In your browser
File extraction for all 11 file types, OCR of scanned pages, the review workspace, burned-in PDF redaction, and assembly of the export ZIP. Working state is checkpointed locally so a long case survives a closed tab.
Trust Center
Every statement on this page is written in the words the data processing agreement uses and can be checked against the product. Documents are read and redacted in your browser and are never uploaded. Only extracted text is sent for detection, together with the details of the data subject entered for the case, and no document is stored on our servers.
your-browser/ stays on your machine documents read and redacted here redacted pack built and downloaded here working state checkpointed locally detection-service/ text and subject details standard route deleted within 30 days UK and EU route not stored or logged our-servers/ no document content account data case audit metadata counts, timings, route
Extraction, OCR, review, redaction and export all run in the browser tab. The detection service receives extracted text, with the details of the data subject entered for the case, and returns detections. Apart from the account, usage and security records described below, nothing else leaves the machine.
File extraction for all 11 file types, OCR of scanned pages, the review workspace, burned-in PDF redaction, and assembly of the export ZIP. Working state is checkpointed locally so a long case survives a closed tab.
Receives extracted text in sections and returns detections. Two layers: pattern matching for structured identifiers and an AI layer for names and personal details in prose. Neither layer redacts anything on its own.
Authentication, organization settings, entitlements, security logs and case audit metadata (file and character counts, timings, the processing route). They hold no document content, extracted text or redacted output.
| Data | Where it goes | How long it is kept |
|---|---|---|
| Documents | Never uploaded. Read and redacted in the browser. | Not held by SafeRedact at any point. |
| Extracted text | Sent to the detection service on the route fixed for your organization. | Standard route: never used for training and deleted within 30 days under our commercial terms. EU route: not stored or logged by the AI provider. |
| Data subject details | Sent with the extracted text so that the subject’s own information is not redacted. Subject records saved for reuse stay in the browser. | Not stored by SafeRedact. Held by the AI provider on the same terms as the extracted text. |
| Redacted output | Built in the browser and downloaded by the reviewer. | Not held by SafeRedact at any point. |
| Case audit metadata | Our database (Supabase). Per-file character and byte counts, a one-way fingerprint of the extracted text, timings, route, attestation events. No file names, no content. | For the life of the account, as the customer's own processing record. Deleted within 30 days of termination or written request. |
| Account data | Our database (Supabase). Name, email, organization, roles, agreements, and a security log of sign-ins with IP address and browser user agent. | For the life of the account. Deleted within 30 days of termination or written request, except billing records, which are kept as the law requires. |
| Staff notifications | Sent to SafeRedact staff by Slack and by email: account events with the user’s email address and file counts, and feedback sent from the application. No content. | Kept by Slack and by Resend under their standard retention. |
| Emails to users | Sent through Resend: sign-in links, agreement copies, receipts and case notices. | Copies kept by Resend under its standard retention. |
| Help assistant questions | Where the assistant is enabled for an organization, answered by Anthropic. | SafeRedact records that a question was asked, not its text. |
The route is fixed per organization before a case begins and cannot be changed from inside a case. Every change is recorded in an audit trail.
Detection runs on Anthropic Claude. Text is never used for training and is deleted within 30 days under our commercial terms. Anthropic stores API data in the United States and may process requests there or in selected countries in Europe, Asia and Australia.
Detection runs on AWS infrastructure within the UK and EU (European regions including London). Text is not stored or logged by the AI provider. Extracted text is not transferred to the United States on this route.
What the model sees. Extracted text, in sections, with the data subject's identifiers so that they can be preserved. It does not see the original file, the file name, or who is reviewing.
What the model does. Proposes detections with a type and a confidence. It does not redact, does not decide, and does not learn from your text: on the standard route it is never used for training, on the EU route it is not stored or logged.
What a person does. Every detection is accepted, rejected or added by a reviewer, by entity or by file. Export waits for the reviewer's attestation, and files with undecided detections are named before the pack is built. No automated decision reaches the disclosure pack.
