Alternatives to Prompt flow
Compare Prompt flow alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Prompt flow in 2026. Compare features, ratings, user reviews, pricing, and more from Prompt flow competitors and alternatives in order to make an informed decision for your business.
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Maxim
Maxim
Maxim is an agent simulation, evaluation, and observability platform that empowers modern AI teams to deploy agents with quality, reliability, and speed. Maxim's end-to-end evaluation and data management stack covers every stage of the AI lifecycle, from prompt engineering to pre & post release testing and observability, data-set creation & management, and fine-tuning. Use Maxim to simulate and test your multi-turn workflows on a wide variety of scenarios and across different user personas before taking your application to production. Features: Agent Simulation Agent Evaluation Prompt Playground Logging/Tracing Workflows Custom Evaluators- AI, Programmatic and Statistical Dataset Curation Human-in-the-loop Use Case: Simulate and test AI agents Evals for agentic workflows: pre and post-release Tracing and debugging multi-agent workflows Real-time alerts on performance and quality Creating robust datasets for evals and fine-tuning Human-in-the-loop workflowsStarting Price: $29/seat/month -
2
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.Starting Price: Free -
3
Respan
Respan
Respan is a self-driving observability and evaluation platform built specifically for AI agents. It enables teams to trace full execution flows, including messages, tool calls, routing decisions, memory usage, and outcomes. The platform connects observability, evaluations, and optimization into a continuous improvement loop. Metric-first evaluations allow teams to define performance standards such as accuracy, cost, reliability, and safety. Respan also includes capability and regression testing to protect stable behaviors while improving new ones. An AI-powered evaluation agent analyzes failures, identifies root causes, and recommends next steps automatically. With compliance certifications including ISO 27001, SOC 2, GDPR, and HIPAA, Respan supports secure, large-scale AI deployments across industries.Starting Price: $0/month -
4
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.Starting Price: $97 -
5
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. -
6
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. -
7
Teammately
Teammately
Teammately is an autonomous AI agent designed to revolutionize AI development by self-iterating AI products, models, and agents to meet your objectives beyond human capabilities. It employs a scientific approach, refining and selecting optimal combinations of prompts, foundation models, and knowledge chunking. To ensure reliability, Teammately synthesizes fair test datasets and constructs dynamic LLM-as-a-judge systems tailored to your project, quantifying AI capabilities and minimizing hallucinations. The platform aligns with your goals through Product Requirement Docs (PRD), enabling focused iteration towards desired outcomes. Key features include multi-step prompting, serverless vector search, and deep iteration processes that continuously refine AI until objectives are achieved. Teammately also emphasizes efficiency by identifying the smallest viable models, reducing costs, and enhancing performance.Starting Price: $25 per month -
8
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. -
9
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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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.Starting Price: Free -
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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. -
12
BenchLLM
BenchLLM
Use BenchLLM to evaluate your code on the fly. Build test suites for your models and generate quality reports. Choose between automated, interactive or custom evaluation strategies. We are a team of engineers who love building AI products. We don't want to compromise between the power and flexibility of AI and predictable results. We have built the open and flexible LLM evaluation tool that we have always wished we had. Run and evaluate models with simple and elegant CLI commands. Use the CLI as a testing tool for your CI/CD pipeline. Monitor models performance and detect regressions in production. Test your code on the fly. BenchLLM supports OpenAI, Langchain, and any other API out of the box. Use multiple evaluation strategies and visualize insightful reports. -
13
ChainForge
ChainForge
ChainForge is an open-source visual programming environment designed for prompt engineering and large language model evaluation. It enables users to assess the robustness of prompts and text-generation models beyond anecdotal evidence. Simultaneously test prompt ideas and variations across multiple LLMs to identify the most effective combinations. Evaluate response quality across different prompts, models, and settings to select the optimal configuration for specific use cases. Set up evaluation metrics and visualize results across prompts, parameters, models, and settings, facilitating data-driven decision-making. Manage multiple conversations simultaneously, template follow-up messages, and inspect outputs at each turn to refine interactions. ChainForge supports various model providers, including OpenAI, HuggingFace, Anthropic, Google PaLM2, Azure OpenAI endpoints, and locally hosted models like Alpaca and Llama. Users can adjust model settings and utilize visualization nodes. -
14
Opik
Comet
