idappt lab:
how does it work?
idappt is an AI-native engineering lab. We don't just use AI to autocomplete code — we architect entire AI teams that design, build and test it.
How idappt lab works
Context pipelines
Every useful AI agent depends on the right information arriving at the right step. We design complex context pipelines that gather, filter, version, and route the documents, data, and instructions an agent needs — so each LLM call receives the task-relevant context it needs to make better-informed decisions.
LLM orchestration
Different models are good at different things. We orchestrate Large Language Models in concert — reasoning models for planning, fast models for routine work, specialised models for code, retrieval, or critique — so the right intelligence shows up for the right task.
Multi-agent software "startups"
We experiment with networks of specialised AI coding agents that can research, plan, build and review software as coordinated teams — organised in the roles a software company has: analysts, architects, engineers, testers. Humans set the mission, approve the direction, and answer for anything that ships.
Throughput of a much larger team
As a small foundation our goal is to achieve the throughput normally associated with a much larger software team — while at the same time being thorough in documentation, testability, accessibility, and the drive to develop solutions for citizens.