Controls & Monitoring
AI Agent Risk Monitor
Monitors agent actions for risky or unexpected behavior.
Controls & Monitoring
AI Security Monitoring
Security-relevant events across your AI systems are centralized and watched continuously, with alerts reaching your team as they happen.
Security signals from your AI systems are scattered across a dozen logs that nobody reads until something breaks. This monitoring brings logins, configuration changes, error spikes and unusual usage into one place, watches them continuously and ranks what it finds. Alerts reach Slack or Jira with enough context to act. A person on your team always makes the call.
- Security events from your AI systems gathered in one place
- Unusual logins, config changes and error spikes ranked by severity
- Alerts with context delivered to Slack or Jira
$5,400
20–30 working days
Optional maintenance $270/mo
What it is
AI Security Monitoring is an agent that centralizes security-relevant events, such as logins, configuration changes and error spikes, from across the AI systems you name and watches them for anything worth attention. It is general-purpose and ongoing, not one narrow signal like API traffic or data content alone.
Why businesses buy it
Most security incidents leave traces well before anyone notices them: a strange login, a changed setting, a burst of errors at night. When those traces sit in separate logs, they stay invisible until the damage is done. Pulling them into one watched view gives your team a fair chance to catch problems early, without hiring a dedicated analyst. The written scope lists the systems and monitors included, so you know what coverage you get before you order.
Problems this solves
Security events from AI tools sit in separate logs nobody reads
The monitor centralizes logins, configuration changes and error spikes from up to three AI systems. Your team reviews one admin console or written report instead of checking each tool on its own.
A suspicious login or settings change can go unnoticed for weeks
Up to five monitors are configured to watch for the events your policies care about. When one fires, it is raised for attention rather than waiting for someone to stumble across it.
Error spikes are hard to tell apart from everyday noise
Monitors are tested against agreed scenarios, and the control test log records how each one behaved. Two revision rounds let you tune what counts as worth attention before handover.
Policies say what to watch, but nothing is actually watching
We read your security policies, up to twenty documents, and turn the relevant parts into specific monitors. Each alert can be traced back to the policy that asked for it.
A good fit if
You run several AI applications or connected systems and want one place watching security-relevant activity across all of them.
You do not have a single narrow concern, such as only API traffic or only data leakage, but want broad, ongoing visibility.
You want events like logins, configuration changes and unusual usage flagged and routed to your team as they happen.
You want a weekly summary report alongside real-time alerts, so slower-building trends are visible too.
Not the right fit if
Your priority is API traffic specifically, such as abuse and unauthorized access on your endpoints; see AI API Security Monitor, which is narrower.
Your priority is sensitive data appearing in outputs or logs specifically; see AI Data Leakage Monitor, for content-focused watching.
You want a one-time report rather than ongoing monitoring; see AI Security Audit, for a point-in-time review.
You want this combined with guardrails and injection screening for your agents specifically; see AI Agent Security Layer, our broadest option.
How it works
- We connect to the systems you name. Typically cloud provider logs, your AI applications, and other connected systems in scope, so events from each land in one place rather than staying siloed.
- Security-relevant event types are defined with you. Logins, configuration changes, error spikes and unusual usage patterns across the systems in scope, agreed during setup rather than assumed generically.
- Events are centralized and watched continuously. Rather than checking each system's own logs separately, activity across your whole named footprint is visible from one place, watched around the clock.
- Rules and thresholds flag what is worth attention. Not every login or config change is equally significant, and the monitor is tuned to your systems so the alerts that reach you are the ones that matter.
- Alerts route to Slack or Jira with severity attached. Whoever owns security response sees the flag with enough context to act, rather than a raw event stream to sift through manually.
- A weekly summary report rounds things out. Alongside real-time alerts, you get a written overview of what the monitor saw, useful for spotting a pattern that no single alert would show on its own.
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.
- Written authorization confirming which systems we may monitor.
- The list of AI applications and systems you want in scope.
- The kinds of events you consider security-relevant, even in rough form.
- Read access to cloud provider logs and the systems in scope, as needed.
- A named IT or security owner who can respond to alerts after launch.
- 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 can approve the alerting thresholds and sign off the launch.
The 72-hour rule. Send everything on your checklist, including access, within 72 hours of ordering so your build starts on time.
Timeline
Start
Systems, event types and scope confirmed.
Weeks 1–2
Monitoring built and thresholds tuned to your systems.
Week 3
Log, system and alerting connections completed.
Weeks 3–4
Documented test scenarios run and results sent to you.
Week 4
Your review and two rounds of changes to the thresholds.
