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Perspective · 6 minute read

Contracts are becoming interfaces for AI. What should cross the boundary?

Machine-readable contracts make better automation possible. They also make it easier for sensitive values to travel. The next interface legal teams need is a deliberate privacy boundary.

Common Paper describes contracts as interfaces between companies—and argues that turning their terms into structured data can bring legal work some of the clarity and leverage that APIs brought to software.

AI makes that argument more urgent. Once an agent can read, compare, summarize, and act on contracts, the document is no longer only a page to be signed. It becomes an input to a system.

Read “Turn Any Contract into an API” at Common Paper

The shift

From a signed artifact to a working interface.

A traditional contract workflow produces a file. A machine-readable workflow exposes parties, dates, obligations, renewal terms, payment amounts, and other values that software can use. That enables better search, reporting, drafting, and decision support.

When a contract becomes an input to AI, disclosure becomes part of the interface design.

An approved AI account answers one question: which system may be used? It does not answer a second, equally important question: which details does this particular task require the system to receive?

The missing boundary

Separate useful legal context from unnecessary identity.

Source

Confidential contract

Real parties, values, contacts, identifiers, and matter-specific terms.

Local boundary

Review what crosses

Detect, replace, add, and approve sensitive values in the browser.

Mapping stays here
Destination

Approved AI

The structure and relationships needed for the task, with reviewed tokens.

Confidential source

Northstar Medical must pay $475,000 to Calder Group within 30 days.

AI working copy

[[COMPANY_1]] must pay [[AMOUNT_1]] to [[COMPANY_2]] within 30 days.

The fictional example preserves who owes what and when. It does not claim that tokenization makes every document anonymous or every AI use appropriate.

Four design principles

A useful privacy layer behaves like infrastructure.

  1. 01

    Minimize before transmission

    Send the clauses and facts the task requires, not the entire source document by default.

  2. 02

    Make replacement deterministic

    Use stable, meaningful tokens so the same party or value keeps the same role throughout the text.

  3. 03

    Keep judgment visible

    Let a person confirm, ignore, recategorize, or add terms before anything leaves the local environment.

  4. 04

    Restore at the endpoint

    Keep the reversible mapping with the user and restore recognized values only when the response returns.

Where LegisComply fits

LegisComply does not turn the contract into an API.

It prepares a protected working copy before the contract reaches an AI. Detection, replacement, review, and restoration happen locally in the browser. The user decides what to replace and whether the resulting text is appropriate to share with the organization’s approved tool.

The original document does not need to be uploaded to LegisComply.

Meaningful tokens preserve roles and relationships for the AI task.

The user approves every replacement and can add confidential terms.

Authorization, professional judgment, and output verification remain with the user.

Prepare an example contract

This perspective provides general educational information and does not constitute legal advice.

Ready when you are

Prepare the working copy before AI reviews the contract.

Try LegisComply with fictional or non-critical text. Processing and review happen locally in your browser.