Comparison · RedactSure Research
Chris Sowa · Founder, RedactSure
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RedactSure vs Basis Theory: 2026 Comparison & Alternative
Basis Theory vaults payment data and issues agents scoped tokens, while RedactSure, a Basis Theory alternative built for AI agents, tokenizes the 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.
The buyer who starts with a Basis Theory alternative usually has one screen in mind: a customer payment record in a subscription billing console the organization bought, where the card on file is read by an agent. Basis Theory holds card data in its vault and gives applications and agents tokens or a single purchase credential. RedactSure replaces the values on the rendered page before any model reads it, so the model works with CUST_001 and CARD_4092.
This page quotes Basis Theory's own documentation and works through one record type: the payment record a billing specialist would open, holding a customer name, the last four digits of a card, a billing address and a payment history. Data Privacy Vault or Screen-Level Tokenization? sets out where a vault's reach ends.
Key findings
- As a Basis Theory alternative built for agent work, RedactSure replaces the values on a rendered screen with consistent tokens before any model reads it, so the agent works with CUST_001 and CARD_4092 and the real values resolve only at an approved destination (What Is Render-Layer Tokenization?).
- A model that never received the card digits cannot be persuaded to repeat them, and OWASP's disclosure entry records that "Personal identifiable information (PII) may be disclosed during interactions with the LLM" (OWASP, LLM02, 2025).
- None of Basis Theory's pages describes a control over the screen of an application the organization bought, where the record is drawn from the application's own database; its token and Elements pages cover values held as Basis Theory tokens (Basis Theory, What are Tokens, 2026).
- Basis Theory's token page defines the object it governs: "Tokens are a reference to the sensitive data that's stored in our system" (Basis Theory, What are Tokens, 2026).
- Its Agentic Payments guide puts one credential in front of an agent: a credential minted from a purchase allowance is "the only resource exposed to the agent, who has no access to the underlying payment method" (Basis Theory, Agentic Payments Overview, 2026).
- Elements collect and reveal sensitive fields without the application touching them: "Elements can securely display tokenized data to your users without your application accessing the plaintext values" (Basis Theory, Elements, 2026).
How do the two compare side by side?
The table sets Basis Theory's own wording beside what a governed environment does on the same point.
| Dimension | Basis Theory, per its pages | RedactSure | What to verify |
|---|---|---|---|
| Where the control sits | "Tokens are a reference to the sensitive data that's stored in our system" (Basis Theory, What are Tokens, 2026) | On the screen the agent works in, before any model reads it | The exact place a value is replaced |
| How coverage starts | "the raw card never reaches your servers" (Basis Theory, Agentic Payments Implementation, 2026) | The agent works inside the governed environment; the purchased application is unchanged | How many applications carry an integration today |
| What the model receives | "the agent receives only a minted credential" (Basis Theory, Agentic Payments Overview, 2026) | Tokens such as CUST_001 and CARD_4092, consistent for the whole run | One screen, shown as the model received it |
| How real values are restored | "Elements can securely display tokenized data to your users" (Basis Theory, Elements, 2026) | Released at an approved destination when a named person approves the action | Who authorizes the release, and where |
| Who approves an action | "An allowance defines the customer-approved constraints: merchant, amount, and expiration." (Basis Theory, Agentic Payments Overview, 2026) | A named person approves every payment, submission and record change | A person's name, not a policy line |
| The audit record | "All activities around tokens are audited" (Basis Theory, What are Tokens, 2026) | Every screen as tokens, every action and approval, in a control record exported to the customer's SIEM | Whether the record shows what the model saw |
Read the two middle columns together: each product governs a different object. Basis Theory governs the values a developer places in its vault and the tokens built on them; RedactSure governs what an agent reads, and its record is the screen as the model read it. They also differ on who turns a token back into a real value: a policy and an allowance on Basis Theory's pages, a named person in RedactSure's design.
What does Basis Theory protect, and where does it act?
