Alternatives to Teammately
Compare Teammately alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Teammately in 2026. Compare features, ratings, user reviews, pricing, and more from Teammately competitors and alternatives in order to make an informed decision for your business.
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Gemini Enterprise Agent Platform is a comprehensive solution from Google Cloud designed to help organizations build, scale, govern, and optimize AI agents. It represents the evolution of Vertex AI, combining advanced model development with new capabilities for agent orchestration and integration. The platform provides access to over 200 leading AI models, including Google’s Gemini series and third-party options like Anthropic’s Claude. It enables teams to create intelligent agents using both low-code and code-first development environments. With features like Agent Runtime and Memory Bank, businesses can deploy long-running agents that retain context and perform complex workflows. The platform emphasizes security and governance through tools like Agent Identity, Agent Registry, and Agent Gateway. It also includes optimization tools such as simulation, evaluation, and observability to ensure consistent agent performance.
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2
LM-Kit.NET
LM-Kit
LM-Kit.NET is a complete local AI runtime for .NET that lets engineering teams ship AI-powered features without cloud dependencies, per-token costs, or data leaving the network. Most .NET AI integrations stop at inference. LM-Kit.NET covers the full range of capabilities production applications actually need: agentic workflows with tool calling, planning, and memory; document intelligence with OCR and structured extraction; retrieval-augmented generation with built-in vector storage; multilingual speech-to-text; vision and multimodal understanding; text analysis with classification, NER, PII extraction, and sentiment; and text generation with translation, summarization, and constrained output. Ships in one NuGet package, runs in-process with no sidecar services, and works across all major hardware acceleration backends. Drop-in replacement for Semantic Kernel through its Microsoft.Extensions.AI compatibility layer. -
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Orq.ai
Orq.ai
Orq.ai is the #1 platform for software teams to operate agentic AI systems at scale. Optimize prompts, deploy use cases, and monitor performance, no blind spots, no vibe checks. Experiment with prompts and LLM configurations before moving to production. Evaluate agentic AI systems in offline environments. Roll out GenAI features to specific user groups with guardrails, data privacy safeguards, and advanced RAG pipelines. Visualize all events triggered by agents for fast debugging. Get granular control on cost, latency, and performance. Connect to your favorite AI models, or bring your own. Speed up your workflow with out-of-the-box components built for agentic AI systems. Manage core stages of the LLM app lifecycle in one central platform. Self-hosted or hybrid deployment with SOC 2 and GDPR compliance for enterprise security. -
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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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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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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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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 -
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Braintrust
Braintrust Data
Braintrust is an AI observability and evaluation platform designed to help teams build, monitor, and improve AI systems in production. It enables users to capture and inspect real-time traces of AI interactions, including prompts, responses, and tool usage. The platform allows teams to measure performance using automated and human evaluations to ensure output quality. Braintrust helps identify issues such as hallucinations, regressions, and performance drops before they impact users. It supports prompt and model comparisons, making it easier to optimize AI workflows over time. With scalable trace ingestion and real-time monitoring, teams gain full visibility into how their AI systems behave. The platform integrates with multiple programming languages and tools, allowing developers to work within their existing tech stack. Overall, Braintrust provides a comprehensive solution for maintaining and improving AI quality at scale. -
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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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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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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 -
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Dify
Dify
Dify is an open-source platform designed to streamline the development and operation of generative AI applications. It offers a comprehensive suite of tools, including an intuitive orchestration studio for visual workflow design, a Prompt IDE for prompt testing and refinement, and enterprise-level LLMOps capabilities for monitoring and optimizing large language models. Dify supports integration with various LLMs, such as OpenAI's GPT series and open-source models like Llama, providing flexibility for developers to select models that best fit their needs. Additionally, its Backend-as-a-Service (BaaS) features enable seamless incorporation of AI functionalities into existing enterprise systems, facilitating the creation of AI-powered chatbots, document summarization tools, and virtual assistants. -
