LastMile

Its core product is a notebook-based development environment similar in concept to Jupyter notebooks but purpose-built for AI application development where developers define AI pipelines, test prompts against real inputs, evaluate output quality systematically, and iterate rapidly without the friction of switching between multiple development tools.

This integrated approach is designed to address the gap between AI prototypes that work in demos and AI applications that perform reliably in production across the full distribution of real user inputs.

A central feature of LastMile is its evaluation framework, which enables development teams to define quantitative metrics for AI output quality accuracy, coherence, task completion rate, safety and run systematic evaluations against test datasets at every iteration.

Rather than relying on manual inspection of AI outputs to assess quality, teams can establish automated evaluation pipelines that catch regressions when prompts, models, or retrieval configurations change.

This evaluations-first approach to AI development is increasingly recognized as the key engineering practice that separates AI applications that remain reliable over time from those that degrade as conditions change.

LastMile supports multi-model workflows where different models are applied to different stages of an AI pipeline based on their respective strengths for example, using a smaller, faster model for initial classification and a more capable model for nuanced generation.

Its deployment infrastructure manages versioning, rollout, and A/B testing of AI pipeline changes in production, giving engineering teams the same deployment control over AI applications that they have over traditional software releases.