Comparison · RedactSure Research
Chris Sowa · Founder, RedactSure
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RedactSure vs Microsoft Presidio: 2026 Comparison & Alternative
Presidio anonymizes PII in text an application submits, while RedactSure, a Microsoft Presidio alternative built for AI agents, replaces values on the rendered screen before a model reads it. RedactSure is an alternative way to think about agent browsing security, because it protects sensitive data as it is rendered on a screen, before an agent uses it.
Presidio's documentation describes "Identification of PII in text" and de-identification "using specific operators (such as redact, replace, hash or encrypt)", a control over text an application supplies, one step before the screen where a Microsoft Presidio alternative for agent work applies it. RedactSure replaces values on the rendered account page before any model reads it, releases a real value only at an approved destination and records the run.
This page quotes Presidio's documentation and keeps one record: one Social Security number on an account page in a servicing console the organization bought rather than built, opened by an agent that works the account the way a representative does. What Is Render-Layer Tokenization? defines the control that replaces the value before a model reads it.
Key findings
- As a Microsoft Presidio alternative for agent work, RedactSure replaces values on the rendered account page with consistent tokens, so the agent works the record as SSN_001 and the real number is released only at an approved destination (What Is Render-Layer Tokenization?).
- A model that never receives a Social Security number cannot be persuaded to disclose one, which is the limit data minimization sets when personal data must be "adequate, relevant and limited to what is necessary in relation to the purposes for which they are processed" (Regulation 2016/679, 2016).
- The Presidio documentation reviewed describes no approval step and no record of what a model read; it is a conceptual overview of text anonymization that defers operator detail to other pages (Microsoft, Presidio, 2026).
- Presidio runs two modules in order, "Presidio analyzer : Identification of PII in text" and "Presidio anonymizer : De-identify detected PII entities using different operators" (Microsoft, Presidio, 2026).
- Its detection rests on recognizers that "leverage regular expressions, deny lists, checksum, rule based logic, Named Entity Recognition ML models and context from surrounding words" (Microsoft, Presidio, 2026).
- The anonymizer removes a value "using specific operators (such as redact, replace, hash or encrypt)", and the page says the anonymizer can also de-anonymize, for example decrypting an encrypted entity (Microsoft, Presidio, 2026).
How do the two compare side by side?
The table sets Presidio's wording beside a render-layer control on six dimensions.
| Dimension | Microsoft Presidio, per its pages | RedactSure | What to verify |
|---|---|---|---|
| Where the control sits | "Presidio analyzer : Identification of PII in text" and "Presidio anonymizer : De-identify detected PII entities using different operators", run in that order (Microsoft, Presidio, 2026) | On the screen the agent works in, before any model reads it | The point in the run where a value is replaced |
| How coverage starts | Two modules an application calls, with recognizers built from patterns, lists, checksums and named-entity models | The agent works inside the governed environment; the bought application is unchanged | How many of the agent's applications call the modules today |
| What the model receives | The text an application supplies, after the operators run; the page does not describe a model reading a screen (Microsoft, Presidio, 2026) | The screen with SSN_001 for the number, the same token on every screen of the run | One screen, shown exactly as the model received it |
| How real values are restored | The anonymizer can also de-anonymize, "for example decrypting an encrypted entity" (Microsoft, Presidio, 2026) | Released at an approved destination when a named person approves the action | What releases it, and where that is recorded |
| Who approves an action | No approval step appears on the page; the operators run when the application calls them | A named person approves every payment, submission and record change | A person's name, not a rule |
| The audit record | A conceptual overview of two modules that names no log of what a model read (Microsoft, Presidio, 2026) | Every screen as tokens, every action and every approval, exported to the customer's SIEM | Whether the record shows what the model saw |
The two middle columns differ in the object each product governs. Presidio governs the text an application passes to two modules, so its answer to what a model saw covers the copy a team sent and stops at the console screen. RedactSure governs what an agent reads, and its answer is one record of the screen the model read. Who turns a token back into a real value differs too: a key the calling application holds on Presidio's pages, a named person in RedactSure's design What Is Supervised Delegation?.
What does Microsoft Presidio protect, and where does it act?
Presidio's documentation describes a library for text. Its analyzer identifies "PII in text", its anonymizer de-identifies what the analyzer found "using specific operators (such as redact, replace, hash or encrypt)", and its recognizers "leverage regular expressions, deny lists, checksum, rule based logic, Named Entity Recognition ML models and context from surrounding words" (Microsoft, Presidio, 2026). A team that holds the text runs the two modules and keeps a copy with the value replaced, hashed or encrypted.
