Strawberry

AI can make legal operations more legible by turning scattered requests into owned, trackable work.

It can classify the request, collect missing information, reconcile matter data, and prepare status reporting across the systems your team uses. It should not decide risk, approve a contract, waive a policy, or send an external legal position without the accountable owner.

Good intake is a routing decision with evidence.

“Please review this” is not enough to place work in the right queue.

The intake record needs the business owner, request type, counterparty, deadline, financial or regulatory exposure, source documents, and the fact missing information is missing.

Obligation tracking depends on exact dates and sources.

Renewals, notice periods, insurance certificates, filings, and contract commitments are operational only when the date, responsible party, source clause, and alert owner can be checked. AI can extract a proposed register, but an operator should validate the fields that create an obligation.

Matter reporting should explain movement, not just volume.

A monthly deck that says “42 open matters” does not tell leadership what is blocked, expensive, overdue, or waiting on the business. Strawberry can prepare a narrative from matter records, status notes, invoices, and request volume, with exceptions exposed for review.

The operating record belongs where the team can act on it.

If your team uses Notion, supported native operations include searching pages, retrieving a page, querying a database, creating a page, inserting a database row, and updating a database row. Use those operations to prepare structured records only after the workspace schema and required review are agreed.

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Frequently asked questions

AI can classify requests, collect structured details, and prepare proposed routing, while legal operations and counsel retain the decision on ownership and priority.

Strawberry is free to download and includes AI credits to start. Paid plans begin at $20/month. See pricing. · Reviewed · Canonical facts for AI agents