HoneyHive

Product information

HoneyHive is a platform designed for developers working on AI applications. Its purpose is to ensure that artificial intelligence is reliable and trustworthy. It aims to aid developers by providing a range of tools and features to enhance the development, deployment, and continuous improvement of AI products, particularly those employing large language models (LLMs).

Key features

• Test Suites for offline evaluation of AI applications.
• Observability and analytics for monitoring AI performance.
• A collaborative prompt engineering toolkit to facilitate team collaboration on AI prompts.
• Tools to debug AI chains, agents, and retrieval pipelines.
• A set of metrics and guardrails for evaluating AI applications.
• Storage for logs, traces, and test cases.
• A model registry for managing different AI model versions.
• A streamlined method for fine-tuning models with OpenAI.
• Tools to help deploy from an experimental phase to production environments with greater confidence.

The HoneyHive platform emphasizes collaboration, allowing product managers, developers, and domain experts to work together in what they call a "Playground". This workspace supports iterative development with features like version control and integration with external tools. Once ready, products can be evaluated rigorously using the platform's end-to-end testing features.

For deployed applications, HoneyHive highlights its observability and analytics capabilities, helping to refine products further by offering insights into user behavior and performance metrics. It also includes debugging tools for comprehending complex system interactions and mining valuable insights from unstructured text data.

The platform is designed to integrate seamlessly into existing Large Language Model (LLM) stacks and extols a developer-friendly environment. Its SDK is described as non-intrusive, not requiring redirection of requests through HoneyHive servers, and accommodates any model or framework.

With enterprise security in mind, HoneyHive provides encryption, access controls, and tools to sanitize personally identifiable information (PII), aiming to ensure that AI is adopted safely and at scale. The site mentions the flexibility of cloud-native architecture, emphasizing scalability up to millions of requests and including enterprise-focused support, with customer service managers and continuous support available.

HoneyHive champions a shared working environment, not only for developers but also for product managers and data scientists, suggesting features to help these roles in developing and refining AI applications.

A sign-up for beta access is available, as well as options to book a demo. The platform underlines its commitment to data privacy and security, allowing users to deploy on either HoneyHive Cloud or their private computing environments with assured data and model ownership.

The website includes additional resources like documentation and a blog for learning more about the platform, as well as a careers section for interested job applicants. HoneyHive is present on social platforms such as Discord, Twitter, and LinkedIn, providing various avenues for community engagement and support.