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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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OpenPipe
OpenPipe
OpenPipe provides fine-tuning for developers. Keep your datasets, models, and evaluations all in one place. Train new models with the click of a button. Automatically record LLM requests and responses. Create datasets from your captured data. Train multiple base models on the same dataset. We serve your model on our managed endpoints that scale to millions of requests. Write evaluations and compare model outputs side by side. Change a couple of lines of code, and you're good to go. Simply replace your Python or Javascript OpenAI SDK and add an OpenPipe API key. Make your data searchable with custom tags. Small specialized models cost much less to run than large multipurpose LLMs. Replace prompts with models in minutes, not weeks. Fine-tuned Mistral and Llama 2 models consistently outperform GPT-4-1106-Turbo, at a fraction of the cost. We're open-source, and so are many of the base models we use. Own your own weights when you fine-tune Mistral and Llama 2, and download them at any time.Starting Price: $1.20 per 1M tokens -
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Athina AI
Athina AI
Athina 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 -
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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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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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DSPy
Stanford NLP
DSPy is the framework for programming—rather than prompting—language models. It allows you to iterate fast on building modular AI systems and offers algorithms for optimizing their prompts and weights, whether you're building simple classifiers, sophisticated RAG pipelines, or Agent loops.Starting Price: Free -
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Lamatic.ai
Lamatic.ai
A managed PaaS with a low-code visual builder, VectorDB, and integrations to apps and models for building, testing, and deploying high-performance AI apps on edge. Eliminate costly, error-prone work. Drag and drop models, apps, data, and agents to find what works best. Deploy in under 60 seconds and cut latency in half. Observe, test, and iterate seamlessly. Visibility and tools ensure accuracy and reliability. Make data-driven decisions with request, LLM, and usage reports. See real-time traces by node. Experiments make it easy to optimize everything always embeddings, prompts, models, and more. Everything you need to launch & iterate at scale. Community of bright-minded builders sharing insights, experience & feedback. Distilling the best tips, tricks & techniques for AI application development. An elegant platform to build agentic systems like a team of 100. An intuitive and simple frontend to collaborate and manage AI applications seamlessly.Starting Price: $100 per month -
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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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LayerLens
LayerLens
LayerLens is an independent AI model evaluation platform for understanding how models perform through verified results across benchmarks, prompt-level results, agentic benchmarks, and audit-ready comparisons across vendors. It helps teams compare more than 200 AI models side by side, with transparent benchmarks, model comparison tools, and consistent evaluation methods for accuracy, latency, behavior, and real-world applicability. LayerLens is built for deep model analysis through Spaces, where teams can group benchmarks and evaluations, explore task strengths, and track performance patterns in context. It supports continuous evaluation by running ongoing evals across model versions, prompt changes, judge updates, and live traces, helping teams detect quality regressions, drift, silent failures, contamination, and policy issues before they affect production. -
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LLM Council
LLM Council
LLM Council is a lightweight multi-model orchestration tool that enables users to query several large language models simultaneously and synthesize their outputs into a single, higher-confidence response. Instead of relying on one AI system, it routes a prompt to a panel of models, each of which produces an independent answer before anonymously reviewing and ranking the others’ work. A designated “Chairman” model then combines the strongest insights into a unified final output, mimicking the dynamics of a panel of experts reaching consensus. It typically runs as a simple local web interface with a Python backend and React frontend and connects through aggregation services to access models from providers such as OpenAI, Google, and Anthropic. This structured peer-review workflow is designed to surface blind spots, reduce hallucinations, and improve answer reliability by introducing multiple perspectives and cross-model critique.Starting Price: $25 per month -
