Governance
AI Model Inventory
Every AI model and tool in active use is logged in one register, with its owner, vendor and purpose recorded.
Ask most companies which AI tools they use and the honest answer is a guess. This inventory finds out. It starts from what your team already knows, runs a short discovery pass across the systems in scope, and records every AI model and tool with its vendor, owner, purpose and risk level. The register lives in your own tools and stays current.
- Every AI tool in use recorded with vendor and owner
- Discovery pass that surfaces tools nobody had listed
- A risk level and purpose noted for each entry
$5,900
20–30 working days
Optional maintenance $295/mo
What it is
AI Model Inventory catalogs every AI model and tool your organization actually uses, recording its vendor, owner, purpose and risk level in one register that stays current as tools are added or retired. A discovery pass across your connected systems finds tools nobody had listed centrally.
Why businesses buy it
You cannot govern, secure or budget for AI tools you do not know about. Unlisted tools are where customer data leaks, duplicate subscriptions pile up and audit questions go unanswered. Building the list by email survey is slow and always incomplete. This inventory combines what your governance owner knows with a discovery pass, so the register reflects real use. It is often the first step before any other governance work, and the written scope sets what is covered before you order.
Problems this solves
Nobody knows every AI tool the business actually uses
A discovery pass across up to three connected systems finds tools nobody had listed centrally. Each one is recorded with its vendor, owner, purpose and risk level.
AI tool lists live in spreadsheets that quickly go stale
The register is set up to stay current as tools are added or retired. Changes come through the workflow configured in this build rather than someone's memory.
Risk questions stall because no tool has a named owner
Every entry carries an owner and a risk level. When a client, insurer or auditor asks about a tool, you know who to ask and how it was rated.
A good fit if
Nobody in your organization can currently list every AI tool that is actually in use, only the ones that were formally approved.
You need to know which team owns a given AI tool when a question about it comes up.
You are preparing for an audit, a security review, or a vendor risk assessment that starts with an accurate list.
New AI tools tend to show up through individual teams before anyone in IT or governance hears about them.
Not the right fit if
You need to track how much a tool is actually being used day to day, not just that it exists. See AI Usage Monitoring.
You need an approval process for new models, not a static list of what is already in use. See AI Model Governance.
You need the full governance build spanning policy, risk and audit as well as the register. See AI Governance System.
You need to check specific tools against regulatory requirements, not just list them. See AI Compliance Monitoring.
How it works
- We start from what is already known. Current AI tools and vendors your governance owner can name, plus any policy documents that mention them.
- Teams are asked what they actually use. A short discovery pass across the systems in scope, such as Google Workspace, Microsoft 365 or Slack, surfaces tools nobody had listed centrally.
- Each entry gets a full record. Vendor, owner, purpose, and a risk level, held in one register rather than scattered across spreadsheets and inboxes.
- The register is tested against real questions. Can you name who owns a given tool, and what it is for, in under a minute? That is the bar.
- Access to the register is set up. Governance, legal and IT can each check the same source rather than keeping their own partial lists.
- A findings report closes out the build. Summarizing what was found, including any tool nobody had previously logged.
What you provide within 72 hours
Your portal lists these the moment you order. Delivery starts the working day after everything is in and your access is checked.
- Your business information (company basics, hours and brand voice), shared during intake, or confirmation we can reuse what you gave us on an earlier order.
- Whatever list of AI tools and vendors you already have, even if it is incomplete.
- Copies of internal policies that mention approved or restricted tools, if they exist.
- A governance owner who can confirm ownership and purpose for each entry we find.
- Written authorization for any discovery pass across the systems in scope.
- Admin access and API keys for every connected system, shared by adding our team as a user or creating a key you control, never by email.
- One decision-maker who signs off the final register before handoff.
The 72-hour rule. Send everything on your checklist, including access, within 72 hours of ordering so your build starts on time.
Timeline
Start
business information confirmed and any existing tool list received.
Weeks 1–2
Discovery pass run across systems in scope, register populated with vendor, owner and purpose.
Week 3
Risk levels assigned and register access set up for governance, legal and IT.
Weeks 3–4
Findings report produced, listing any tool that was not previously on record.
Week 4
Your review and two rounds of changes to entries or fields.
Go-live
Live, recorded handoff session, and the 30 days of support begins.
| Option | Delivery time | Price |
|---|---|---|
| Standard | 20–30 working days | $5,900 |
| Express | 15–25 working days | $6,800 |
| Rush | 10–20 working days | $7,650 |
What you receive at handover
- AI Model Inventory configured and deployed, with a register of AI models and tools
- Results of the discovery pass across up to three connected systems
- Register fields for vendor, owner, purpose and risk level, plus workflow and guardrail configuration
- A test report with a control test log for the agreed scenarios
- An admin guide and a recorded 60-minute handoff session
- 30 days of post-launch support
Expected benefits and how to measure them
- Can give you one trusted list of the AI tools in use.
