Comparison · RedactSure Research
Chris Sowa · Founder, RedactSure
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RedactSure vs DoControl: 2026 Comparison & Alternative
DoControl governs who and what reaches SaaS files and connected apps, while RedactSure, a DoControl alternative built for AI agents, replaces values on the rendered screen before any 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.
A service representative has a customer record open in the CRM and an agent is about to read it, so the DoControl alternative question is what the model receives from the page. DoControl governs who and what can reach SaaS files and connected apps. RedactSure, a DoControl alternative built for AI agents, replaces the values on the rendered screen before any model reads them.
This page follows one record: a customer record in a CRM the organization bought, holding a customer name, email address, phone number and account number, opened by an agent working the CRM as a representative does. The What Is Render-Layer Tokenization? page defines the substitution, and Runtime Tokenization vs DLP for AI Agents sets out why replacing a value differs from detecting one.
Key findings
- As a DoControl alternative for agent work, RedactSure replaces the values on the rendered CRM screen before any model reads it, so the agent works with CUST_001 and ACCT_001 and the real details stay out of the model (What Is Render-Layer Tokenization?).
- A control that changes the outcome replaces values with tokens before any model reads them and releases a real value only at an approved destination; OWASP records that "Personal identifiable information (PII) may be disclosed during interactions with the LLM" (OWASP, LLM02, 2025).
- No DoControl page describes a change to what a model reads on a rendered screen; the controls act on "SaaS application assets, users and third-party OAuth apps" instead (DoControl, SaaS Security Posture, 2026).
- Its governance page says a "machine learning-based classification model sets a sensitivity score for each data asset" (DoControl, Data Access Governance, 2026).
- Its DLP page states that DoControl "immediately quarantines or removes sensitive data shared in SaaS applications according to your SaaS security policies," which remedies shared data rather than what a screen shows (DoControl, SaaS Data Loss Prevention, 2026).
- The AI security post says the platform can "monitor and detect activity across SaaS platforms with the ability to differentiate between human and non-human actions," which covers agent activity without changing the screen (DoControl, AI Security Use Cases, 2026).
How do the two compare side by side?
The table sets DoControl's own wording beside what a governed environment does on the same point, and names the check a buyer can run.
| Dimension | DoControl, per its pages | RedactSure | What to verify |
|---|---|---|---|
| Where the control sits | DoControl "builds an inventory of all your SaaS application assets" (DoControl, SaaS Security Posture, 2026) | On the screen the agent works in, before any model reads it | Where a value is replaced |
| How coverage starts | "Discover all your SaaS data" over connected applications (DoControl, Data Access Governance, 2026) | The agent works inside the governed environment; the CRM is unchanged | How many are connected today |
| What the model receives | Not described; the platform "provides complete visibility, threat detection, and remediation" (DoControl, SaaS Security Posture, 2026) | The CRM screen with tokens, CUST_001 and ACCT_001, held for the whole run | The model's input for one screen, field by field |
| How real values are restored | No detokenization: DoControl can "remove permissions on-demand from hundreds of thousands of assets" (DoControl, Data Access Governance, 2026) | Released at an approved destination when a named person approves the action | Who releases it, and where |
| Who approves an action | A policy: a user who violates one is "immediately notified and guided to remediate the issue" (DoControl, Insider Risk Management, 2026) | A named person approves every payment, submission and record change | A person's name, not a rule |
| The audit record | "Monitors SaaS activity streams for anomalies" (DoControl, Rewriting SaaS Security, 2026) | Every screen as tokens, every action and approval, exported to the customer's SIEM | Whether the model's reading is recorded |
The difference is the object each product governs. DoControl governs the SaaS asset and the access around it, so its answer covers what connectors reach. RedactSure governs what an agent reads, and its answer is one record of the screen. They also differ on who releases a value: a policy there, a named person in the governed design (What Is Supervised Delegation?).
What does DoControl protect, and where does it act?
The overview says the platform provides "complete visibility, threat detection, and remediation for sensitive data exposure and insider threats, across all your major SaaS ecosystems," with NLP scanning for "PII, PHI, PCI, secrets, and credentials" (DoControl, SaaS Security Posture, 2026). The insider risk page says DoControl "enriches threat detection with business context, integrating metadata from your Identity Provider (IdP), HRIS, and EDR systems," and that "If a user violates a policy, they are immediately notified and guided to remediate the issue" (DoControl, Insider Risk Management, 2026).