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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 -
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IBM watsonx.ai
IBM
Now available—a next generation enterprise studio for AI builders to train, validate, tune and deploy AI models IBM® watsonx.ai™ AI studio is part of the IBM watsonx™ AI and data platform, bringing together new generative AI (gen AI) capabilities powered by foundation models and traditional machine learning (ML) into a powerful studio spanning the AI lifecycle. Tune and guide models with your enterprise data to meet your needs with easy-to-use tools for building and refining performant prompts. With watsonx.ai, you can build AI applications in a fraction of the time and with a fraction of the data. Watsonx.ai offers: End-to-end AI governance: Enterprises can scale and accelerate the impact of AI with trusted data across the business, using data wherever it resides. Hybrid, multi-cloud deployments: IBM provides the flexibility to integrate and deploy your AI workloads into your hybrid-cloud stack of choice. -
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NVIDIA Agent Toolkit
NVIDIA
NVIDIA Agent Toolkit is a solution stack designed to build, deploy, and scale autonomous AI agents that can reason, plan, and execute complex tasks across enterprise systems. Unlike traditional generative AI, which responds to single prompts, agentic AI uses sophisticated reasoning and iterative planning to solve multi-step problems independently, enabling systems to analyze data, develop strategies, and complete workflows without continuous human input. It integrates multiple components of the NVIDIA AI ecosystem, including pretrained models, microservices, and development frameworks, allowing organizations to create context-aware AI agents that operate using their own data. These agents can ingest large volumes of structured and unstructured data from enterprise systems, interpret context, and coordinate actions across applications to automate processes such as customer service, software development, analytics, and operational workflows. -
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AgentBench
AgentBench
AgentBench is an evaluation framework specifically designed to assess the capabilities and performance of autonomous AI agents. It provides a standardized set of benchmarks that test various aspects of an agent's behavior, such as task-solving ability, decision-making, adaptability, and interaction with simulated environments. By evaluating agents on tasks across different domains, AgentBench helps developers identify strengths and weaknesses in the agents’ performance, such as their ability to plan, reason, and learn from feedback. The framework offers insights into how well an agent can handle complex, real-world-like scenarios, making it useful for both research and practical development. Overall, AgentBench supports the iterative improvement of autonomous agents, ensuring they meet reliability and efficiency standards before wider application. -
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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 -
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Respan
Respan
Respan is a self-driving observability and evaluation platform built specifically for AI agents. It enables teams to trace full execution flows, including messages, tool calls, routing decisions, memory usage, and outcomes. The platform connects observability, evaluations, and optimization into a continuous improvement loop. Metric-first evaluations allow teams to define performance standards such as accuracy, cost, reliability, and safety. Respan also includes capability and regression testing to protect stable behaviors while improving new ones. An AI-powered evaluation agent analyzes failures, identifies root causes, and recommends next steps automatically. With compliance certifications including ISO 27001, SOC 2, GDPR, and HIPAA, Respan supports secure, large-scale AI deployments across industries.Starting Price: $0/month -
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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 -
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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. -
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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 -
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Graviti
Graviti
Unstructured data is the future of AI. Unlock this future now and build an ML/AI pipeline that scales all of your unstructured data in one place. Use better data to deliver better models, only with Graviti. Get to know the data platform that enables AI developers with management, query, and version control features that are designed for unstructured data. Quality data is no longer a pricey dream. Manage your metadata, annotation, and predictions in one place. Customize filters and visualize filtering results to get you straight to the data that best match your needs. Utilize a Git-like structure to manage data versions and collaborate with your teammates. Role-based access control and visualization of version differences allows your team to work together safely and flexibly. Automate your data pipeline with Graviti’s built-in marketplace and workflow builder. Level-up to fast model iterations with no more grinding. -
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Amazon Bedrock