- Helps you spot unapproved or forgotten tools before they cause trouble.
- Makes risk and contract reviews easier because each tool has an owner.
- Tools in the register
- Count entries at launch and each quarter after. Compare with your old list to see what discovery added.
- Entries missing an owner or risk level
- Count incomplete entries each month and track them down to zero.
- Retired tools removed on time
- Check each quarter whether tools no longer in use still appear as active.
Before you start: Gather any existing list of AI tools and note when it was last updated. Ask each team lead which AI tools they use and record the answers.
These are things to track, not promised results. Outcomes depend on your data, your team and your market.
Running costs
The build price is one-time. Running the register afterwards costs roughly $20 to $300 a month in your own accounts, mostly hosting for wherever the register lives and any lightweight sync tools.
AI usage during build and testing also bills to your own accounts, so ownership of every provider relationship stays with you.
Ask about running costsCustom requirements
Need to surface tools across more than three connected systems, or track more than five fields per entry? Add a note at checkout for a written Change Quote, while your original order keeps its normal timeline. Larger or bespoke projects use the Custom AI request form.
Request a custom versionKeep it running
Optional monthly maintenance covers monitoring, fixes, model and platform updates, a monthly health report and monthly change hours, enough to add newly discovered tools or update an owner as teams change. It starts after the 30 days of support.
$295/mo (5% of the build price a month, includes 2 change hours)
Optional. Starts after the post-launch support period. Cancel any month.
How maintenance worksHow this compares
| Do it yourself with a SaaS tool | Hire a custom agency | Upmark Labs | |
|---|---|---|---|
| Price | A general IT asset management tool bundles this into a wider subscription | A consultancy bills for a discovery engagement | Ours is one fixed price, shown on this page before you buy |
| Scope | An asset tool tracks software generally, not AI specifically | An agency's discovery scope depends on what was agreed | Ours is written to AI tools and vendors specifically |
| Delivery | An asset tool still needs weeks of configuration and tagging | A discovery engagement often takes a month or more | Ours has a fixed delivery time shown before you buy, with faster options |
| Accuracy | An asset tool only sees what is registered through it | An agency's findings depend on who they manage to interview | Ours includes a discovery pass to surface tools nobody had listed |
Questions about this product
How much does AI Model Inventory cost?
The build is one fixed price covering everything on the Scope Card: the discovery pass across up to three systems, the populated register, its owner and risk fields, an admin guide and a recorded handoff. The price panel on this page shows that figure at each delivery speed, so you know the total before you commit. Keeping the register current afterwards is optional maintenance.
What does AI Model Inventory cost to run each month?
Running the register afterwards costs roughly $20 to $300 a month in your own accounts, mostly hosting for wherever the register lives, such as Notion or Confluence, plus any lightweight sync tools. There is no separate license fee on top of that. The exact figure depends on how many systems feed the register.
How is AI Model Inventory different from AI Usage Monitoring?
AI Model Inventory answers which AI tools exist, who owns them and what they are for, as a reference list that changes slowly. AI Usage Monitoring instead tracks how much each tool is actually being used in real time, which changes constantly. Most organizations build the inventory first, since usage monitoring needs a known list of tools to track in the first place.
What happens if the discovery pass finds a tool nobody registered?
It gets logged in the register with whatever owner and purpose we can establish, and flagged for your governance owner to confirm or reassign. We do not remove access to a tool or decide it should stop being used; a qualified person on your team makes that call once they see what was found, using the record as the starting point.
Can we add newly discovered tools to AI Model Inventory later?
Yes. Adding a tool that appears after launch, or updating an owner when a team changes, usually fits inside the monthly change hours included with maintenance. Expanding the discovery pass to a fourth or fifth connected system beyond the three in scope goes through a Change Quote agreed before that extra work begins on your register.
Can we cancel AI Model Inventory maintenance later?
Yes. Maintenance has no lock-in, so you can cancel any month once the 30 days of included support has ended. It covers monitoring, fixes, a monthly health report and monthly change hours for new tools or owner updates. Bigger changes go through a Change Quote.
Who owns the AI Model Inventory register once it is live?
You do. The register lives inside your own systems, such as Notion, Confluence or a spreadsheet you already use, not a platform we hold the keys to. We run the discovery pass and populate it, then hand it over with an admin guide and a recorded session, and every entry stays fully editable by your team.
Know exactly which AI tools are actually in use.
Order AI Model Inventory and a populated register of your AI tools, owners and vendors is live on a fixed delivery date.
Works well with
