Requests spanning multiple systems
Maps the request’s scope to the systems holding relevant personal data, giving reviewers a clear basis for assessing the extent of fulfilment.
— Risk & Compliance
Assesses a data subject access request end to end and returns a governed decision on whether to fulfil it, fulfil it in part, refuse it with reasons or extend the deadline, having verified identity, mapped the request to the systems that actually hold the data and held the outcome for a data protection sign-off before anything is disclosed.
1–2 hours → ~5 minutes
For one document, brief or record at a time
No coding required
— USE CASES
Maps the request’s scope to the systems holding relevant personal data, giving reviewers a clear basis for assessing the extent of fulfilment.
Sets out proposed redactions and applicable exemptions with cited grounds, supporting a reasoned recommendation for partial fulfilment or refusal.
Calculates the statutory deadline from the request details and applicable rules, and assesses whether an extension is justified.
Provides a documented decision assessment covering identity verification, scope and disclosure restrictions, with mandatory Data Protection Officer sign-off as a condition of release.
Data subject access requests create difficult judgements about identity, the information held across systems, disclosure limits and statutory deadlines. Requests spanning multiple systems is the typical trigger — maps the request’s scope to the systems holding relevant personal data, giving reviewers a clear basis for assessing the extent of fulfilment. Done properly it is defensible; done at pace it becomes a judgement call nobody can retrace. And "properly" usually means 1–2 hours of manual work.
As a Skill, the work is already sequenced. You bring the evidence, and the run produces reasoned recommendation to fulfil, partially fulfil, refuse or extend the deadline plus identity verification assessment. The judgement is built in — how items are broken up, what standard they are held to, and where the run stops for a human review. Net effect: 1–2 hours down to ~5 minutes, no drift between runs, and every conclusion traceable back to the evidence behind it.
Data Subject Access Request (DSAR) Engine exports as a structured SKILL.md file and is MCP-ready, so the same method runs in ChatGPT, Claude, Copilot or your own AI products. Adapt it to your methodology, and the intelligence stays yours — not locked to one vendor.
Pairs a full evidence set against every audit assertion or PBC item to produce a coverage matrix, naming the assertions nothing supports and the documents supporting nothing.
Fans multiple audit or review reports into individual findings, deduplicates repeats, and sorts them by severity into one consolidated register with sources retained.
Extracts documented controls and framework requirements, then grades every requirement covered, partial or absent for SOC 2 or ISO 27001 readiness.
Runs a scored risk and control self-assessment questionnaire and calculates residual risk identically every time, producing a register comparable across teams and quarters.
Researches a named regulation live, extracts every obligation with its clause reference, and maps each one against your own policies and controls to produce an obligation-level gap report with owners.
Reads every liability cap in a contract portfolio, derives actual exposure as a number, and aggregates it by entity, flagging uncapped contracts separately.