If you're looking for a replacement for Autoblocks, Humanloop could be a good option. The service is geared to oversee and optimize Large Language Models (LLMs) applications, tackling issues like suboptimal workflows, manual evaluation and bad collaboration. Humanloop has a collaborative prompt management system, an evaluation and monitoring tool for debugging, and customization and optimization tools. It integrates with common LLM suppliers and has Python and TypeScript SDKs for easy integration, so it should appeal to product teams, developers and anyone building AI capabilities.
Another good option is HoneyHive. The service offers a single environment for collaboration, testing and evaluation of GenAI applications, including monitoring and debugging LLM failures in production. HoneyHive supports automated CI testing, observability, dataset curation, and prompt management. It also has a playground for collaborative testing and deployment of new prompts and models, so it's a good option for teams building GenAI applications.
If you want a unified DevOps platform, Keywords AI could be a good alternative. It streamlines the full life cycle of AI software with a single API endpoint for multiple LLM models, easy integration with OpenAI APIs, and a playground for testing and refining models. The service also includes performance monitoring, data collection and fine-tuning, so it's a good option for AI startups that want to concentrate on building products, not infrastructure.