Confidently evaluate, test, and ship LLM applications with a suite of observability tools to calibrate language model outputs across your dev and production lifecycle. Log traces and spans, define and compute evaluation metrics, score LLM outputs, compare performance across app versions, and more. Record, sort, search, and understand each step your LLM app takes to generate a response. Manually annotate, view, and compare LLM responses in a user-friendly table. Log traces during development and in production. Run experiments with different prompts and evaluate against a test set. Choose and run pre-configured evaluation metrics or define your own with our convenient SDK library. Consult built-in LLM judges for complex issues like hallucination detection, factuality, and moderation. Establish reliable performance baselines with Opik's LLM unit tests, built on PyTest. Build comprehensive test suites to evaluate your entire LLM pipeline on every deployment.Starting Price: $39 per month -
15
Langfuse
Langfuse
Langfuse is an open source LLM engineering platform to help teams collaboratively debug, analyze and iterate on their LLM Applications. Observability: Instrument your app and start ingesting traces to Langfuse Langfuse UI: Inspect and debug complex logs and user sessions Prompts: Manage, version and deploy prompts from within Langfuse Analytics: Track metrics (LLM cost, latency, quality) and gain insights from dashboards & data exports Evals: Collect and calculate scores for your LLM completions Experiments: Track and test app behavior before deploying a new version Why Langfuse? - Open source - Model and framework agnostic - Built for production - Incrementally adoptable - start with a single LLM call or integration, then expand to full tracing of complex chains/agents - Use GET API to build downstream use cases and export dataStarting Price: $29/month -
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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.Starting Price: $0 -
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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. -
18
Traceloop
Traceloop
Traceloop is a comprehensive observability platform designed to monitor, debug, and test the quality of outputs from Large Language Models (LLMs). It offers real-time alerts for unexpected output quality changes, execution tracing for every request, and the ability to gradually roll out changes to models and prompts. Developers can debug and re-run issues from production directly in their Integrated Development Environment (IDE). Traceloop integrates seamlessly with the OpenLLMetry SDK, supporting multiple programming languages including Python, JavaScript/TypeScript, Go, and Ruby. The platform provides a range of semantic, syntactic, safety, and structural metrics to assess LLM outputs, such as QA relevancy, faithfulness, text quality, grammar correctness, redundancy detection, focus assessment, text length, word count, PII detection, secret detection, toxicity detection, regex validation, SQL validation, JSON schema validation, and code validation.Starting Price: $59 per month -
19
TruLens
TruLens
TruLens is an open-source Python library designed to systematically evaluate and track Large Language Model (LLM) applications. It provides fine-grained instrumentation, feedback functions, and a user interface to compare and iterate on app versions, facilitating rapid development and improvement of LLM-based applications. Programmatic tools that assess the quality of inputs, outputs, and intermediate results from LLM applications, enabling scalable evaluation. Fine-grained, stack-agnostic instrumentation and comprehensive evaluations help identify failure modes and systematically iterate to improve applications. An easy-to-use interface that allows developers to compare different versions of their applications, facilitating informed decision-making and optimization. TruLens supports various use cases, including question-answering, summarization, retrieval-augmented generation, and agent-based applications.Starting Price: Free -
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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.Starting Price: $0 -
21
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. -
22
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.Starting Price: Free -
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HyperFlow AI
HyperFlow AI
HyperFlow AI is a unified generative AI development platform that lets users design, build, test, scale, and deploy AI-powered applications and workflows with minimal coding by transforming domain expertise into powerful AI solutions via intuitive interfaces and visual tools; it supports prompt crafting for large language models and offers a no-code/low-code environment so teams can create custom AI apps and services quickly and iteratively. It emphasizes accessibility and democratizing AI creation, enabling users to develop advanced AI applications without traditional software engineering barriers while retaining control over their models and outputs. It provides a visual, drag-and-drop workflow design environment where users can configure and automate AI-driven processes, integrate data and external systems, and manage deployments from development through production. -
24
Vivgrid
Vivgrid
