Handit

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 workflows

Iterate quickly and ship confidently. Confidently ship by evaluating your prompts with a suite of evals like context recall, llm-rubric (LLM as a judge), latency, and more. Let us handle intelligent caching and complex implementations to save you time and money. Quickly iterate on your prompts in a collaborative playground that supports all the major providers, variables, automatic versioning, and more. Easily build datasets from real data using Logs, upload your own as a CSV, or collaboratively build and edit within your Adaline workspace. Track usage, latency, and other metrics to monitor the health of your LLMs and the performance of your prompts using our APIs. Continuously evaluate your completions in production, see how your users are using your prompts, and create datasets by sending logs using our APIs. The single platform to iterate, evaluate, and monitor LLMs. Easily rollbacks if your performance regresses in production, and see how your team iterated the prompt.