metatext

    Build, evaluate, deploy, and refine custom natural language processing models. Empower your team to automate workflows without hiring an AI expert team and costly infra. Metatext simplifies the process of creating customized AI/NLP models, even without expertise in ML, data science, or MLOps. With just a few steps, automate complex workflows, and rely on intuitive UI and APIs to handle the heavy work. Enable AI into your team using a simple but intuitive UI, add your domain expertise, and let our APIs do all the heavy work. Get your custom AI trained and deployed automatically. Get the best from a set of deep learning algorithms. Test it using a Playground. Integrate our APIs with your existing systems, Google Spreadsheets, and other tools. Select the AI engine that best suits your use case. Each one offers a set of tools to assist creating datasets and fine-tuning models. Upload text data in various file formats and annotate labels using our built-in AI-assisted data labeling tool.
    Starting Price: $35 per month
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    PromptIDE
    The xAI PromptIDE is an integrated development environment for prompt engineering and interpretability research. It accelerates prompt engineering through an SDK that allows implementing complex prompting techniques and rich analytics that visualize the network's outputs. We use it heavily in our continuous development of Grok. We developed the PromptIDE to give transparent access to Grok-1, the model that powers Grok, to engineers and researchers in the community. The IDE is designed to empower users and help them explore the capabilities of our large language models (LLMs) at pace. At the heart of the IDE is a Python code editor that - combined with a new SDK - allows implementing complex prompting techniques. While executing prompts in the IDE, users see helpful analytics such as the precise tokenization, sampling probabilities, alternative tokens, and aggregated attention masks. The IDE also offers quality of life features. It automatically saves all prompts.
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    GradientJ

    GradientJ

    GradientJ

    GradientJ provides everything you need to build large language model applications in minutes and manage them forever. Discover and maintain the best prompts by saving versions and comparing them across benchmark examples. Orchestrate and manage complex applications by chaining prompts and knowledge bases into complex APIs. Enhance the accuracy of your models by integrating them with your proprietary data.
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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.