FIG 0.1
Discover what is already in use
Build an inventory from the systems you already run, then see status, ownership, usage, and risk in one place.
Product, Not a Service
AI governance, built as a product — not billed as a service.
Clarier is end-to-end software for discovering AI use, reviewing new tools, tracking decisions, and proving governance progress. Expert support is included, but the system belongs to your team.
What makes it a product
The work happens inside Clarier.
A service can advise you. Clarier gives your team the operating layer to keep AI governance moving every week.
FIG 0.2
Decide with a repeatable process
Evaluate new tools, embedded AI features, and internal builds with structured workflows and pre-built research.
FIG 0.3
Prove progress with evidence
Keep audit trails, maturity reporting, and stakeholder-ready views current as the program changes.
How we're built
Platform plus experts. That is the product.
Clarier can feel high-touch because our team helps you succeed. The difference is that the work is captured in a system your team keeps using.
Software your team can use
Your team logs in, sees the AI landscape, starts reviews, and tracks decisions directly in Clarier.
Connected signal
Discovery, vendor intelligence, approvals, and reporting stay connected instead of living in one-off files.
Reusable workflows
Requests, assessments, approvals, evidence, and re-reviews follow the same system every time.
Predictable commercial model
You buy the platform and included expert support, not a meter that runs every time your team needs help.
The Approach
Two very different ways to handle AI risk.
Professional services have a place. But AI governance needs a durable system of record, not only another point-in-time engagement.
Service-led model
✕Engagements scoped around a specific assessment or deliverable
✕Quarterly snapshots and point-in-time reports
✕Insights live in PDFs and shared drives
✕Teams wait for the next meeting to move a decision forward
✕Support is attached to the engagement and handoff
Clarier product model
✓A standing system your team keeps using after the first review
✓Current inventory, workflows, and reporting that update as work happens
✓Findings, approvals, evidence, and follow-ups live in the product
✓Business teams, IT, and reviewers can move work through the same flow
✓In-product guidance plus expert support included with the platform
Capability by Capability
A practical comparison for buyers.
The distinction is not software versus humans. It is whether the work becomes a repeatable operating system for your team.
| Capability | Service-led model | Clarier product model |
|---|---|---|
| AI tool discovery | Manual interviews, surveys, and spreadsheets | Automated discovery across identity, network, endpoint, SaaS, and DLP signals |
| Vendor & tool-request reviews | On-demand analyst work, often repeated from scratch | Pre-researched vendors and structured request workflows your team can reuse |
| Time to first value | Weeks of scoping before any output | A working inventory and review process as integrations and onboarding come online |
| Audit trail & evidence | Compiled by request, attached to email threads | Continuous, queryable, audit-ready by default |
| Ongoing monitoring | Re-engagement required | Continuous monitoring and re-review triggers built into the platform |
| Pricing model | Per-engagement, scope-driven, hourly add-ons | Predictable platform plans with included expert support |
| Self-service for teams | Routed through the vendor's analysts | Built-in portals for business teams, IT, and reviewers |
| Integrations | One-off exports and manual handoffs | Native sources across M365, Google Workspace, identity, security, and collaboration tools |
And yes — humans are included
Our team helps with onboarding, assessments, reporting, and program momentum. The difference is that every answer, review, approval, and evidence trail strengthens the same platform your team operates.
See what an AI governance product feels like.
A short walkthrough of the platform — and how your team would actually use it day one.