AI is being deployed faster than the tools to govern, monitor, and trust it are being built. Qanata Labs works on that gap - in the open, one project at a time.
AI is being deployed faster than the infrastructure to govern it is being built. The people who understand that gap most clearly are not vendors - they're the practitioners living inside it every day.
Enterprise vendors are selling governance frameworks to buyers who don't fully understand what they're buying. The resulting tools are compliance theatre, not operational reliability. Qanata Labs builds from a different position: the inside out, practitioner-first, in the open.
Each one compounds the others. Together they explain why AI is failing silently in production environments across every regulated industry.
Organisations are deploying models into production workflows before the infrastructure to monitor, govern, and trust those outputs exists. Silent failures are the result.
Vendors are selling governance to buyers who don't understand what they're buying. The result is compliance theatre. The failure modes remain invisible.
Developers, architects, and knowledge workers know exactly where AI fails in their workflows. That knowledge isn't making it into the tools - yet. That's what we're fixing.
We incubate focused infrastructure tools. Some will become products. Some will inform the ones that do. All of it is open.
AI chat that runs entirely in your browser. No servers, no API keys, no data leaves your device. Runs open-source models locally via WebGPU.
Async coordination layer between AI agents and human decision-makers. Agents request approvals with full context; humans respond via web or Slack; every transition is audit-logged.
Open dataset tracking AI crawler and agent behaviour in real time. Identifies and logs AI user agents as they crawl, building a longitudinal record traditional analytics can't see. Watch this space: the bots are feeding it faster than we are.
One AI architect and information scientist. One enterprise technology leader who started as a developer. Between us, 30-plus years building, selling, and shipping technology at Microsoft, Cisco, Autodesk, and Oxford University Press - and two startups built from scratch.
Currently leading AI strategy and implementation at Oxford University Press, where he builds the frameworks and technical infrastructure that turn emerging AI capabilities into products learners and teachers can trust. Previously in Microsoft's Cloud + AI division, where he developed hands-on understanding of how ML systems operate at enterprise scale. His background in information architecture and data quality gives him a perspective that is rare in AI leadership - a deep grounding in the structures that determine whether AI actually works in production.
linkedin.com/in/isaacpattisMarketing and growth leader with 30 years across startups, scale-ups, and global technology companies. Started as a developer - C, assembly, and systems software - before moving into sales and go-to-market roles at Microsoft, Cisco, and Autodesk. Has held executive roles including CMO and CRO, and built revenue teams from the ground up at two startups. Brings the commercial instinct and enterprise relationships that turn infrastructure tools into businesses.
linkedin.com/in/markalani
Qanata takes its name from the qanat - an ancient system of underground channels, engineered
to carry water safely and continuously across harsh terrain to the communities that depended on it.
The engineering was invisible. The delivery was reliable. The system was
built to last.
That's what good infrastructure does. That's what we're building for AI.
Everything starts open. Because the practitioners who understand this problem best should be able to inspect, fork, and build on the work.