The pipeline pulls from your cloud, identity, code and ticketing systems as things happen
AI is monitoring your controls while you do the work.
Anecdotes’ data pipeline reflects your processes as they run: evidence, tests and findings, without a stakeholder in the loop, kept ready for your agents.
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A 30-minute walkthrough on the systems and frameworks you actually run. No slides.
Every control, continuously.
Every framework, mapped once.
Every answer, from data your systems already produce.
What continuous control monitoring changes.
Controls are tested all year round, not in the weeks before an audit
Findings reach their owner the day they appear, with no one chasing screenshots
Built for the GRC team, and for the agents they run.
Anecdotes turns your compliance program into data: the controls, the evidence behind each one, the risks they cover, the policies they come from, the vendors they depend on. Structured, current, and open to your own AI agents.
Teams come to Anecdotes when:
- controls are checked by hand, between audits
- evidence is still screenshots and spreadsheets
- a second or third framework is on the roadmap
- their AI agents need compliance data they can trust
Questions GRC teams ask about continuous control monitoring
What is continuous control monitoring?
Continuous control monitoring (CCM) tests your security and compliance controls automatically and all the time, from the data your systems already produce, instead of sampling them by hand before an audit. Anecdotes collects that data from your cloud, identity, code and ticketing systems as things happen, so evidence, tests and findings stay current. Agentic continuous control monitoring →
How is continuous control monitoring different from a periodic audit?
A periodic audit looks at a sample of evidence at one point in time. Continuous monitoring tests every control all year round, so a failing control shows up the day it fails and its owner can fix it long before the next audit window. Real-time visibility →
What is agentic continuous control monitoring?
Traditional CCM stops at detection. In Anecdotes' agentic CCM, AI agents also notify the right stakeholders, manage remediation of the gap, and verify that the fix holds, so a finding is closed rather than only reported. How agentic CCM works →
Which systems does Anecdotes connect to?
Anecdotes has 230+ pre-built integrations, including AWS, Azure, Okta, GitHub and Jira. Its data engine collects, normalizes and structures evidence from those systems into one audit-grade data layer. The plugin library →
Which compliance frameworks does Anecdotes support?
60+ frameworks come pre-mapped, including ISO 27001, HIPAA and PCI DSS, and you can add custom frameworks. Cross-mapping lets you collect evidence once and reuse it for every framework you run. The framework library →
Can our own AI agents use Anecdotes' compliance data?
Yes. Anecdotes turns your compliance program into structured, current data, and its MCP server connects AI assistants such as Claude and ChatGPT to your controls, evidence and risks. The Anecdotes MCP server →
How can I see Anecdotes on my own stack?
Book a 30-minute walkthrough on the systems and frameworks you actually run. No slides. Book a demo →
Go deeper on anecdotes.ai
- Agentic continuous control monitoringDetection, notification, remediation and verification, end to end.
- What is agentic GRC?AI agents that run complete GRC workflows, with experts in oversight.
- The GRC data engineAudit-grade data from 230+ systems, normalized into one context.
- 60+ frameworks, fully mappedISO 27001, HIPAA, PCI DSS and more, adopted in a click.
- Multi-framework complianceCollect once, reuse continuously across frameworks.
- Model Context Protocol for GRCBring your compliance data into the AI tools you already use.
- Watch the platform demoAI agents running evidence collection and control monitoring.
- Anecdotes Trust CenterHow Anecdotes secures its own platform and your data.
Ready when you are