Amazon
Amazon Bedrock is a fully managed service that simplifies building and scaling generative AI applications by providing access to a variety of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself. Through a single API, developers can experiment with these models, customize them using techniques like fine-tuning and Retrieval Augmented Generation (RAG), and create agents that interact with enterprise systems and data sources. As a serverless platform, Amazon Bedrock eliminates the need for infrastructure management, allowing seamless integration of generative AI capabilities into applications with a focus on security, privacy, and responsible AI practices. -
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Wordware
Wordware
Wordware enables anyone to develop, iterate, and deploy useful AI agents. Wordware combines the best aspects of software with the power of natural language. Remove constraints of traditional no-code tools and empower every team member to iterate independently. Natural language programming is here to stay. Wordware frees prompt from your codebase by providing both technical and non-technical users with a powerful IDE for AI agent creation. Experience the simplicity and flexibility of our interface. Empower your team to easily collaborate, manage prompts, and streamline workflows with an intuitive design. Loops, branching, structured generation, version control, and type safety help you get the most out of LLMs, while custom code execution allows you to connect to virtually any API. Easily switch between various large language model providers with one click. Optimize your workflows with the best cost-to-latency-to-quality ratios for your application.Starting Price: $69 per month -
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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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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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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 -
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Vertesia
Vertesia
Vertesia is a unified, low-code generative AI platform that enables enterprise teams to rapidly build, deploy, and operate GenAI applications and agents at scale. Designed for both business professionals and IT specialists, Vertesia offers a frictionless development experience, allowing users to go from prototype to production without extensive timelines or heavy infrastructure. It supports multiple generative AI models from leading inference providers, providing flexibility and preventing vendor lock-in. Vertesia's agentic retrieval-augmented generation (RAG) pipeline enhances generative AI accuracy and performance by automating and accelerating content preparation, including intelligent document processing and semantic chunking. With enterprise-grade security, SOC2 compliance, and support for leading cloud infrastructures like AWS, GCP, and Azure, Vertesia ensures secure and scalable deployments. -
39
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. -
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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. -
41
PromptDrive
PromptDrive
PromptDrive helps teams adopt and use AI by bringing all your prompts, chats, and teammates into one workspace. Create prompts quickly with our web app. Link to a platform, select a folder, and add notes for context. You can even leave comments to help your team use and iterate on prompts. Run and collaborate on ChatGPT, Claude, and Gemini without ever leaving PromptDrive. Just add your API keys, choose your model, and start prompting. Iterate as you go to get the response you want. Organize your prompts however you want. Our prompt management tool has built-in search so you can find, copy, and execute prompts with a few clicks. Add variables to speed up your workflow for those repetitive prompts. We make it easy to share your prompts. Each folder and prompt has a unique URL that allows you to share your work with anyone publicly and privately. Use our extension to quickly find and use the prompts you need when you need them.Starting Price: $10 per month -
42
Dynamiq
Dynamiq
Dynamiq is a platform built for engineers and data scientists to build, deploy, test, monitor and fine-tune Large Language Models for any use case the enterprise wants to tackle. Key features: 🛠️ Workflows: Build GenAI workflows in a low-code interface to automate tasks at scale 🧠 Knowledge & RAG: Create custom RAG knowledge bases and deploy vector DBs in minutes 🤖 Agents Ops: Create custom LLM agents to solve complex task and connect them to your internal APIs 📈 Observability: Log all interactions, use large-scale LLM quality evaluations 🦺 Guardrails: Precise and reliable LLM outputs with pre-built validators, detection of sensitive content, and data leak prevention 📻 Fine-tuning: Fine-tune proprietary LLM models to make them your ownStarting Price: $125/month -
43
Asteroid AI
Asteroid AI
