Nicole Altman, Associate General Counsel at Instacart, had wanted to build her own AI app for a while. In her words, “there were always other things that rose higher.” Then she joined a hackathon and, with a few teammates, built Contract Compass. Upload a contract and all of its amendments, and it tells you what changed and which terms apply today. She calls it GitHub for contracts. Contract Compass is a hackathon-sized version of contract intelligence: the capability to turn a company’s executed agreements into structured, cited data that in-house counsel can query across the whole portfolio.
A legal AI platform reads every document, pulls the parties, dates, renewal triggers, caps, and obligations out of the prose, and lets a lawyer put a question to four thousand contracts the way they would put it to one.
Altman described the problem she was solving:
“A contract is not a single document. There’s the contract, there’s the rider, there are all the amendments. The amendments typically don’t restate the whole thing; you have to stitch and piece them together. When I want to understand what the terms are, I go into our database, search for the counterparty name, and get back dozens and dozens of documents. What are the operative terms? There’s no document that gives that to me, shockingly.”
In-house teams do this stitching by hand, inside a spreadsheet a summer associate built in 2021, or inside the head of the one lawyer who’s been there long enough to remember why a certain clause is even in there. Contract intelligence moves that work into a system, with a citation under every answer.
Here at GC AI, we built Contract Intelligence to put that system within reach. Point a Vault at wherever your contracts already live, ask a question in plain language, and get a cited answer back in minutes. A question that spans 500 contracts takes the same effort as one that spans 50,000.
What Is Contract Intelligence?
Contract intelligence is software that reads a company’s signed agreements, extracts the operative terms as structured data with a citation back to the source language, and answers questions across the entire contract base.
Some vendors now stretch the term to cover pre-signature work: intake, first-pass review, negotiation playbooks. The core of the category sits after signature: reading what you signed and answering questions across it.
Contract intelligence returns answers: which of your MSAs cap liability below one year of fees, which agreements auto-renew before the quarter closes, which counterparties hold an audit right you would rather they did not, each one attached to the agreement it came from so a lawyer can check the work before repeating it to the CFO.
Four things make that hard, the same four that make the manual version expensive. Amendments supersede each other without restating the whole agreement, so the governing text is spread across a stack. Repositories mix drafts and executed copies with no reliable marker between them. The same counterparty appears as Acme, Acme Corp, and Acme, Inc. across a decade of filings. And the documents sit in four systems, two of which the company inherited through an acquisition.
The cost of leaving that unresolved has a number on it: World Commerce and Contracting puts poor contract management at close to 9% of annual revenue, rising to 15% or more in complex industries, through value leakage: missed entitlements, invoicing errors, and preventable disputes.
How Does Contract Intelligence Work?
Contract intelligence runs in three steps, whatever a vendor calls them:
Ingest: Executed agreements come in from wherever they live: shared drives, a CLM, email exports, scanned PDFs from before the current system existed.
Extract: AI reads each document and pulls the terms into structured data: parties, effective and expiration dates, renewal windows, pricing and escalators, liability caps, and the obligations on both sides.
Answer: The structured data becomes something a lawyer can query, sort, and report on: which contracts renew next quarter, which counterparties hold a most-favored-nation clause, where a volume discount was negotiated and never invoiced.
The third step is where the value lands. Revenue leakage, missed renewals, and unflagged risk all trace back to terms that were signed and then never looked at again. Contract intelligence keeps them in view, with a citation to the source language under each one.
What Contract Intelligence Does With Your Contracts
Cecilia Ziniti, GC AI’s CEO and a general counsel three times over, answered Altman on the same episode with a customer’s version of the problem:
“We’ve been calling it contracts nirvana. The state of CLMs today, unfortunately, is that they don’t do this. We had a customer whose primary agreement with a particular partner went back to 1995. It had been amended six times: 26 contracts, three spinoffs. The AI gave exactly what you described, Nicole: the operative contract is this 1996 version, it was amended here and there. The person who managed that relationship said parsing those contracts took a week when they first joined.”
That was a week of one person’s time to sort out a single counterparty. Contract Intelligence puts an agent on your portfolio to run the same pass across every contract family at once. Point it at wherever the contracts already live, and it takes over from there:
Connect your existing systems: Google Drive, Microsoft SharePoint, OneDrive, Dropbox, or Ironclad, or upload directly: PDFs, Word files, PowerPoint decks, scanned images, .msg and .eml email exports, spreadsheets, plain text. The documents land in a Vault exactly as they are, nothing tagged, renamed, or routed through an implementation consultant first, and connected sources sync every 15 minutes. DocuSign and Salesforce connectors are next on the roadmap.