What is recorded. audit-trail.csv, review-decision-log.csv, a detection report, a subject preservation summary and a processing failure manifest are written into every export, in the customer's hands, not ours.
| Provider | Purpose | Data |
|---|---|---|
| Anthropic | AI detection, standard route; help assistant where enabled | Extracted text and the case’s data subject details; help questions. Never used for training; deleted within 30 days. |
| Amazon Web Services | AI detection infrastructure, EU route, UK and EU regions | Extracted text and the case’s data subject details. Not stored or logged by the AI provider. |
| Vercel | Hosting and serverless compute | Request handling. Zero persistent storage of document content. |
| Supabase | Authentication and database | Account data and case audit metadata. No document content. |
| Stripe | Payment processing | Billing contact and payment records. |
| Resend | Email to users and to SafeRedact staff | User email addresses and the emails described above. |
| Slack | Notifications to SafeRedact staff | Account events with the user’s email address and file counts, and feedback. No document content. |
A data processing agreement is in place before the first case starts. Executed agreements are recorded against the organization with the document version, the executing signatory and a SHA-256 hash of the exact document signed, so the executed text can be produced later, unchanged. Current and previous versions are published at /enterprise/legal.
SafeRedact is not separately certified at this time. Each sub-processor above holds an independent SOC 2 Type II report; these are the providers’ own reports, not SafeRedact’s. The full list, with each provider’s certifications, is in the sub-processor schedule.
Every number on the SafeRedact home page is listed here with what it counts, where it comes from and what it does not claim. Figures are restated when they change; none of them is an estimate.
| Figure | What it counts | Source and limits |
|---|---|---|
| Characters of live DSARs processed to date | The total extracted text, in characters, from files processed for customer organizations answering real data subject requests. Internal accounts and test organizations are excluded. | Summed from the per-file processing record described under Data handling and retention. That record holds a case identifier, a file index, a user identifier, character and byte counts and a one-way fingerprint of the text, and no document content, so the figure can be totalled without reading anything anyone wrote. It is a running total and rises as cases run. It is not a page count and not a file count. |
| 2 GB per mailbox file, up to 25,000 messages | The largest mailbox export file the application will open, and the largest number of messages it will expand from one of them. | Both limits are enforced in the shipped extractor rather than advertised as guidance. A file above the size limit is refused with an explanation, and a warning appears from 1.5 GB. The 2 GB ceiling exists because the whole file is held in memory while it is expanded. Exports larger than this are handled by setting a smaller package size in Purview, which is covered in the export guide. |
| 933,000 AI detections in a single case | The number of detections found and carried through review in one case during scale testing of a 2,000-file corpus. | SafeRedact's own testing, not a customer case. The corpus was built with a deliberately high density of personal data, several times what a real mailbox contains, in order to find the ceiling. The figure covers detection, checkpointing and review. It is not a claim about export at that density on the hardware used for the test, and it is not an accuracy rate: no detection percentage is published anywhere. |
| 63 end-to-end checks, passed twice by every release | An automated suite that runs a case from sign-in through processing, review, attestation and export, then inspects the exported files. It checks that planted third-party identifiers are absent from every artifact, that the data subject's own details survive, that the attestation gate stops an export with undecided detections and records the reason given, that a reviewer's decision to keep a detection is honoured in the export and logged, that the black boxes on each rendered page, scanned pages included, cover the text they replace and nothing beside it, and that the server's own record of the case matches. | The suite runs in a real browser against the deployed build, and a release ships only after two consecutive clean runs. A separate set of regression tests runs on every change. Neither suite measures detection quality, which is why review by a person is mandatory before export. |
Figures are stated without a date because the first one is cumulative and changes. If you need a figure as at a particular day for a procurement file, ask and we will confirm it in writing.
Security or privacy concerns go to support@saferedact.app. Include the build stamp from the application header where relevant.
Set your organisation up, accept the data processing agreement and run one real case.