Compliance Operations
AI Compliance Knowledge System
Organizes regulations and internal controls into a searchable knowledge base.
Compliance Operations
AI Compliance Monitoring
AI workflows are checked against your internal compliance rules on an ongoing basis, with issues flagged as they occur.
Compliance problems in AI workflows usually surface at audit time, months after they started. This monitoring turns the internal rules you name into checks and runs them continuously against the workflows in scope. When something breaks a rule, the flag names the rule and reaches your governance owner in Slack or Jira. Your compliance team judges each flag. The software does not.
- Internal compliance rules turned into continuous checks
- Issues flagged as they occur, not at audit time
- Each flag names the exact rule at stake
$6,900
20–30 working days
Optional maintenance $345/mo
What it is
AI Compliance Monitoring checks your AI workflows against your internal compliance rules on an ongoing basis, flagging issues as they occur rather than leaving them to surface at audit time. Each rule you name is turned into a specific check, and every flag reaches your governance owner with the rule attached.
Why businesses buy it
Finding a compliance gap during an audit means explaining how long it ran and why nobody noticed. Fixing it then is slower and more expensive than catching it the week it began. Manual spot checks cannot keep up with AI workflows that run all day. This monitoring checks continuously against your own rules, so issues reach a person while they are still small. The written scope lists the rules, monitors and systems covered, so you know exactly what is checked.
Problems this solves
Compliance problems in AI workflows only surface at audit time
The system checks your AI workflows against your internal rules on an ongoing basis. Issues are flagged as they occur, giving your team time to fix them before an audit.
Internal rules are written vaguely and nobody tests them
Each rule you name is turned into a specific check, up to five in this build. Your policies, up to twenty documents, are the source for those checks.
Flags reach a general inbox with no context attached
Every flag goes to your governance owner with the rule it relates to. They can see what was breached and why without reopening the policy.
A good fit if
You operate under specific regulatory requirements and need AI workflows checked against them continuously, not just once a year.
You want compliance issues flagged when they happen, not discovered when an external auditor arrives.
You already know which rules apply to your AI use and need them checked systematically, not applied inconsistently by different teams.
You need evidence of ongoing compliance checking to show a regulator, customer or auditor, not just a policy statement.
Not the right fit if
You need broad governance oversight across policy, risk and audit, not compliance-specific monitoring. See AI Governance System.
You need a reference knowledge base about which rules apply, not active monitoring against them. See AI Compliance Knowledge System.
You need a one-time rating for a specific initiative rather than ongoing checking. See AI Risk Assessment.
You need to watch agent behavior generally, not compliance specifically. See AI Agent Risk Monitor.
How it works
- We define which rules apply with you. Your governance owner names the specific requirements your AI workflows need to meet, drawn from your existing policies.
- Each rule is translated into a check. Turned into something the monitor can actually test against your workflows, rather than left as a general statement of intent.
- Checks run continuously against the systems in scope. Typically your AI applications plus Google Workspace, Microsoft 365 or Jira, wherever the workflow actually happens.
- Issues are flagged with the specific rule they relate to. Whoever reviews the flag knows exactly which requirement is at stake, not just that something looks off.
- Alerts route to Slack or Jira with that context attached. Your governance owner sees the flag and the rule behind it, ready for a qualified person to assess.
- A control test log and findings report confirm the checks work. Run against your agreed scenarios before handoff, not left untested.
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.
- The specific compliance rules or requirements your AI workflows need to meet.
- Your current AI tools and vendors, so we know what needs checking.
- A governance owner who can confirm what a compliance issue looks like in practice.
- Written authorization for any testing of the checks we configure.
- 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 rules and alert routing.
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 the compliance rules in scope named.
Weeks 1–2
Rules translated into checks and connections to systems in scope built.
Week 3
Alert routing configured to Slack or Jira with your governance owner.
Weeks 3–4
Control test log and findings report produced against agreed scenarios.
Week 4
Your review and two rounds of changes to rules or routing.
Go-live
Live, recorded handoff session, and the 30 days of support begins.
| Option | Delivery time | Price |
|---|---|---|
| Standard | 20–30 working days | $6,900 |
| Express | 15–25 working days | $7,950 |
| Rush | 10–20 working days | $8,950 |
What you receive at handover
- AI Compliance Monitoring configured and deployed, covering up to three AI systems or workflows
- Up to five compliance checks built from your internal rules
- Flag routing to your governance owner, with the relevant rule attached
- 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 turn audit preparation from a scramble into a review of known issues.