Extract terms into cited Columns. Describe what you want in plain language: governing law, the notice period for termination, whether a most-favored-nation clause exists, the exact limitation of liability figure and what it’s a multiple of. Every value in the resulting View carries a citation you can click straight through to the source passage.
Link documents into contract families. An amendment finds its master agreement, an SOW finds its MSA, a renewal finds the original. Current Terms then rolls up the in-force language, so what governs today reads as one document, even when somebody signed the original in 2019.
Split compound PDFs automatically. A 340-page file with a master agreement and six amendments scanned together separates into its own rows.
Normalize counterparty names. Acme, Acme Corp, and Acme, Inc. resolve to one counterparty, so a renewal report stops fragmenting across three spellings.
Ask portfolio-wide questions in plain language. Chat answers and filters the View to the exact agreements behind the answer at the same time, so the conclusion and the evidence arrive together.
It also marks each document as a draft or an executed copy on its own, renames files into your convention while the originals stay untouched at the source, and keeps each teammate’s saved views in the Vault. A question your department has been answering from memory since 2018 becomes a column anyone on the team can sort.
Contract Intelligence and the CLM You Already Pay For
A CLM does two jobs. One is workflow: drafting from templates, routing approvals, running redlines, collecting signatures. The other is storage: keeping the signed contracts and finding them again when someone has a question.
Contract intelligence takes over the storage job. Your signed contracts stay where they live today, in Google Drive, SharePoint, or the CLM itself. GC AI connects to that source, reads every agreement, and answers questions across all of them in minutes, with a citation under every answer. Setup is connecting a source and asking a question.
If you already use GC AI to review contracts one at a time, GC AI’s Contract Intelligence lets you put thousands of them in one place and ask across all of them.
The workflow job is where the buying decision sits. Open your CLM and look at what your team touched last quarter. If most of the activity is intake requests, approval routing, and signature workflows, keep the CLM for that and add contract intelligence for the questions it has never answered well. If most of the activity is people opening it to find a PDF, you are paying enterprise pricing for a filing cabinet with a search box, and contract intelligence covers the part you use.
That second case is more common than CLM renewal decks suggest. Plenty of teams bought the lifecycle and ended up living in the repository, then built a shadow spreadsheet next to it because the repository could not answer which agreements auto-renew in Q4. Contract intelligence is the intelligence you always wanted from your CLM and rarely got.
Contract intelligence works after signature. It reads what you signed. Drafting and negotiation happen upstream, where Playbooks checks a draft against your standard positions and proposes redlines inside Microsoft Word. GC AI’s contract management AI guide maps how the two halves fit together.
Who Gets the Most Out of Contract Intelligence
The teams that see an obvious return share a profile:
A portfolio past roughly a thousand active contracts, where nobody has read all of them and nobody realistically could.
A legacy book of business: a company old enough that some still-governing agreement predates the current CLM, carrying an amendment chain long enough to need its own index.
A live use case already burning hours: an M&A diligence request, a renewal calendar with holes in it, or a recurring search so specific that no vendor’s out-of-the-box field covers it.
That last signal is where the demos get specific:
The department with years of accumulated vendor agreements: “Which of our vendor agreements have uncapped liability, and what’s the cap where there is one?” The View filters to the agreements named, and each cap traces back to the clause behind it.
The M&A lawyer mid-diligence: point a fresh Vault at a target’s contract set and ask, “Flag any agreement with a change of control or anti-assignment provision, and add a column for consent requirements.” Several hundred documents get one pass before the next diligence call.
The publisher needs every agreement where audio rights reverted, and the payments company needs every contract carrying a most-favored-nation clause tied to volume tiers, surfaced before the next pricing review.
The services company closes an acquisition a month and wants the acquired contract base classified before each deal closes.
The hospitality company still operates under a property agreement signed in the nineties, and somebody has to find its terms.
A keyword search cannot answer these. Answering them by hand can burn a paralegal’s whole week.
Contract intelligence doesn’t fit every team. If your company is young enough that one or two lawyers have personally handled every agreement in the last eighteen months, they already have the answers, in their heads, for free.
