If you're looking for a platform that uses AI to accelerate product verification and validation, Autoblocks is definitely worth a look. It includes a range of tools for collaborative testing, monitoring and debugging, and integrates with tools like LangChain, LlamaIndex and OpenAI. It's geared for fast iteration and secure development, and is good for consumer and enterprise markets.
Another strong contender is Dataloop, which handles data curation, model management and pipeline orchestration to accelerate AI application development. It offers tools for data management, model deployment and pipeline automation, and has strong security controls. Dataloop can handle a variety of unstructured data types and is designed to improve collaboration and development productivity, with big time savings and quality improvements.
For more specific needs in self-service QA testing, check out QA.tech. This AI-based platform crawls web applications, runs tests and produces detailed bug reports so software can be tested without manual labor. It can be integrated with CI/CD tools and offers immediate feedback, which is good for SaaS companies that have to test a lot of user flows.
If you're building GenAI applications, HoneyHive is a powerful AI evaluation, testing and observability platform. It can handle automated testing and debugging, dataset curation and prompt management, and integrates with popular GPU clouds for broad model support. It's good for teams that need a full-fledged platform for AI product development and quality assurance.