Vivgrid is a development platform for AI agents that emphasizes observability, debugging, safety, and global deployment infrastructure. It gives you full visibility into agent behavior, logging prompts, memory fetches, tool usage, and reasoning chains, letting developers trace where things break or deviate. You can test, evaluate, and enforce safety policies (like refusal rules or filters), and incorporate human-in-the-loop checks before going live. Vivgrid supports the orchestration of multi-agent systems with stateful memory, routing tasks dynamically across agent workflows. On the deployment side, it operates a globally distributed inference network to ensure low-latency (sub-50 ms) execution and exposes metrics like latency, cost, and usage in real time. It aims to simplify shipping resilient AI systems by combining debugging, evaluation, safety, and deployment into one stack, so you're not stitching together observability, infrastructure, and orchestration.Starting Price: $25 per month -
25
PromptLayer
PromptLayer
The first platform built for prompt engineers. Log OpenAI requests, search usage history, track performance, and visually manage prompt templates. manage Never forget that one good prompt. GPT in prod, done right. Trusted by over 1,000 engineers to version prompts and monitor API usage. Start using your prompts in production. To get started, create an account by clicking “log in” on PromptLayer. Once logged in, click the button to create an API key and save this in a secure location. After making your first few requests, you should be able to see them in the PromptLayer dashboard! You can use PromptLayer with LangChain. LangChain is a popular Python library aimed at assisting in the development of LLM applications. It provides a lot of helpful features like chains, agents, and memory. Right now, the primary way to access PromptLayer is through our Python wrapper library that can be installed with pip.Starting Price: Free -
26
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 -
27
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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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. -
29
DeepEval
Confident AI
DeepEval is a simple-to-use, open source LLM evaluation framework, for evaluating and testing large-language model systems. It is similar to Pytest but specialized for unit testing LLM outputs. DeepEval incorporates the latest research to evaluate LLM outputs based on metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., which uses LLMs and various other NLP models that run locally on your machine for evaluation. Whether your application is implemented via RAG or fine-tuning, LangChain, or LlamaIndex, DeepEval has you covered. With it, you can easily determine the optimal hyperparameters to improve your RAG pipeline, prevent prompt drifting, or even transition from OpenAI to hosting your own Llama2 with confidence. The framework supports synthetic dataset generation with advanced evolution techniques and integrates seamlessly with popular frameworks, allowing for efficient benchmarking and optimization of LLM systems.Starting Price: Free -
30
ZBrain
ZBrain
Import data in any format, including text or images from any source like documents, cloud or APIs and launch a ChatGPT-like interface based on your preferred large language model like GPT-4, FLAN and GPT-NeoX and answer user queries based on the imported data. A comprehensive list of sample questions across various departments in different industries that can be asked to an LLM connected to a company’s private data source through ZBrain. Seamless integration of ZBrain as a prompt-response service into your existing tools and products. Enhance your deployment experience with secure options like ZBrain Cloud or the flexibility to self-host on a private infrastructure. ZBrain Flow empowers you to create business logic without writing any code. The intuitive flow interface allows you to connect multiple large language models, prompt templates, and image and video models with extraction and parsing tools to build powerful and intelligent applications. -
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RagaAI
RagaAI
RagaAI is the #1 AI testing platform that helps enterprises mitigate AI risks and make their models secure and reliable. Reduce AI risk exposure across cloud or edge deployments and optimize MLOps costs with intelligent recommendations. A foundation model specifically designed to revolutionize AI testing. Easily identify the next steps to fix dataset and model issues. The AI-testing methods used by most today increase the time commitment and reduce productivity while building models. Also, they leave unforeseen risks, so they perform poorly post-deployment and thus waste both time and money for the business. We have built an end-to-end AI testing platform that helps enterprises drastically improve their AI development pipeline and prevent inefficiencies and risks post-deployment. 300+ tests to identify and fix every model, data, and operational issue, and accelerate AI development with comprehensive testing. -
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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 -
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MakerSuite
Google
MakerSuite is a tool that simplifies this workflow. With MakerSuite, you’ll be able to iterate on prompts, augment your dataset with synthetic data, and easily tune custom models. When you’re ready to move to code, MakerSuite will let you export your prompt as code in your favorite languages and frameworks, like Python and Node.js. -
34
promptfoo
promptfoo
