Omniq

One person + a team of self-improving agents = 10×. Omniq Atlas gives every employee a team of specialist agents (20 role agents across developer, PM, director and CTO, with higher roles inheriting the agents below them). Those agents improve themselves every week by watching how people actually work. It solves the problem that enterprise agents ship once and never get better, and the risk that self-improving agents get worse or leak data. You hand off a job with @agent, and the agent answers in your context: your role, persona, projects, and only the documents IAM lets you see. There are no feedback forms. Rephrases, corrections, follow-ups (“now also write the rollback plan”, classified as an extension), regenerations and copies become signals in Atlas and in Raindrop. Raindrop’s Query API tells each agent where it fails, by failure type and playbook version. Every person and every agent runs a 7-day improvement cycle, and a Raindrop failure spike triggers one immediately. Each cycle proposes one change to the agent’s playbook (rules, retrieval, workflow or template). The change is kept only if it wins on unseen tests and a blind side-by-side replay, passes an absolute leak test, and reflects a pattern from 2+ people. Bigger changes wait for a manager. A watchdog compares Raindrop failure rates per version and auto-rolls back regressions. The gateway is model agnostic: local Gemma/Llama or any cloud model, with private data restricted to local models. Results so far: 26 automatic decisions, 6 kept, 12 undone, 4 refused, +38 points on kept changes, 0 leaks, and 78% of answers right the first time.