Every AI project,on the record.
Continuum vets, prices, and approves AI initiatives against your own governance policy — turning the documents you already wrote into a decision your committee can actually defend.
6 pillars · 4 approval gates · 1 audit trailCustomer support copilot
Policy compliance
92Data access
78Security & identity
88Technical fit
84Regulatory exposure
54Operational readiness
7178
/ 100The problem
AI adoption is outrunning AI governance. Most organisations have no structured way to decide which projects should proceed — so the decision defaults to whoever asks last.
Continuum puts policy management, risk assessment, cost estimation, and committee review on one surface. Teams move at the speed they want; governance stops being the thing they route around.
How it works
Onboarding to approval
Four gates. Each one produces evidence the next one depends on.
Onboard your organisation
Upload policy documents and Continuum extracts the prohibited topics, approval rules, and regulatory frameworks buried inside them.
Submit an AI project
A governance assistant interviews the project owner, probing risk across six pillars and flagging conflicts with your policy.
Estimate the cost
Generate a monthly cost model from usage, deployment shape, integrations, and the infrastructure you already run.
Committee review
Assigned reviewers weigh the evidence and the cost analysis, then approve or reject against a permanent audit trail.
Capabilities
Everything the committee asks for
Policy extraction
Point Continuum at the governance documents you already have. It reads them and turns prose into structured policy config — no manual re-entry.
AI vetting conversations
Structured probing across all six pillars, with per-answer evidence captured and scored.
Committee workflows
Chairs, reviewers, routing rules, and recorded decisions.
Cost analysis before approval
Every project arrives at the committee with a defensible monthly estimate attached, so approval is a budget decision as well as a risk one.
Build orchestration
Authorised projects provision real Azure infrastructure against the gates that approved them.
Continuous audit trail
Who decided what, on which evidence, at which time — retained and exportable.
Assessment model
Six pillars, weighted and evidenced
Every submission is scored against a structured framework. Each pillar carries its own weight, its own confidence, and the specific evidence drawn from the assessment conversation that produced it.
Policy compliance
Data access
Security & identity
Technical fit
Regulatory exposure
Operational readiness
Put your AI programme on the record
Set up your organisation in minutes, invite your governance committee, and start vetting projects against the policy you already have.