Separate client workspaces
Keep systems, evidence, users and delivery records scoped to the correct client and agency.
FOR MULTI-CLIENT AI DELIVERY TEAMS
Turn scattered AI governance work into a client-ready proof trail.
Keep each client's AI inventory, human-review decisions, supporting evidence, review dates and audit history in one separated workspace — then deliver a clean report or revocable share without mixing tenants.
Client-separatedWorkspaces and delivery records stay scoped to the correct client.
Human reviewedThe software records decisions; it does not issue legal verdicts.
Evidence linkedSupporting proof stays attached to the system and decision context.
Controlled sharingClient-facing links can expire or be revoked.
HOW IT WORKS
One operating trail from deployment to client handoff.
Instead of rebuilding the story from spreadsheets, inboxes and folders, the team maintains a small set of durable operational records.
AI system inventory
Record the system, use case, provider/deployer role, owner and factual operating context.
Human review
Surface review prompts, record the human decision, and keep review dates and currentness visible.
Evidence + audit
Attach supporting evidence and preserve reviewable activity history over time.
Client-ready delivery
Generate a branded report or controlled share without exposing another client's workspace.
WHO IT IS FOR
Built for teams carrying responsibility across multiple client AI systems.
Keep the evidence trail after go-live.
Move from advisory, pilot and deployment into a maintainable client record instead of a project folder that freezes on handoff.
Run recurring client reviews without rebuilding context.
Keep decisions, evidence, ownership and review dates tied to the same operational system record.
Give clients a clean proof package.
Deliver a reviewable summary while keeping internal files, other tenants and working notes separated.
SYNTHETIC EXAMPLE — NO CUSTOMER DATA
What a usable proof trail looks like
ClientMaison Nova
AI systemCustomer Booking Assistant
StackOpenAI + n8n
Recorded roleDeployer
1
Inventory record
RecordedCustomer-facing booking assistant, owner and operational use case recorded.
2
Review prompts
3 actionsRelevant transparency and human-review questions surfaced from recorded facts and versioned sources.
3
Human decision
AuditedThe responsible operator confirms, rejects or marks a prompt not applicable.
4
Supporting evidence
LinkedApproved disclosure/control evidence is linked to the same AI system and review context.
5
Client handoff
DeliverableThe report/share packages inventory, decisions and evidence into a reviewable client-facing trail.
SECURITY & TRUST
Designed for client separation, controlled access and reversible sharing.
Trust is part of the workflow. AI Gov Trail keeps operational data separated by workspace, supports role-based team access and makes external report sharing explicit and revocable.
Client and agency records are scoped to the correct workspace rather than mixed into one global evidence pool.
Owners, admins, members and viewers have distinct operating boundaries.
Read-only report links can expire or be revoked; private evidence-file downloads are not exposed through the share.
The product records facts, prompts, decisions and evidence without claiming automatic legal sufficiency or certification.
RESOURCES
Practical notes for teams operating AI across clients.
No content farm. The resource library focuses on concrete operating questions that appear after AI systems move into real use.
OPERATIONS
What should exist after an AI system goes live?
A practical evidence trail for inventory, decisions, supporting proof and re-review.
MULTI-CLIENTHow to structure AI inventory across client accounts
A model that stays useful after the spreadsheet grows beyond the first few systems.
HUMAN REVIEWWhat makes a human-review record actually useful?
Capture enough context to explain what was reviewed, by whom, when and against what evidence.
FAQ
Questions a serious buyer should ask.
Is AI Gov Trail a legal compliance checker?
No. It is an operational evidence workspace. It helps teams record facts, human-review decisions, evidence and audit history; legal conclusions remain with the responsible people and advisers.
Is this only for the EU AI Act?
No. Article 50 and transparency work are an initial wedge, but the product's core job is broader: maintain a durable operating trail for client AI systems.
Can one agency manage several clients?
Yes. Multi-client separation is the primary operating model rather than an afterthought.
What does a client receive?
A reviewable client-facing report or controlled share containing the relevant inventory, human-review status and evidence index.
Does a trial require payment details?
No. During controlled beta, invited design partners can use one private workspace for seven days without a card or automatic renewal.
What happens after the seven-day trial?
We first ask whether the workflow was genuinely useful. Commercial terms are discussed only after the team has had a chance to use the product on a real or sanitized workflow.
WHY WE ARE BUILDING IT
Governance should survive the handoff.
AI projects often produce a strong implementation moment and a weak operating record. AI Gov Trail is being built around the opposite assumption: the evidence, decisions and review context should remain usable after the project team moves on.
EARLY CONTROLLED BETA
Try one private client workspace for 7 days.
One workspace, one real or sanitized client workflow, up to two AI systems, the full core evidence flow, no card and no commitment. The goal is simple: find out whether this actually improves your operating work.
7 daysPrivate workspace
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