Selected engagements, written by the engineers who delivered them. Customers are anonymized by default, and every number says exactly what kind of number it is.
One competitive proof of concept that became a production network. One Phase-0 AI proof of concept built entirely on synthetic data. Both are described in the same detail we would use internally.
A global, multi-site organization ran a competitive proof of concept to find a credible path to a policy-driven network. The Cisco architecture our engineers designed won the evaluation — and the same engineers were engaged to deliver it.
Read the use caseA Québec health network needed to know whether AI could read clinical urgency reliably in Québec French and Canadian English — before funding a build. We proved it on fully synthetic voicemails, with no patient information.
Read the proof of conceptEngineering work in regulated environments is done under confidentiality. We would rather publish the architecture honestly than trade a customer’s name for marketing collateral.
Customers are described by profile — industry, scale, environment — never identified. We name a customer only with their explicit written permission, and we have not asked these two for it.
A figure measured in production and a figure measured in a proof of concept are not the same claim, so we never let them look the same. Where a number comes from a model or a synthetic dataset, it says so beside the number.
Each use case is written from the engineering record by the people who did the work, then reviewed. If a phase was scoped but not delivered, it is described as scoped, not delivered.
A senior engineer — not a salesperson — will spend 30 minutes on your environment and give you an honest read on fit.