Promptfoo discovers and eliminates major LLM risks before they are shipped to production. Its founders have experience launching and scaling AI to over 100 million users using automated red-teaming and testing to overcome security, legal, and compliance issues. Promptfoo's open source, developer-first approach has made it the most widely adopted tool in this space, with over 20,000 users. Custom probes for your application that identify failures you actually care about, not just generic jailbreaks and prompt injections. Move quickly with a command-line interface, live reloads, and caching. No SDKs, cloud dependencies, or logins. Used by teams serving millions of users and supported by an active open source community. Build reliable prompts, models, and RAGs with benchmarks specific to your use case. Secure your apps with automated red teaming and pentesting. Speed up evaluations with caching, concurrency, and live reloading.Starting Price: Free -
35
LMArena
LMArena
LMArena is a web-based platform that allows users to compare large language models through pair-wise anonymous match-ups: users input prompts, two unnamed models respond, and the crowd votes for the better answer; the identities are only revealed after voting, enabling transparent, large-scale evaluation of model quality. It aggregates these votes into leaderboards and rankings, enabling contributors of models to benchmark performance against peers and gain feedback from real-world usage. Its open framework supports many different models from academic labs and industry, fosters community engagement through direct model testing and peer comparison, and helps identify strengths and weaknesses of models in live interaction settings. It thereby moves beyond static benchmark datasets to capture dynamic user preferences and real-time comparisons, providing a mechanism for users and developers alike to observe which models deliver superior responses.Starting Price: Free -
36
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 -
37
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 -
38
Humanloop
Humanloop
Eye-balling a few examples isn't enough. Collect end-user feedback at scale to unlock actionable insights on how to improve your models. Easily A/B test models and prompts with the improvement engine built for GPT. Prompts only get your so far. Get higher quality results by fine-tuning on your best data – no coding or data science required. Integration in a single line of code. Experiment with Claude, ChatGPT and other language model providers without touching it again. You can build defensible and innovative products on top of powerful APIs – if you have the right tools to customize the models for your customers. Copy AI fine tune models on their best data, enabling cost savings and a competitive advantage. Enabling magical product experiences that delight over 2 million active users. -
39
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. -
40
Deepchecks
Deepchecks
Release high-quality LLM apps quickly without compromising on testing. Never be held back by the complex and subjective nature of LLM interactions. Generative AI produces subjective results. Knowing whether a generated text is good usually requires manual labor by a subject matter expert. If you’re working on an LLM app, you probably know that you can’t release it without addressing countless constraints and edge-cases. Hallucinations, incorrect answers, bias, deviation from policy, harmful content, and more need to be detected, explored, and mitigated before and after your app is live. Deepchecks’ solution enables you to automate the evaluation process, getting “estimated annotations” that you only override when you have to. Used by 1000+ companies, and integrated into 300+ open source projects, the core behind our LLM product is widely tested and robust. Validate machine learning models and data with minimal effort, in both the research and the production phases.Starting Price: $1,000 per month -
41
Verta
Verta
Get everything you need to start customizing LLMs and prompts immediately, no PhD required. Starter Kits with model, prompt, and dataset suggestions matched to your use case allow you to begin testing, evaluating, and refining model outputs right away. Experiment with multiple models (proprietary and open source), prompts, and techniques simultaneously to speed up the iteration process. Automated testing and evaluation and AI-powered prompt and refinement suggestions enable you to run many experiments at once to quickly achieve high-quality results. Verta’s easy-to-use platform empowers builders of all tech levels to achieve high-quality model outputs quickly. Using a human-in-the-loop approach to evaluation, Verta prioritizes human feedback at key points in the iteration cycle to capture expertise and develop IP to differentiate your GenAI products. Easily keep track of your best-performing options from Verta’s Leaderboard. -
42
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. -
43
HumanSignal
HumanSignal
HumanSignal's Label Studio Enterprise is a comprehensive platform designed for creating high-quality labeled data and evaluating model outputs with human supervision. It supports labeling and evaluating multi-modal data, image, video, audio, text, and time series, all in one place. It offers customizable labeling interfaces with pre-built templates and powerful plugins, allowing users to tailor the UI and workflows to specific use cases. Label Studio Enterprise integrates seamlessly with popular cloud storage providers and ML/AI models, facilitating pre-annotation, AI-assisted labeling, and prediction generation for model evaluation. The Prompts feature enables users to leverage LLMs to swiftly generate accurate predictions, enabling instant labeling of thousands of tasks. It supports various labeling use cases, including text classification, named entity recognition, sentiment analysis, summarization, and image captioning.Starting Price: $99 per month -
44
Gram
