Governance in the design
Governance is part of the first design review, with model risk and its evaluation criteria agreed before any code reaches production.
AI governance your regulator can inspect line by line
We engineer governance into the architecture from the first design review, so every decision leaves a trail your auditor and your regulator can follow back to its source.
- ISO/IEC 27001:2022
- SOC 2 Type II
- PII masking
- AES-256 encryption
- Isolated hosting
- Role-based access
What we engineer
Assurance engineered into every stage
A trail an auditor can follow
Every decision leaves a documented trail that your internal reviewers and your regulator can follow back to its source.
Watched after go-live
Monitoring continues for as long as the system is in operation, so a change in behaviour is caught and recorded well before any audit.
Accountability by design
Everything an auditor will ask to see
A complete audit trail
Every decision is logged with its source, so any action can be reviewed independently after the fact.
Every answer explained
Responses that matter carry inline citations and a confidence score, so a reader can check the evidence before acting on it.
Human in the loop
Consequential decisions escalate to a person, so the final call on anything that matters stays with your team.
Secure by default
Data is encrypted to AES-256 and personal information is masked before any model sees it.
Role-based access
Each user sees only the sources their role permits, with least-privilege access as the default.
ISO 27001 certified
An information-security foundation certified to ISO/IEC 27001:2022 and held to SOC 2 Type II, both independently audited.
Where it operates
See all case studiesGoverned outcomes, proven in production
74% reduction in evaluation time through AI-native candidate screening
97%
Faculty concordance
9,200+
Candidates evaluated
6,100
Person-hours saved a year
A rubric-based evaluation methodology for consistent and explainable candidate screening at scale, free of bias.
Read the case studyThe path to production
We operate what we engineer
Discovery
Discovery ends with a written outcome and the metric we will report against.
~1 week
Prove it on real data
We engineer against your real workflow, with its actual data and its edge cases.
~2 weeks
Go live
We move the proven system into production without your data leaving your environment.
~1 week
Validate
We test under real conditions and record the evidence your reviewers will ask for.
~2 weeks
Operate & iterate
We operate the system and report against the number agreed at the start.
Recurring
From the blogField notes from the people
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