For AI, the platform will "Govern AI connectors and prevent sensitive data leaks to untrusted models" (DoControl, Rewriting SaaS Security, 2026). On September 8, 2026 it announced that "DoControl has been acquired by Spin.AI" and that "DoControl remains DoControl" (DoControl, Joins Spin.AI, 2026).
Every benefit depends on one condition: the application is connected, so the platform can inventory assets and apply policy to sharing. Those connectors carry records and events, not the pixels a screen displays, so a control over what a model reads on a rendered page is outside what the pages reviewed describe, the distinction What alternatives to traditional DLP reduce false positives? draws.
What does an agent read when it opens a customer record?
Consider the customer record. The agent opens it the way a service representative does, and the model receives the page as rendered: the customer name, email address, phone number and account number, plus the fields the task never needed, the surface What Does an AI Agent See in a Screenshot? describes.
The CRM was bought rather than built, and DoControl's connectors carry the assets and activity its APIs expose, not the pixels the model reads (DoControl, SaaS Security Posture, 2026). The exposure sits in the model: OWASP states that "Personal identifiable information (PII) may be disclosed during interactions with the LLM," and a study of task-executing agents found that injections asking them to leak personal data observed during a task reached "average attack success rates (ASR) around 20 percent" (OWASP, LLM02, 2025; Alizadeh et al., 2025). There is an identity gap too: if the agent works under the representative's session, the CRM logs the representative, and nothing separates the agent's reads from the person's work, the question What Is Least Exposure? puts to a team. The DLP and insider risk category DoControl belongs to holds 13 products in the review of 86, and 7 describe recording prompts or payloads while 7 describe a SIEM export of AI activity, against 36 and 33 across the whole set (How Many AI Security Products Control What an AI Agent Sees?).
Which control fits which work?
Keep DoControl for
- Inventory and sensitivity scoring, where a model "maps the level of exposure for internal, public and external sharing" (DoControl, Data Access Governance, 2026).
- Bulk permission removal: DoControl can "remove permissions on-demand from hundreds of thousands of assets" (DoControl, Data Access Governance, 2026).
- Insider-risk review that brings IdP, HRIS and EDR context to an alert and asks the employee to fix their sharing (DoControl, Insider Risk Management, 2026).
Add RedactSure for
- Agents working the CRM screen in a bought application, where the model reads CUST_001 in place of the customer's name (What Is Render-Layer Tokenization?).
- A named person who signs off on every payment, submission and record change before it lands (What Is Supervised Delegation?).
- The record of what the model received on every screen, exported to the customer's SIEM (What Is an AI Control Record?).
Most organizations running agents on bought applications need both; this block shows which protects the screen.
How do you test it on one workflow?
Compare the two on one real workflow, over an afternoon, with both vendors present and answers written down.
Step 1. Choose a task the agent will run in the CRM, such as updating an account address, and pick the customer record screen it opens.
Step 2. Ask each vendor to replay, field by field, what the model was given when it opened that screen. If the phone number and account number are legible there, the model read them, whatever the platform reported afterward.
Step 3. List the workflow's applications and mark each as inside DoControl's inventory, covered by a DLP policy, or neither. The last group is the first-day exposure; count it yourself.
Step 4. Trace one value, the account number, back to the real value: what released it, at which destination, and whose name is in the record. An alert is a policy event, not an approval.
Step 5. Calculate first-day coverage. If the task touches five applications and two are connected, first-day coverage is two of five. Compare connector work with the agent work that waits, and put both numbers beside the first-day count before either vendor quotes a scope.
The comparison is decided by what each vendor shows for the rendered page, not by the connector count.
What does a governed environment change?
A governed environment is a control class, not a product feature. The agent works under its own session and identity, and it sees a different screen because values are replaced with consistent tokens before the model reads anything. The customer appears as CUST_001, with EMAIL_001, TEL_001 and ACCT_001, on every screen. 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 control record exported to the SIEM.
