A methodology-driven workbench for independent auditors to conduct, evidence, and report Digital Personal Data Protection audits under India's DPDP Act, 2023 and DPDP Rules, 2025. Evidence is SHA-256 hashed into an append-only ledger, and four report artifacts are generated from that one dataset, with no duplicate entry and no version drift.
The workbench never alters client systems. Every read is least-privilege, and every action an auditor takes is logged to the ledger with identity, timestamp, and rationale.
Client, audit period, significant data fiduciary status, and scope. The control-library version is stamped onto the engagement at the start.
Upload the client's exports. Each artifact is SHA-256 hashed, timestamped, attributed to the uploader, and locked into the evidence ledger.
The engine proposes Pass, Fail, Needs Review, or Not Applicable per control from the tagged evidence. Phased controls outside their in-force window are auto-marked Not Applicable.
The named auditor confirms, overrides with a required rationale, or marks Needs Review. The auditor's judgment always sits above the engine's proposal.
Narrative findings are drafted from failed controls with severity and an evidence reference, ready for the auditor to refine.
The lead auditor signs off per module or per engagement. Sign-off is cryptographically recorded against the ledger head and freezes that section.
Each entry hashes the previous entry's hash together with its own payload. Altering any historical entry breaks every hash that follows it. Anyone holding the export can recompute the chain to confirm the trail was never edited after sign-off.
Every report is a projection of the same engagement data, SHA-256 sealed and carrying a persistent verification reference back to the ledger.
Opinion-led, fixed structure, ready to hand to the client's board or regulator.
Control by control, drawn directly from the ledger, for the file a reviewer can trace.
Risk rollup and top findings, sized for a five-minute read.
Open the zero-install demo workbench in a browser, no server, no network, no client data leaves your machine.
Tamper-evident history, risk findings, and audit-ready reports for customer-facing AI.
Score accuracy, hallucination, and injection resistance, gated in CI.
Ranked exposure and predicted attack paths across your AI stack.
Trust scoring, verification, and the Trustra Verified badge.