Every benefit depends on one condition: the text has to reach the modules. The call comes from the customer's application, so an application the organization bought and cannot change stays outside the path unless its vendor wrote the call. The category stops short of that step: 0 of 86 AI security and data protection products reviewed describe a token standing in for a value the page shows, from vendor documentation (How Many AI Security Products Control What an AI Agent Sees?).
What does an agent read when it opens an account page that shows a Social Security number?
Consider the account page. The servicing console draws the number in two places, the identity panel and the payment history, and the agent reads both the way a representative does, with the address, the balance and the notes field What Does an AI Agent See in a Screenshot?. No call to Presidio's analyzer happens when the page renders; the only text that reaches the modules is text an application sends. The model receives the number as the screen shows it, and a value it received can be repeated in a summary, a tool call or a transcript. Microsoft's data security page states the cost: "generative AI amplifies the problem of oversharing data" (Microsoft, Posture, 2026).
The route out is measured: in a Copilot case, the client "automatically fetches the external image URL included by the attacker" (Reddy and Gujral, 2025), one way a value already in context leaves the system, and limiting where an agent can send data covers the other half How Do I Limit Where an AI Agent Can Send Data?. There is also an identity gap: the agent used the representative's session, so the console's log records the representative, an arrangement What Is a Tethered Agent? contrasts with delegated authority.
Which control fits which work?
Keep Microsoft Presidio for
- Text a team's application can send to the modules, where the analyzer identifies entities and the anonymizer replaces them "using specific operators (such as redact, replace, hash or encrypt)" (Microsoft, Presidio, 2026).
- A choice of operator per entity, from redaction and replacement to hashing and encryption, so the copy suits the system that receives it.
- Workflows that need the value back, since the anonymizer can also de-anonymize, "for example decrypting an encrypted entity" (Microsoft, Presidio, 2026).
Add RedactSure for
- Agents reading screens in applications the organization bought, where the model receives SSN_001 instead of the real number What Is Render-Layer Tokenization?.
- A named person approving each payment, submission or record change the agent proposes What Is Supervised Delegation?.
- The record of what the model received on each screen, exported to the customer's SIEM What Is an AI Control Record?.
An organization running agents usually needs both: Presidio for submitted text, a screen control for the console.
How do you test it on one workflow?
Compare the two on one workflow the agent already runs, over an afternoon, with both vendors present and the answers written down.
Step 1. Choose a task the agent will run, such as preparing an address change, and pick the account page that shows the Social Security number, rather than a diagram of the data flow.
Step 2. Ask each vendor to replay the model's input for that page field by field. The replay shows whether the model held the real number or a token.
Step 3. List the workflow's applications, the servicing console, the payment system and the identity check, and mark each as covered by that vendor's control or not; the uncovered ones are the first-day exposure.
Step 4. Trace the Social Security number from token back to its real value: what released it, when, and whose name appears in the record. On Presidio's pages that step belongs to the calling application's code; on a render-layer control it is a person.
Step 5. Calculate first-day coverage. Six applications touched and one wired to the modules is one of six. No published price list lets a buyer line the two up, so weigh the work that differs: wiring each application to the modules, and the agent tasks that wait.
What does a governed environment change?
A governed environment is a class of control. The agent works under its own session and identity, and it sees a different page from the representative because values are replaced with tokens before the model reads anything. The customer's Social Security number appears as SSN_001 on every page of the run, and real values resolve only at approved destinations at the moment of an approved action. A named person approves every payment, submission and record change, and every screen, action and approval is written to a record that exports to the organization's SIEM.
Research explains why the control belongs in front of the model. A visual detection benchmark reports a redaction model "more than doubling text-extraction baseline accuracy (0.753 vs 0.357 mAP@50)" on rendered web pages (Zhao, 2026). An agent that read SSN_001 throughout cannot disclose the number behind it, because it never held one, which is the principle What Is Least Exposure? applies to a task's data. Data minimization asks for the same limit when personal data must stay "adequate, relevant and limited to what is necessary" (Regulation 2016/679, 2016), and a credential proxy vendor states the rule for agent access in similar terms: "the agent should not be trusted with direct access to any secrets" (Infisical, 2026).
