AI Training & Distribution Platform
An AI-native platform that trains, fine-tunes, and serves a fleet of specialized AI agents — from a daily training loop to a production inference API.
Photo: ChrisDag, CC BY 2.0Problem
Shipping reliable, specialized AI agents required more than one general-purpose model — different agent roles needed different behavior, and the training pipeline needed to keep improving without manual intervention.
Approach
Built a daily automated training loop that collects new examples, fine-tunes per-agent adapters, and validates them before rollout, on top of a local inference engine serving an OpenAI-compatible API.
Architecture
A backend with a ReAct-style agentic loop, multiple specialized agents with role-specific prompts, a local model engine for inference (no cloud GPU dependency), streaming responses for chat, and a nightly training daemon that retrains and validates adapters.
Results
[Placeholder — measurable outcome, e.g. training cadence, response latency improvement]