HoneyHive Alternatives

Collaborative LLMOps environment for testing, evaluating, and deploying GenAI applications, with features for observability, dataset management, and prompt optimization.
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Humanloop

If you're looking for a replacement for HoneyHive, Humanloop is another option. The platform is geared for managing and optimizing Large Language Model (LLM) development, a process plagued by workflow inefficiencies and bad collaboration. It's a sandbox for developers, product managers and domain experts to develop and iterate on AI features, along with a suite of tools for debugging and monitoring AI performance. It integrates with common LLM suppliers and comes with Python and TypeScript SDKs for easy integration, so it should be adaptable to a wide range of AI development needs.

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Parea

Another option is Parea, an experimentation and human annotation platform geared for AI teams. Parea has powerful tools to track experiments, monitor model performance and gather human feedback. It's got a prompt playground for testing multiple prompts on large swaths of data, and it integrates with common LLM suppliers like OpenAI and Anthropic. The company offers a variety of SDKs for integration and a few pricing tiers, including a free option, so it should be usable by small teams and adaptable to large enterprises.

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Freeplay

Freeplay is a wide-ranging set of tools for managing the life cycle of LLM product development. It's got tools for experimentation, testing, monitoring and optimization, with features for prompt management and versioning, automated batch testing and AI auto-evaluations. Freeplay offers lightweight developer SDKs and compliance deployment options, so it should be a good option for speeding up development velocity and lowering costs.

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LastMile AI

If you want something more elaborate, LastMile AI is a full-stack platform for productionizing generative AI applications. It's got features like Auto-Eval for automated hallucination detection, RAG Debugger for better performance monitoring and Service Mesh for unified API gateway access. The company's platform supports a range of AI models, and it's got a notebook-inspired environment for prototyping and building applications, so it's a good option for building more mature AI applications.

More Alternatives to HoneyHive

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Athina

Experiment, measure, and optimize AI applications with real-time performance tracking, cost monitoring, and customizable alerts for confident deployment.

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Klu

Streamline generative AI application development with collaborative prompt engineering, rapid iteration, and built-in analytics for optimized model fine-tuning.

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TeamAI

Collaborative AI workspaces unite teams with shared prompts, folders, and chat histories, streamlining workflows and amplifying productivity.

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Deepchecks

Automates LLM app evaluation, identifying issues like hallucinations and bias, and provides in-depth monitoring and debugging to ensure high-quality applications.

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Keywords AI

Streamline AI application development with a unified platform offering scalable API endpoints, easy integration, and optimized tools for development and monitoring.

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Appen

Fuel AI innovation with high-quality, diverse datasets and a customizable platform for human-AI collaboration, data annotation, and model testing.

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MLflow

Manage the full lifecycle of ML projects, from experimentation to production, with a single environment for tracking, visualizing, and deploying models.

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Vellum

Manage the full lifecycle of LLM-powered apps, from selecting prompts and models to deploying and iterating on them in production, with a suite of integrated tools.

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Openlayer

Build and deploy high-quality AI models with robust testing, evaluation, and observability tools, ensuring reliable performance and trustworthiness in production.

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Dataloop

Unify data, models, and workflows in one environment, automating pipelines and incorporating human feedback to accelerate AI application development and improve quality.

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Predibase

Fine-tune and serve large language models efficiently and cost-effectively, with features like quantization, low-rank adaptation, and memory-efficient distributed training.

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Abacus.AI

Build and deploy custom AI agents and systems at scale, leveraging generative AI and novel neural network techniques for automation and prediction.

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Airtrain AI

Experiment with 27+ large language models, fine-tune on your data, and compare results without coding, reducing costs by up to 90%.

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LLMStack

Build sophisticated AI applications by chaining multiple large language models, importing diverse data types, and leveraging no-code development.

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Contentable

Compare AI models side-by-side across top providers, then build and deploy the best one for your project, all in a low-code, collaborative environment.

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AirOps

Create sophisticated LLM workflows combining custom data with 40+ AI models, scalable to thousands of jobs, with integrations and human oversight.

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Honeycomb

Combines logs and metrics into a single workflow, with AI-powered query assistance, to quickly identify and resolve problems in distributed services.

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Dify

Build and run generative AI apps with a graphical interface, custom agents, and advanced tools for secure, efficient, and autonomous AI development.

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MonsterGPT

Fine-tune and deploy large language models with a chat interface, simplifying the process and reducing technical setup requirements for developers.

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Hebbia

Process millions of documents at once, with transparent and trustworthy AI results, to automate and accelerate document-based workflows.