Basis Theory's pages describe a payment vault. "You can store any primitive, complex, or unstructured data with our token type," the token page says, and its access controls "allow some systems access to highly confidential data while restricting access to only masked or redacted" (Basis Theory, What are Tokens, 2026). Its environment is independently verified for PCI DSS Level 1 (Basis Theory, Security, 2026). Agentic Payments gives an agent a credential "minted from the allowance for a single purchase" (Basis Theory, Agentic Payments Overview, 2026), and the agentic commerce page names a Browser Proxy for agents that "interact with any merchant website or API" (Basis Theory, Agentic Commerce, 2026).
Every benefit depends on a value that reached the vault. The agentic commerce page does not say what the Browser Proxy changes about the content of a page. What a rendered screen shows a model in a bought application is not described in the pages reviewed, and Can a Credential Vault Protect What an AI Agent Reads? traces the same boundary for vaults. Judged on public documentation, none of 86 AI security and data protection products describes reversible tokenization of what an agent reads on a screen, and the vaults in that set that tokenize reversibly do it inside pipelines a team integrates (How Many AI Security Products Control What an AI Agent Sees?).
What does an agent read when it opens a subscription billing console?
The record is a customer payment record in a subscription billing console the organization bought, which holds a customer name, the last four digits of a card, a billing address and a payment history. The agent works the console the way a billing specialist does, preparing a refund.
The card in the vault is protected, and the agent never goes there. The console draws the record from its own database, where no token sits, and displays the name, the address and the digits as the application writes them. The model receives every field the page renders, including the billing address and the account details the refund does not need. A computer-use agent "reads the rendered page as an image," and what enters its context is everything visible (What Does an AI Agent See in a Screenshot?).
The exposure sits in the model rather than in storage. The agent also borrowed the specialist's session, so the console's log records the specialist, and a record that separates the two exists only if the environment the agent worked in writes it (What Is an AI Control Record?).
Which control fits which work?
Keep Basis Theory for
- Card payments a team builds, where a proxy charges the card "while offloading PCI compliance scope with ease" (Basis Theory, Charge a Card, 2026).
- Agentic flows where "the raw card never reaches your servers," because Elements collect it into the vault (Basis Theory, Agentic Payments Implementation, 2026).
- Applications the team owns, where Elements can "securely display tokenized data to your users without your application accessing the plaintext values" (Basis Theory, Elements, 2026).
Add RedactSure for
- Agents reading screens in applications the organization bought, where the model receives CUST_001 and CARD_4092 instead of the real values (What Is Render-Layer Tokenization?).
- A named person who approves every payment, submission and record change the agent proposes (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?).
An organization running agents will usually want both: the vault for stored card data, a screen control for the console.
How do you test it on one workflow?
Run both vendors through one real workflow in an afternoon, with each present and the answers written down.
Step 1. Choose the customer payment record in the subscription billing console, a screen the agent will actually open, rather than a diagram of the data flow.
Step 2. Have each vendor show that screen as the model received it, with the output captured. The output itself shows whether the model saw the name and the card digits or tokens.
Step 3. List every application the workflow touches and mark each one as carrying a vault integration, an agentic credential flow, or neither. The third group is the exposure on the first day; write the list down and keep it, because the count is the number a pilot has to move.
Step 4. Trace one value, the last four digits or the billing address, from token back to its real value: what releases it, when, and whose name appears in the record.
Step 5. Calculate first-day coverage. If the task list touches six applications and one carries an integration, first-day coverage is one of six. Compare the two costs that differ: the instrumentation program, and the agent work delayed until it is finished, and read both against the coverage count before a scope is quoted.
What does a governed environment change?
A governed environment is a category of control rather than a product feature. The agent works under its own session, recorded under its own identity, and sees a different screen because values are replaced with consistent tokens before the model reads anything. The customer appears as CUST_001, with CARD_4092 and ADDR_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 that exports to the organization's SIEM.
The research explains why the control sits in front of the model. OWASP's injection entry records that "Indirect prompt injections occur when an LLM accepts input from external sources, such as websites or files," and its listed mitigation is to "Restrict the model's access privileges to the minimum necessary for its intended operations" (OWASP, LLM01, 2025). A model that only ever received CUST_001 cannot be coaxed into repeating a card number it never held, which is the principle in What Is Least Exposure?: the data an agent receives for a task stays at the minimum, and the screen is where that minimum is set.
