One system holds the whole program.
Controls, policies, evidence, monitoring, risk and vendors in one place, mapped across every framework you're carrying.
Control Engine
The system underneath the capabilities below.
The Control Engine keeps your controls mapped and current. Agents draft, collect, and map policies, evidence, and controls, then monitor them continuously. A named Compliance Lead is accountable for the program; you approve the decisions.

Control mapping
One control satisfies its requirement in every framework it appears in.
Evidence collection
Integrations pull evidence on a schedule; gaps are flagged, not discovered at audit.

Policy engine
A full policy set drafted against how you actually operate, versioned, with the approval record attached.

Continuous monitoring
Control drift, failed checks and expiring evidence, surfaced when they happen.
Screenshot pendingRisk and vendor registers
Risk and vendor registers
The two artefacts every auditor asks for, maintained rather than reconstructed.
Screenshot pendingAudit workspace
Audit workspace
The evidence pack your auditor needs, assembled as you go.
AI drafts, collects, maps and monitors. It doesn't decide. Every output is a draft for review, and nothing is filed on your behalf.
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India data residency
Mumbai by default
No training on your data
Customer content excluded
DPA on request
DPDP Act 2023 compliant
Compliance management
Frameworks, controls, owners, and status in one place.
Evidence automation
Requests, reminders, labels, and an audit trail.
Risk management
Registers, scoring, and treatment tied to controls.
Policy management
Draft, review, publish, and map policies to controls.
AI governance
Inventory and controls for models you build or buy.
Also related
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- DPDP Act 2023
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