Go-live
Live, recorded handoff session, 30 days of support begin.
| Option | Delivery time | Price |
|---|---|---|
| Standard | 20–30 working days | $5,400 |
| Express | 15–25 working days | $6,200 |
| Rush | 10–20 working days | $7,000 |
What you receive at handover
- AI Security Monitoring configured and deployed in your environment, watching up to three AI systems
- Up to five monitors built from your policies, with workflow, prompt and guardrail configuration
- Connections to the agreed systems and one admin console or written report for reviewing events
- 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 shorten the gap between a security event and someone noticing it.
- Makes it easier to review AI security in one place rather than tool by tool.
- Helps you show auditors and clients that monitoring is in place and working.
- Time to notice an event
- For each alert, compare when the event happened with when someone acknowledged it. Track the figure month by month in the console.
- Alerts reviewed on time
- Count alerts raised each month and how many were reviewed within the window you set. Use the console history.
- Alerts closed as not relevant
- Count them each month after launch. Watch whether tuning during support brings the number down.
Before you start: Note where AI security events are logged today and how often anyone checks them. Record any incidents from the last quarter and how they came to light.
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 monitor costs roughly $20 to $300 a month in your own accounts, for hosting, logging and the monitoring tools it relies on day to day.
AI model usage during the build and testing is billed the same way, directly to your accounts, so you keep ownership of every provider relationship involved.
Ask about running costsCustom requirements
If you need something outside the Scope Card, such as monitoring across more than three systems, add a note at checkout. You get a written Change Quote, and that work only starts once you accept it. Larger or bespoke projects go through the Custom AI request form instead.
Request a custom versionKeep it running
Monthly maintenance covers monitoring and change hours for work such as adding an event type or adjusting thresholds. It starts after the 30 days of included support and can be cancelled any month.
$270/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 security monitoring platform charges per log volume, monthly | A security firm quotes after a scoping call | Ours is one fixed price, shown on this page before you buy |
| Scope | A security monitoring platform ingests everything and leaves tuning to you | An agency agrees scope during the engagement | Ours is tuned to your named systems and event types |
| Delivery | A security monitoring platform still needs weeks of rule tuning | A security firm engagement often takes weeks to schedule | Ours has a fixed delivery time shown before you buy, with faster options |
| Routing | A security monitoring platform sends alerts to its own dashboard | An agency delivers reports on its own schedule | Ours posts alerts to your Slack or Jira as they happen |
| Guarantee | A security monitoring platform may market a detection rate figure | An agency build depends on what was agreed | Ours flags what is worth attention; no monitor catches everything |
Questions about this product
What makes AI Security Monitoring different from a narrower monitor like AI API Security Monitor?
AI Security Monitoring watches broadly across the AI systems you name, covering logins, configuration changes, error spikes and general unusual usage. AI API Security Monitor and AI Data Leakage Monitor are narrower, focused specifically on API traffic or on sensitive data exposure. This one is the general-purpose, always-on option.
Do I need AI Security Monitoring if I already have AI API Security Monitor?
It depends on what you are watching for. If API traffic and data leakage are your only concerns, the narrower monitors may already cover you well. If you also want logins, configuration changes and general system activity watched together in one place, AI Security Monitoring adds that broader coverage on top.
How much does AI Security Monitoring cost to run each month?
Running costs land in your own accounts: roughly $20 to $300 a month for hosting, logging and the monitoring tools that store events and alerts. More systems and more activity push the figure toward the top of that range. We take no per-event fee. The one-time build price, with each faster delivery option, is in the price panel on this page.
What kinds of events does AI Security Monitoring actually watch for?
The event types are agreed with you during setup, commonly logins, configuration changes, error spikes and unusual usage patterns across the systems in scope. There is no fixed generic list; what counts as worth watching depends on how your particular systems are normally used day to day. We would rather tune the list to your reality than ship a list that does not fit.
What happens when AI Security Monitoring flags an event?
An alert with severity and context routes to Slack or Jira, and a named person on your team investigates and decides what to do next. The monitor does not take automated action on your systems; it is built to surface what is worth a human's attention, not replace their judgment.
Can I add more systems to the monitoring later?
Yes. Within the three systems included in scope, adding coverage is part of the build. Watching more systems than that comes through a Change Quote, priced and agreed with you before any work starts. Tuning thresholds or event types on systems already connected usually fits inside the monthly change hours that come with maintenance, so coverage keeps pace with your AI footprint.
Who owns the monitoring configuration and alert history once it is live?
You do. The thresholds, the event definitions and the alert history all live in your own connected accounts and tools, not a separate platform we control, so you retain full visibility and can adjust the setup without our involvement at all. We keep no separate copy that would lock you into working with us going forward.
Watch your whole AI footprint from one place.
Order AI Security Monitoring and it starts centralizing security events across your named systems, live on a fixed delivery date.
Works well with
Controls & Monitoring
AI Security Policy System
Maintains security policies and checks systems against them.
Controls & Monitoring
AI Agent Permission System
Defines and enforces what each AI agent may access and do.