
How Amplitude handles 400+ security questionnaires a year with a single reviewer
$1.5M+
Annual value delivered
Hours
Per security review, down from weeks
When a DPA, MSA, or security addendum hits the queue, Wolfia hands you a cited first pass instead of a blank doc. This is AI contract review grounded in the same policy corpus that answers your security questionnaires, so every verdict points at a document you already publish.
Built for GRC, customer trust and sales engineering teams.
01
The DPA, MSA, or security addendum as a DOCX or PDF. Wolfia reads every section, every comment left in the margin, and every tracked revision already in the document.
02
Your standard terms in force on that date, your ratified playbook positions, what you have already signed with other customers, and the policies and approved facts behind your security answers.
03
Each requirement comes back marked favorable, needs review, or not applicable, with the policy, SLA, or certification behind it linked. Clauses your corpus says nothing about are routed to you instead of guessed.
04
Proposed changes appear as tracked changes and the reasoning as comments, in your own paper’s language. Accept, reject, or rewrite each one, then export the DOCX.
You walk into the security conversation with a triaged draft instead of a blank doc, and the deal does not stall on you.
AI contract review software reads a contract someone else wrote and tells you, clause by clause, where it sits against what your company has already committed to. Instead of a lawyer opening a blank comment thread on a fifty-page agreement, the software gives every requirement a verdict, the reason behind it, and the policy, SLA, or certification that supports it.
Four documents show up again and again in a B2B software deal. A data processing agreement, a master services agreement, a security addendum, and a platform or SLA schedule. They arrive on the customer’s paper, they re-ask the same twenty or thirty requirements in different words, and the answer to most of them is already written down somewhere in your policies. That is what makes the work automatable. A DPA review is rarely a fresh legal question. It is the same set of positions, asked again in a new order.
The point is not to remove the lawyer. It is to move the lawyer from author to reviewer, so the first pass arrives triaged and cited and the judgment goes to the clauses that actually need it.
Upload the DPA or security exhibit. Each clause comes back marked favorable, needs review, or not applicable, so the work in front of you is review, not assembly.
Each flag links to the exact policy it came from, so you can defend the position because you can see what it rests on.
It reads the policies and approved facts Wolfia maintains for your security reviews, including overrides, so your first pass reflects your current stance.
It retrieves from your real corpus rather than writing new legal language. When the corpus has nothing on a clause, it routes it to you.
Upload the DOCX or PDF the customer sent. Wolfia reads every section, every comment your team or theirs left in the margin, and every tracked revision already in the document. A comment written by your own team is treated as a standing position. A comment written by the counterparty is the ask behind the text.
Before it judges anything on their paper, it reads yours. Your standard terms in force on that date, the playbook positions your team has ratified, the values you have already signed with other customers, and the policies and approved facts behind your security answers.
When an attachment reproduces your SLA or DPA, every number is checked against the version you publish. A response time or recovery window the counterparty quietly tightened comes back as a change to make.
A bracketed fill-in field such as a four-hour notice window is read as the value it names, compared to what you publish, and flagged so the brackets are struck at signature.
When a clause asks for a value you have already accepted elsewhere, the finding says so and names how many of your customers you signed it with. When it asks for something tighter than anything you hold, the redline steers to the tightest value you already have.
Payment terms, invoicing fields, and boilerplate are compared to your template rather than to a security policy, so the review covers the whole document and not only the security sections.
Clauses your documented policies already satisfy come back marked as met, with the document named. Clauses that protect you better than your own template are marked favorable, so your team knows to keep them through a negotiation. Clauses that have to move before you sign carry a word-level redline that touches one sentence, and inside it only the words that change, written in your own paper’s language. Headings, definitions, and cross-references are recorded as not applicable, so you can see they were read rather than skipped. A clause that needs a fact your knowledge base does not hold yet goes to a person, with the searches Wolfia ran listed so you know which document would settle it.
A second pass then reads every finding for coverage and accuracy and records its concerns, and a benchmark places the contract against market norms for its type. What you export is a DOCX with the redlines already in as tracked changes and the reasoning as comments. For the mechanics of the redline itself, see how AI contract redlining works.
Anyone on your team with contract review access can upload a contract and work the findings. Adding standard terms and ratifying playbook positions are admin actions, so the positions a redline steers to are the ones your team signed off on rather than whatever the last reviewer happened to type. A review runs without standard terms or a playbook at all, from your knowledge base alone. Both make it sharper, because standard terms give the commercial clauses a baseline and the playbook steers redlines to language legal has already agreed.
What it does not do is decide. It does not sign, it does not negotiate, and it does not write new legal language of its own. Every position it proposes comes from something you already publish or already signed, and when the corpus says nothing about a clause it hands the clause back instead of inventing a stance you would then have to defend. It also does not stand in for the security team’s read on a security addendum. Once a contract is signed and its review completes, the commitments inside it feed your obligations register with owners and due dates. If you want the manual version of the same checklist first, we wrote up the DPA and MSA review checklist for security teams.
The contract review is newer than Wolfia’s security questionnaire product. It does not replace your review or the security team’s. The job it does today is getting you out of the cold start and the manual section pull, and it gets better every time you feed a position back in.
General legal AI invents positions you then have to defend. Wolfia takes the position from your own policies and approved facts, so a proposed redline is your paper’s sentence rather than a new one, cites every flag, and routes what it does not know to you. The corpus behind it is the same one that runs Wolfia’s security questionnaire software, which is why the answer legal gives a customer matches the answer security already gave them. See the full workflow in Wolfia for legal teams.
In-house legal teams that review incoming DPAs and security addendums and do not want to be the queue every deal sits in.
AI contract review software reads an incoming contract and gives every clause that imposes a requirement a verdict, a reason, and the evidence behind it, measured against your own standard terms, playbook positions, and policies. In Wolfia the output is a triaged first pass with a tracked-change redline on the clauses that have to move, not a summary of the document.
Yes. A data processing agreement is the document Wolfia sees most. It reads the DOCX or PDF the customer sent, checks each requirement against your policies and approved facts, marks the clauses your documentation already satisfies, and flags the ones that conflict with a redline back to the position you already hold. Clauses your corpus says nothing about are routed to you rather than guessed.
Data processing agreements, master services agreements, security addenda, and platform or SLA schedules, in DOCX or PDF. It reads the comments in the margin and the tracked revisions already in the document, and when an attachment reproduces your own SLA or DPA it checks that attachment value by value against the version you publish.
No. It gets you to a defensible first pass fast so you walk into the security conversation with a triaged draft instead of a blank doc. It removes the grunt work, not the judgment.
No. Every verdict cites a fact retrieved from your real corpus, and the position a redline steers to comes from your standard papers, your ratified playbook, or the tightest value you have already signed. When it has no evidence on a clause, it leaves it for you rather than guessing.
Yes. It marks each clause favorable, needs review, or not applicable, links the policy behind the flag, and on the clauses that need to change it proposes a redline and exports the document with tracked changes and comments already written in. The proposed wording is your own. Where your standard papers or ratified playbook cover the clause, the redline is that sentence, and where neither does it steers to the tightest value you have already signed. You accept, reject, or edit each one before export.
Wolfia is SOC 2 Type II certified. Your corpus is scoped to your organization, the contract review is limited to the people who should see it, and your data is never used to train shared models.

$1.5M+
Annual value delivered
Hours
Per security review, down from weeks
“The sales team thinks it’s magic. They send in a questionnaire and get responses back the same day.”

Garrett CloseHead of GRC
Wolfia reads your policies where they already live and answers in Slack, the buyer’s portal or the file they sent.
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