Our technology
Agentic AI Data Pipeline
A modular, on-premise pipeline of agents and verifiers that turns raw tickets, documents, logs and images into validated, evidenced outputs.
Agents collect, clean, label and transform data from your systems - Jira, GitHub, Figma, PACS, WMS, sensor logs - and hand every result to a verifier we have measured with mutation testing. A human accepts or rejects, and the decision is recorded.
Proven pipeline steps crystallise into deterministic, zero-token scripts, so cost falls as usage grows. The AI Security Gateway minimises context, tokenises sensitive data and routes each task to the smallest model that can do it.
Research on arXiv
- Reflexion: Language Agents with Verbal Reinforcement Learning
- Let's Verify Step by Step
- DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines
Used in
See it on your own data
We start with an MVP on your screens, devices or tickets. Request an MVP and bring a real use case.
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