Research

Building the trust layer for autonomous AI.

Technical writing on the architecture that makes AI agents trustworthy in production — from pre-production simulation to runtime drift detection.

Architecture/Technical deep dive

01/ARCHITECTURE

The Fabrik Architecture: Building Trustworthy AI Agents

A complete system architecture spanning pre-production simulation to production monitoring — deterministic isolation, tool interception, context engineering, adversarial generation, trace analysis, and drift detection working together to catch failures before users experience them.

18 min

Reliability/Why simulation matters

02/RELIABILITY

Evals Aren't Enough: Reliable Agents Need Simulation

AI agents don't fail because they can't answer a question. They fail because they're systems — stochastic, stateful, tool-using pipelines. Why evaluation datasets can't predict reliability, and what simulation adds.

12 min

03/RELIABILITY

Why Agent Reliability Is a Systems Problem

Modern agents maintain memory, call tools, mutate state, and coordinate workflows across long-running sessions. Once they operate across evolving state, reliability becomes a systems-engineering problem — not a model-evaluation problem. A technical look at orchestration as the real reliability layer.

14 min

Mission

To make AI agents trustworthy in the real world.

Through integrated systems spanning pre-production simulation to production monitoring.