Healthcare & Life Sciences
PHI cannot leave the covered entity's control, and clinical risk tolerance is near zero. Epic and FHIR integration, HIPAA and HITRUST-aligned architecture.
AI for healthcareBuilt for organizations that cannot compromise on data control.
We work with sectors where the security and compliance requirements are the hardest part of the problem — not a checkbox at the end of it.
Every sector below shares one condition: the data that would make AI valuable is the data that cannot be exposed. Clinical records, transaction histories, controlled technical data, privileged matter files.
That constraint drives the architecture. It is why our practice is built around private deployment rather than around a vendor's platform, and why we lead with the data boundary rather than with the model.
What differs between sectors is not the engineering so much as the regulatory vocabulary, the systems of record, and what the auditor expects to see. Those specifics matter, and they are what the pages below cover.
Sectors
Where we work
Financial Services
Model risk governance and examiner scrutiny make explainability mandatory rather than desirable. Controls that survive examination under SR 11-7 and GLBA.
AI for financial servicesDefense & Aerospace
Controlled and classified data, frequently with no external connectivity at all. CMMC 2.0 and NIST SP 800-171 aligned, including fully air-gapped enclaves.
AI for defenseManufacturing & Industrial
Latency and connectivity constraints at the edge, with OT and IT separation to respect. Plant floor inference, connected or not.
AI for manufacturingGovernment & Public Sector
Public accountability, procurement constraints, and records law. FedRAMP-aligned architectures with the evidence trail that implies.
AI for governmentLegal & Professional Services
Attorney-client privilege and matter-level ethical walls. Privilege-preserving retrieval across iManage, NetDocuments, and Relativity.
AI for legal
Common ground
What these sectors share
The board mandate arrived before the architecture
Budget was approved on the strength of a demo. The security review then asked where the data goes, and the programme has been stalled at that question ever since.
The valuable data is the restricted data
The documents that would make retrieval transformative are exactly the ones under the tightest controls. Any architecture that routes around them delivers little.
Existing entitlements must be respected
These organizations already have carefully managed access control. A retrieval system that ignores it creates a disclosure incident, not a productivity gain.
Audit evidence is a deliverable, not an afterthought
Someone will eventually ask what the system did, on what basis, and who could see what. That has to be answerable from logs and lineage designed in advance.
Discuss your sector's constraints.
The assessment evaluates your data, infrastructure, and regulatory position, then recommends a deployment architecture your review process can actually approve.
We will sign your NDA before a detailed technical discussion.