Asteroid is an AI-driven browser-automation platform that lets both non-technical users and engineers build, deploy, monitor, and refine complex web workflows without writing traditional code. Its core is a graph-based agent builder where you describe desired tasks in natural language and configure repeatable logic with variables and structured outputs. Behind the scenes, Asteroid combines encrypted credential management, selector-based guardrails powered by Playwright, and live browser control to navigate pages, interact with UI elements, and call external APIs as needed. You can instantly deploy agents via a RESTful API, embed them into existing systems, or iterate in the platform’s console with real-time supervision, debugging tools, and human-in-the-loop checkpoints. Use cases range from multi-step data retrieval (insurance quotes, grant applications) and intelligent data entry into legacy systems (patient records, supplier portals) to automated reporting.Starting Price: $30 per month -
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LlamaIndex
LlamaIndex
LlamaIndex is a “data framework” to help you build LLM apps. Connect semi-structured data from API's like Slack, Salesforce, Notion, etc. LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models. LlamaIndex provides the key tools to augment your LLM applications with data. Connect your existing data sources and data formats (API's, PDF's, documents, SQL, etc.) to use with a large language model application. Store and index your data for different use cases. Integrate with downstream vector store and database providers. LlamaIndex provides a query interface that accepts any input prompt over your data and returns a knowledge-augmented response. Connect unstructured sources such as documents, raw text files, PDF's, videos, images, etc. Easily integrate structured data sources from Excel, SQL, etc. Provides ways to structure your data (indices, graphs) so that this data can be easily used with LLMs. -
45
Flowise
Flowise AI
Flowise is an open-source platform that enables developers and teams to build AI agents and LLM-powered applications through a visual interface. The platform provides modular building blocks that allow users to create everything from simple chatbot workflows to complex multi-agent systems. With its drag-and-drop design environment, developers can rapidly prototype and deploy AI-powered applications without extensive coding. Flowise supports integrations with more than 100 large language models, embeddings, and vector databases. It also includes features such as human-in-the-loop workflows, observability tools, and execution tracing for monitoring agent behavior. Developers can extend applications through APIs, SDKs, and embedded chat interfaces using TypeScript or Python. By combining visual development tools with scalable infrastructure, Flowise simplifies the process of building and deploying production-ready AI agents.Starting Price: Free -
46
Weights & Biases
Weights & Biases
Experiment tracking, hyperparameter optimization, model and dataset versioning with Weights & Biases (WandB). Track, compare, and visualize ML experiments with 5 lines of code. Add a few lines to your script, and each time you train a new version of your model, you'll see a new experiment stream live to your dashboard. Optimize models with our massively scalable hyperparameter search tool. Sweeps are lightweight, fast to set up, and plug in to your existing infrastructure for running models. Save every detail of your end-to-end machine learning pipeline — data preparation, data versioning, training, and evaluation. It's never been easier to share project updates. Quickly and easily implement experiment logging by adding just a few lines to your script and start logging results. Our lightweight integration works with any Python script. W&B Weave is here to help developers build and iterate on their AI applications with confidence. -
47
Claude Agent SDK
Claude
The Claude Agent SDK is a developer toolkit that enables the creation of autonomous AI agents powered by Claude, allowing them to perform real-world tasks beyond simple text generation by interacting directly with files, systems, and tools. It provides the same underlying infrastructure used by Claude Code, including an agent loop, context management, and built-in tool execution, and is available for use in Python and TypeScript. With this SDK, developers can build agents that read and write files, execute shell commands, search the web, edit code, and automate complex workflows without needing to implement these capabilities from scratch. It maintains persistent context and state across interactions, enabling agents to operate continuously, reason through multi-step problems, take actions, verify results, and iterate until tasks are completed.Starting Price: Free -
48
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 -
49
PromptQL
Hasura
PromptQL is an enterprise-grade AI platform that builds reasoning models with near-perfect accuracy, tailored to each organization’s unique context. Unlike generic AI tools, PromptQL learns your business rules, tacit knowledge, and internal language to act like a trusted analyst or engineer. It empowers companies to deploy specialized AI that not only delivers correct answers but also signals confidence levels and learns continuously from feedback. Within 14 days, enterprises can go from setup to real-world rollout, unlocking measurable results faster than traditional AI deployments. Used by Fortune 100 companies and global enterprises, PromptQL consistently outperforms warehouse-native AI solutions in accuracy and reliability. Designed for adoption, not obsolescence, PromptQL enables organizations to build AI that truly understands their business. -
50
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.
