Exploring Reliable AI Infrastructure
We research how intelligent systems can work reliably — with knowledge you can trust, decisions you can trace, and coordination that scales.
AI is becoming autonomous
AI systems today don't just answer questions — they search, call services, run models, and act. Some work is straightforward. But the interesting work branches: gather facts, compare sources, reconcile conflicts, loop back.
The harder it gets, the messier it becomes
Hallucinations
Both agents and their orchestrators can confidently produce false information.
Opacity
Decisions become black boxes. There's no clear explanation of why.
Scattered Knowledge
Information lives across vector stores, tables, graphs — no center of gravity.
Unmeasured Autonomy
No way to know how well agents are actually performing.
Incoherence
Multiple agents conflict, contradict, and don't coordinate.
Cost Drift
Unpredictable costs with no clear quality-latency-cost trade-offs.
The graph as memory and control surface
We make the graph not just storage, but the place where knowledge lives and where work is governed.
Primitives for governing AI through structured knowledge
We research and develop methods that address these fundamental problems.
Research that translates to production
Our work produces systems that partners integrate into real applications.
Interested in our research?
We work with partners who want to integrate reliable AI infrastructure into their systems.
Or email us at hello@xploreintelligence.co.uk