Speakeasy
Gram is an open source platform that enables developers to create, curate, and host Model Context Protocol (MCP) servers effortlessly, by transforming REST APIs (via OpenAPI specs) into AI-agent-ready tools without code changes. It guides users through a workflow: generating default tooling from API endpoints, scoping down to relevant tools, composing higher-order custom tools by chaining multiple calls, enriching tools with contextual prompts and metadata, and instantly testing within an interactive playground. With built-in support for OAuth 2.1 (including Dynamic Client Registration or user-authored flows), it ensures secure agent access. Once ready, these tools can be hosted as production-grade MCP servers, complete with centralized management, role-based access, audit logs, and compliance-ready infrastructure, including Cloudflare edge deployment and DXT-packaged installers for easy distribution.Starting Price: $250 per month -
45
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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Scale Evaluation
Scale
Scale Evaluation offers a comprehensive evaluation platform tailored for developers of large language models. This platform addresses current challenges in AI model assessment, such as the scarcity of high-quality, trustworthy evaluation datasets and the lack of consistent model comparisons. By providing proprietary evaluation sets across various domains and capabilities, Scale ensures accurate model assessments without overfitting. The platform features a user-friendly interface for analyzing and reporting model performance, enabling standardized evaluations for true apples-to-apples comparisons. Additionally, Scale's network of expert human raters delivers reliable evaluations, supported by transparent metrics and quality assurance mechanisms. The platform also offers targeted evaluations with custom sets focusing on specific model concerns, facilitating precise improvements through new training data. -
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Agenta
Agenta
Agenta is an open-source LLMOps platform designed to help teams build reliable AI applications with integrated prompt management, evaluation workflows, and system observability. It centralizes all prompts, experiments, traces, and evaluations into one structured hub, eliminating scattered workflows across Slack, spreadsheets, and emails. With Agenta, teams can iterate on prompts collaboratively, compare models side-by-side, and maintain full version history for every change. Its evaluation tools replace guesswork with automated testing, LLM-as-a-judge, human annotation, and intermediate-step analysis. Observability features allow developers to trace failures, annotate logs, convert traces into tests, and monitor performance regressions in real time. Agenta helps AI teams transition from siloed experimentation to a unified, efficient LLMOps workflow for shipping more reliable agents and AI products.Starting Price: Free -
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Shiplight
Shiplight
Shiplight brings autonomous AI agents to quality-assurance workflows, generating, running, and maintaining end-to-end tests so development teams can “ship fast and break nothing.” It enables full test coverage in just days, with no scripting required; test flows are auto-generated from product flows, documentation, support tickets, and more; parallel execution and smart caching deliver fast, reliable feedback; and visual editors and natural-language prompts mean non-coders (product managers, QA analysts) can create, review, and manage tests without writing scripts. The underlying agent “learns” the application’s behavior over time, visually navigating UI elements, clicking through flows, filling in forms, and adapting to UI changes, so that maintenance burdens and flaky tests are dramatically reduced. It fits into existing CI/CD pipelines, supports an agent-driven execution layer. -
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Autoblocks AI
Autoblocks AI
Autoblocks is an AI-powered platform designed to help teams in high-stakes industries like healthcare, finance, and legal to rapidly prototype, test, and deploy reliable AI models. The platform focuses on reducing risk by simulating thousands of real-world scenarios, ensuring AI agents behave predictably and reliably before being deployed. Autoblocks enables seamless collaboration between developers and subject matter experts (SMEs), automatically capturing feedback and integrating it into the development process to continuously improve models and ensure compliance with industry standards. -
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Revyl
Revyl
Mobile Testing is the process of evaluating mobile applications to ensure they function correctly, perform well, and provide a good user experience across different devices and operating systems. With Revyl, slash debugging time and boost quality. Our platform delivers unparalleled visibility into your entire stack, catching issues before they reach production. Our platform generates tests that replicate real user interactions, allowing you to catch issues before they reach production. Agentic Flows: Each test is an agentic flow that is resistant to UI changes. Flows can be run along the whole development lifecycle, from local to production. Connected Telemetry: Easily integrate our platform with your existing telemetry infrastructure to find the root cause of bugs Every test deserves a trace: By connecting agentic end-to-end tests with telemetry data, you'll always know the source of any issue, eliminating uncertainty in your debugging process.