- Helps your governance owner act on problems while they are small.
- Makes vague internal rules concrete and testable.
- Flags raised per rule
- Count flags for each rule every month from the console. A busy rule may point to a process that needs changing.
- Time to resolve a flag
- Compare the time a flag was raised with the time it was closed, tracked monthly.
- Audit findings on AI workflows
- Compare findings at the next internal or external audit with the one before launch.
Before you start: List the internal rules your AI workflows must follow and any findings from the last audit. Note how breaches are spotted today.
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 monitoring afterwards costs roughly $20 to $300 a month in your own accounts, mostly hosting and the logging tools that hold checks and alerts.
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 monitor more than three connected systems, or more than five compliance rules? Add a note at checkout for a written Change Quote; your original order keeps its normal timeline while you wait for it. Larger or bespoke projects use the Custom AI request form.
Request a custom versionKeep it running
Monthly maintenance covers monitoring, fixes, model and platform updates, a monthly health report and monthly hours for changes, which covers a new rule as regulations shift or an adjusted threshold as your workflows change. It starts after the 30 days of support.
$345/mo (5% of the build price a month, includes 3 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 compliance suite bundles this into a broader per-seat subscription | A compliance consultancy bills for periodic reviews | Ours is one fixed price, shown on this page before you buy |
| Scope | A suite covers many regulations generically, few of them precisely | An agency review happens on a schedule they set | Ours checks the specific rules you name, continuously |
| Delivery | A suite needs real configuration before checks reflect your business | A compliance review can take weeks to complete | Ours has a fixed delivery time shown before you buy, with faster options |
| Timing | A suite's alerts depend on how well it was configured | An agency review finds issues only when it runs | Ours flags issues as they occur, not at the next review |
Questions about this product
How much does AI Compliance Monitoring cost?
It is one fixed price for everything on the Scope Card: defining the rules with you, turning each into a check, connecting up to three systems and routing flags, plus testing and a recorded handoff. The price panel on this page lists the figure at each delivery speed. Supporting your compliance process is the goal; the monitoring does not certify compliance.
What does AI Compliance Monitoring cost to run each month?
Running the monitoring afterwards costs roughly $20 to $300 a month in your own accounts, mostly hosting and the logging tools that hold checks and alerts. There is no separate platform license beyond that. The exact figure depends on how many systems you connect and how much activity they generate each month.
How is AI Compliance Monitoring different from AI Compliance Knowledge System?
AI Compliance Monitoring actively checks your AI workflows against specific rules and flags issues as they happen. AI Compliance Knowledge System is a reference tool instead: a searchable base of the regulations and controls relevant to your business, for people to look things up in. Many buyers build the knowledge base first, then add monitoring once the rules are clearly defined.
What happens when AI Compliance Monitoring flags an issue?
The flag names the specific rule at stake and routes to Slack or Jira with that context, so your governance owner can review it quickly. The monitor does not decide whether the issue is actually a violation or take corrective action; a qualified person assesses the flag against the full picture, because that judgment call belongs with your compliance or legal team, not the software.
Can we add more compliance rules to the monitoring later?
Yes. Refining an existing rule, or adjusting an alert threshold as a regulation is clarified, usually fits inside the monthly change hours in maintenance. Adding a fourth connected system beyond the three in scope, or a sixth rule beyond the five included, goes through a Change Quote agreed before that extra work starts on your monitoring.
Can we cancel AI Compliance Monitoring maintenance later?
Yes. Maintenance bills monthly with no lock-in, so you can cancel any month once the 30 days of included support has ended. If your rules stay stable, you may decide the monitoring stays current without it, and you can start again later if things change.
Who owns the compliance checks and alert history?
You do. The rules, the checks and the alert history all live inside your own connected systems, such as Jira or Slack, not a platform we control. We configure the monitoring and hand it over with an admin guide and a recorded session, and every rule and flag stays fully visible and editable by your team.
Catch a compliance issue when it happens, not at audit time.
Order AI Compliance Monitoring and your AI workflows are checked against your compliance rules, live on a fixed delivery date.
Works well with
Compliance Operations
AI Policy Assistant
Answers staff questions about AI and data policies with citations.