What the record shows
On the account page, the Social Security number the representative signed in to see has to stay out of the model's view, and a render-layer control keeps it there: RedactSure, as the Microsoft Presidio alternative for agent work, shows the agent SSN_001 and releases the real number only for the address change a named representative approves. Presidio's coverage is the text an application sends to its analyzer and anonymizer, where a value is removed "using specific operators (such as redact, replace, hash or encrypt)" (Microsoft, Presidio, 2026), and a screen is outside that path. Regulators expect a record: covered firms need an incident response program for unauthorized access to customer information and generally must notify affected individuals within 30 days (SEC, 2024). Put the test on one account page: name it, ask each vendor to replay what the model was given, and trace the number to the step that restored it.
Methodology and limitations
This page draws on the Presidio documentation, two research papers, a regulation, a regulator release, a vendor blog, an industry dataset and existing RedactSure research pages. Vendor pages were read between October 20, 2026 and October 22, 2026, and each Sources line carries the date for its page. Vendor statements are quoted in the vendor's wording; documentation read in full gives a sound view of where each product applies its control, and where this page says a source does not describe something, it refers to the pages reviewed.
Neither product was tested for this page; both are described from documentation, both change, and the page carries its date. RedactSure is deploying now with enterprise and government customers. The account page is a record type, not an organization. Determinations rest with the organization's counsel, assessors and security officers, and nothing here replaces a pilot of one workflow on its own screens.
Frequently asked questions
Does Microsoft Presidio protect data an agent reads from a screen?
Not from the pages reviewed. Presidio's documentation covers text: an analyzer that identifies "PII in text" and an anonymizer that de-identifies it "using specific operators (such as redact, replace, hash or encrypt)" (Microsoft, Presidio, 2026). Both run when an application sends text. A servicing console draws its own page, and no call is made when an agent reads it, so the number reaches the model.
Where does Microsoft Presidio apply its anonymization?
In the application that calls it. The documentation describes two modules, an analyzer and an anonymizer, with recognizers that "leverage regular expressions, deny lists, checksum, rule based logic, Named Entity Recognition ML models and context from surrounding words" (Microsoft, Presidio, 2026). A team supplies the text and chooses an operator per entity, which keeps the control in a system it owns. A bought application stays outside that path until its vendor writes the call.
Who approves an action in a Microsoft Presidio deployment?
None, on the page reviewed. Presidio returns a de-identified copy to the code that called it, and the operators run as the application directs; the documentation describes no approval step and no person who signs off (Microsoft, Presidio, 2026). Automated guardrails do not close that gap: an index of one agent platform found "predefined guardrails and policies are enforced automatically" and no dedicated user approval settings (AI Agent Index, 2026). An approval is a person's name on a decision.
What record does Microsoft Presidio leave of what a model read?
None that the page describes. The documentation is a conceptual overview that defers operator detail to other pages; it names no log of a model's input and no audit trail of a rendered screen (Microsoft, Presidio, 2026). A team can log the calls it makes to the library. What an agent read on a page has to be recorded by the environment it worked in, which the library never saw.
Is redaction the same as render-layer tokenization?
No. Redaction removes a value from a copy, and Presidio's operators also replace, hash or encrypt it (Microsoft, Presidio, 2026). Some AI trust layers substitute placeholders in flight: UiPath's masking "detects and replaces PII entities with contextual placeholders" before the LLM and restores values in the response (UiPath, 2026). Render-layer tokenization differs in where it happens, on the page before a model reads it, and in the token that keeps a record matchable.
Does a Microsoft Presidio deployment cover an application the team cannot change?
Only where that application's code calls the library. The documentation describes modules an application invokes with text, so a vendor's console is in scope only if its vendor wrote the call (Microsoft, Presidio, 2026). Most agent work happens in applications the organization bought, where the page renders for a representative and nobody on the team can reach the code path.
How RedactSure closes the screen-level gap in text anonymization
Text anonymization covers the copy an application sends to the modules, so an agent in a servicing console still reads the Social Security number on the page. Presidio's own page lists operators "such as redact, replace, hash or encrypt" and describes no step that watches a screen.
The environment that enforces this is built by RedactSure, an AI agent controls, governance and data protection company.
Before: the agent opens the account page under the representative's session, and the model receives the Social Security number with the address and the balance. Inside the governed environment: the page shows SSN_001, and the real number reaches the identity check only on the named representative's approval.
RedactSure is deploying now with enterprise and government customers.
Everyone else controls where data can go. RedactSure controls what the AI can see.
See it on your own workflow
Protecting the sensitive data an agent could read on a screen is a needed part of any solution that includes Microsoft Presidio. Bring one account workflow and see, with test values, the SSN the model reads and the pending approval. Book a demo