The interpretation layer
London · 2026
Violet Labs builds the interpretation layer for agentic systems. Reasoning frameworks that encode how your best people think. Data reading guides that teach agents how to query your systems accurately. The layer that turns raw model capability into output that's specific to your business.
The systems are circular by design. Agents analyse through the frameworks, discover patterns in what works, and write back into the reasoning they run on. Soft adjustments decay if not reinforced. Permanent changes require human approval. The system sharpens itself through use.
Intelligence systems that make your data queryable through agents. Meta-cognitive reasoning techniques with structured memory and learning loops driven by real data and human interaction. Design tooling for teams constructing their own agents. Three paths into the same architecture.
Make your data queryable through agents that reason about your business. For companies building toward AI-native operations. Named systems designed around specific domains, with reasoning frameworks that compound across your organisation. The foundation goes live once. Every system after is a new framework cluster, not new architecture.
See the systems →Meta-cognition, reasoning frameworks, and data reading guides. The approach that teaches agents to question their own thinking and detect their own drift. We set up the correct learning loop so the interpretation layer evolves with your business. Frameworks don't go stale. They sharpen.
Read the methodology →The design tool for agentic systems. Four lenses that assess whether your agents will serve their purpose: scope, architecture, drift, and knowledge encoding. Use it as a skill alongside your build, or upload what you've built and get a review back.
See tooling →Every system we deploy is calibrated to detect its own drift. Agents measure their output against real business outcomes, goals, and objectives. Structured memory gives them the data to reason accurately. That's how a system stays aligned as the business evolves.
The system finds patterns across your data that no individual would spot. Each observation is tracked in structured memory that gives agents the context to decipher what's changed and why. These are observations, not conclusions.
Observations accumulate into hypotheses. Hypotheses surface for human review with full evidence. Only confirmed patterns feed back into the interpretation layer. The system discovers. Humans decide.
Confirmed patterns update the reasoning frameworks. Every agent downstream reads through the new lens automatically. The system forgets what's no longer true. The intelligence compounds through use.
Each article addresses a specific way agents lose alignment in production and the design principle that prevents it. The intellectual foundation the company is built on.
Read all →Whether you're building agentic systems from scratch or your agents are already drifting. The first conversation is exploratory.
Get in touch → or read the design philosophy