Research explains why the control sits in front of the model. OWASP lists excessive functionality, excessive permissions and excessive autonomy as root causes of an excessive-agency failure, so limiting what an agent can do does not limit what it already read (OWASP, LLM06, 2025). The same guidance records that personal data "may be disclosed during interactions with the LLM," which is why the exchange with the model matters (OWASP, LLM02, 2025). A model that received CUST_001 cannot be coerced into sending the customer's name, which is the principle What Is Least Exposure? applies to a screen.
What the record shows
The customer record in the CRM decides this comparison: the agent opens it as a representative does, and the model receives the name, email address, phone number and account number unless something replaces them before it reads the page. RedactSure, the DoControl alternative for agent work, does that on the rendered page, holding CUST_001, EMAIL_001, TEL_001 and ACCT_001 for the run and releasing the real account number only for an approved update. DoControl's coverage, from its pages, is the SaaS asset and the access around it, with remediation on data shared inside a connected application. Open one record in both tools, note the four fields the task needs, and run the check as a test: the screen each shows for those fields against what the CRM logged.
Methodology and limitations
This page rests on seven DoControl pages and posts, two OWASP entries, one preprint and existing RedactSure research pages. Sources were read between October 21, 2026 and October 23, 2026, and each Sources entry carries the date its page was read. Quotations keep the vendor's own wording, and public documentation read in full gives a sound view of where each product applies its control; where this page says a source does not describe something, it refers to the pages reviewed.
The products are described from documentation; neither was tested for this page, no customer of either is described, both change, and the page carries its date. RedactSure is deploying now with enterprise and government customers. The record is an illustrative type, not an organization. Determinations rest with the organization's counsel and assessors, and nothing replaces a pilot of one workflow on the organization's own screens.
Frequently asked questions
Does DoControl protect what an agent reads on a rendered screen?
Not from the pages reviewed. DoControl's pages describe a platform that inventories SaaS assets and removes permissions in bulk. None of that changes the page an agent receives: the CRM still shows the customer name, email address, phone number and account number as it always did. A control that changes what the model reads has to sit between the rendered page and the model, the place these pages leave unnamed.
Who approves the agent's action, a policy or a person?
A policy, on DoControl's pages. Its insider risk page says that when "a user violates a policy, they are immediately notified and guided to remediate the issue," so the response is written in advance. That reviews sharing after it happens; it does not put a person's name on the specific record change an agent proposes. The approval worth asking for names the person and the action.
What record exists of what the agent's model received?
An activity record, not a screen record. DoControl "monitors SaaS activity streams for anomalies" and can "differentiate between human and non-human actions," so its evidence is behavior in connected systems. If the agent used the representative's session, the CRM logs the representative, and the model's reading appears nowhere. The record that answers that question has to be written by the environment the agent ran in, not by the CRM.
Does DoControl stop an agent from reading a bought CRM's record?
Only on the paths its connectors reach. DoControl builds its inventory from connected SaaS applications and acts on their assets and permissions, so a bought CRM is inside its governance. What it governs there is access to the record, not the values on the record. An agent signed in with that access reads every field the page displays.
Is DoControl only a data loss prevention product?
No. Its pages describe four jobs, asset inventory, data access governance, insider risk and DLP, plus governance of AI connectors and shadow AI applications. The platform is broader than its DLP use case. The four jobs share the same control point, the SaaS environment and the identity connected to it, none of which is the page a model reads.
Does the Spin.AI acquisition change what DoControl protects?
Not by the company's own account. It says "DoControl remains DoControl," with no change to the product, contracts or support. Spin.AI names "enterprise browser security" as a capability, which the pages reviewed do not describe reaching a rendered screen. The acquisition adds a capability to the portfolio, not a control to the page. The documented control, on SaaS assets, permissions and connected apps, is unchanged.
How RedactSure closes the screen-level gap in SaaS access control
DoControl governs the asset, the permission and the connected app, while the model still reads the account number. Injections that ask agents to leak personal data seen during a task reached attack success rates around 20 percent.
The environment that enforces this is built by RedactSure, an AI agent controls, governance and data protection company.
Before: the agent opens the customer record under the representative's session, the screen shows the four fields, and the model receives all of them. Inside the governed environment: the same record shows CUST_001, EMAIL_001, TEL_001 and ACCT_001, and the real values reach the CRM only when the named representative approves the update.
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 DoControl. Bring one CRM workflow and see, with test values, what the model reads and the approval the before-and-after names. Book a demo