What the record shows
The control that decides this exposure sits on the console screen, where the customer name, the last four digits of the card and the billing address become tokens before the model reads them, and that is the job RedactSure, as the Basis Theory alternative for agent work, does for this record. Basis Theory's real coverage is the data a developer placed in its vault and the tokens built on it, so its pages answer for those holdings and leave the screen of a bought application to the environment the agent works in. The test fits one workflow: name one agent and one payment task, ask each vendor to show the screen the model was given, then trace the last four digits back to the action that released them and the person who approved it.
Methodology and limitations
This page draws on seven Basis Theory documentation pages, two OWASP entries 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. Vendor statements are quoted in 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 a behavior, it means the pages reviewed for that product.
The products on this page are described from documentation; none was tested for this page, and no customer of either product is described. Documentation describes intended design, both products change, and the page carries its date. RedactSure is deploying now with enterprise and government customers. The payment record is an illustrative record type. Compliance determinations belong to the organization's counsel, assessors and security team, and nothing here replaces a pilot of one workflow on its own screens.
Frequently asked questions
Does Basis Theory protect the payment data an agent reads on a billing console?
No, not from the pages reviewed. Basis Theory's pages describe a vault that holds card data, tokens that reference it, Elements that collect and reveal fields, and an Agentic Payments flow that mints an agent a credential for one purchase. Each covers a value a developer or customer placed with Basis Theory. The console draws the record from its own database, so the model reads the name and digits directly.
Is a vaulted card the same as a tokenized screen?
No. A vault token is a reference to a value the vault holds: "Tokens are a reference to the sensitive data that's stored in our system" (Basis Theory, What are Tokens, 2026). A token on a rendered screen is a replacement made where the page is drawn, so the value never enters the output the model reads. The first is about storage, the second about display.
Who approves an agent's payment, a policy or a person?
A policy, on Basis Theory's pages. "An allowance defines the customer-approved constraints: merchant, amount, and expiration," and the agent receives a credential minted inside it (Basis Theory, Agentic Payments Overview, 2026). That is a decision written in advance for a purchase. In RedactSure's design a named person approves each payment, submission or record change, and the approval carries the person's name.
Will the billing console's logs show that an agent opened the record?
Not on their own. When an agent reads a screen, nothing passes through the vault, so the data platform has nothing to log, and the console logs the employee whose session was used. A record that separates the two has to come from the environment the agent worked in. RedactSure's AI Control Record provides that: every screen as tokens, every action and approval, exported to the SIEM.
Does Basis Theory's Browser Proxy change what an agent reads on a merchant page?
Not from the pages reviewed. The agentic commerce page names "a Browser Proxy and Proxy-as-a-Service for agents to interact with any merchant website or API," and says agents have "real-time, scoped access with complete permission control" (Basis Theory, Agentic Commerce, 2026). It does not say the proxy changes what a rendered page shows the agent, and a proxy that routes a request still returns the page the server sends.
What should a buyer ask both vendors in writing?
Ask each vendor to show one screen exactly as the model saw it, to name what releases a real value and whose name is in the record, and to say whether the record covers an application the organization bought. Ask where the values live and who can decrypt them. Treat an answer the documentation does not support as unanswered until a run with test values confirms it.
How RedactSure closes the screen-level gap in payment vaults
Basis Theory protects the card a developer places in its vault, while the billing console an agent reads draws the record from its own database. Its Agentic Payments guide gives the agent only a minted credential for one purchase, which covers a checkout and leaves the screen a specialist works untouched.
The environment that enforces this is built by RedactSure, an AI agent controls, governance and data protection company.
Before: the agent opens the console under the specialist's session, and the name, the last four digits, the address and the history all reach the model. Inside: the same screen shows CUST_001, CARD_4092 and ADDR_001, and real values reach the payment system only on the named specialist'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 Basis Theory. Bring one billing task and watch, with test values, what the model reads and who approves the payment. Book a demo