LastMile AI: Debug, Evaluate & Improve AI Apps

LastMile AI turns the often chaotic process of building generative AI applications into a more rigorous, measurable discipline. At its core is AutoEval, a comprehensive evaluation suite that lets teams test, benchmark, and fine-tune custom evaluator models tailored specifically to their RAG pipelines or multi-agent systems, rather than relying on generic off-the-shelf metrics. This science-first approach gives developers concrete signals about where their AI is succeeding or failing before it ever reaches production. Beyond evaluation, the platform rounds out the AI development lifecycle with synthetic data generation for training robust evaluator models, experiment management for tracking iterations, and online guardrails that continuously monitor live applications to catch drift, hallucinations, or performance regressions in real time. With blazing-fast inference infrastructure and support for secure deployment inside a private virtual cloud, LastMile AI is built to satisfy both the iteration speed developers crave and the security guarantees enterprises demand. Whether you're shipping a retrieval-augmented chatbot or orchestrating a fleet of autonomous agents, LastMile AI gives you the instrumentation to move from guesswork to data-driven confidence at every stage of deployment.

1. Install the LastMile library using pip or yarn. 2. Import the AutoEval class into your project. 3. Run evaluations against your AI outputs using built-in metrics, or define custom metrics suited to your use case. 4. Fine-tune evaluator models with your own data or generated synthetic data. 5. Set up online guardrails to continuously monitor your application in production. 6. Use the experiment management tools to track changes and benchmark performance over time.