A team running a well-tagged CLM that genuinely works should spend the budget elsewhere. And a team whose real pain is drafting and negotiating faster should start upstream with review and playbooks, where the hours are.
What to Ask Before You Buy Contract Intelligence Software
The first question for any vendor is where accuracy gets verified, and how fast. One extracted value travels into every portfolio answer that touches it and lands in front of the CFO with the same confident formatting as every other value, so checking has to be cheap enough to run on each one that matters.
GC AI’s answer is Exact Quote, character-level citations that tie each extracted term back to the precise contract language it came from. Contract Intelligence carries the same discipline into the Vault through View source, which opens the underlying document with the passage highlighted in-app. Verification is one click per value, so a lawyer checks all of them and skips the sample-and-hope routine.
How to Evaluate Contract Intelligence Software
Run the evaluation against your own agreements, in your own systems, with your own weird clauses. Six questions separate a working platform from a demo:
Hand it a contract family: Give the demo a master agreement plus two amendments and ask which terms govern today. A working platform returns the current terms with the change history behind them, and lets you click straight through to the amendment that moved each one.
Ask where each value comes from. Every extracted term should link back to the passage behind it at the character level, viewable in one click.
Test a question nobody would build a field for. Use the strange one your business asks twice a year. Out-of-the-box field libraries handle governing law and fall apart on royalty reversion.
Bring your messiest file: a 340-page scanned compound PDF, a signature page with a counterparty name spelled three ways, or an .msg export with the agreement as an attachment.
Confirm the connectors and the capacity. Check that it reads from the systems your contracts sit in today, and size the capacity against your full document count, archived contracts included.
Get the security posture in writing before the pilot starts: the SOC 2 Type II report and the data-retention terms with model providers.
Then run a ten-agreement pilot.
Pick ten contracts your team has already reviewed, run them through the platform, and compare what comes back against what your lawyers caught.
The pilot goes better when the lawyers running it already know how to ask: how to describe a Column, how to phrase a portfolio question, when to click through to the source. GC AI’s legal AI classes teach exactly that, hands-on, and have taught more than 8,000 lawyers so far.
What Contract Intelligence Costs and What GC AI Customers Get Back
Contract Intelligence is a paid add-on to GC AI, priced on document capacity and sized to the portfolio you want to bring in. It sits separate from the $500/mo individual seat that covers the core platform. You can see it in action on your own contracts and get full pricing by reaching out to GC AI.
What comes back is measurable in the two currencies a GC reports upward. Across the GC AI platform, in GC AI’s December 2025 ROI study of more than 100 active customers, teams reported saving an average of 14 hours per week and cutting outside counsel spend by 14%, about $252,000 in annual savings for the median company. Run your own inputs through the GC AI ROI calculator.
The time savings show up as compressed tasks: the calendar looks the same, but each item on it takes less time. Cameron Clark, Head of Legal at Arc’teryx, put a stopwatch on it:
“What used to take an hour, like reviewing contract feedback and drafting a reply, now takes ten minutes, and the results are better.”
In the same study, 97.5% of teams saw value from GC AI before the end of month one. More than 2,000 legal teams across 53 countries run on GC AI as of August 2026, including 200+ public companies.
See It Run on Your Own Contracts
Altman’s hackathon build runs standalone: upload the documents, get back a change log and a stitched-together final version. Contract Intelligence does that same work connected to wherever your contracts already live, across every counterparty at once.
The fastest way to judge it is to watch it run on your messiest one.
Bring the master agreement, the amendments, the order forms, and the assignment letter to a demo, and ask what the operative terms are today. You will watch the contract family assemble, see the change history behind each term, and click from any value to the clause it came from, in minutes. Pricing for your portfolio comes up in the same conversation.
Frequently Asked Questions
Is Contract Intelligence the Same Thing as AI Contract Review?
AI contract review works on one agreement at a time, checking a draft against your standard positions and proposing redlines. Contract intelligence works across the whole executed portfolio at once, extracting terms into a queryable Vault with citations. The two work side by side, and GC AI covers the single-agreement workflow in its AI contract review guide.
What Is the Difference Between Contract Intelligence and Contract Analytics?
Contract analytics reports on data a system already holds: cycle times, volume by contract type, renewal counts. Contract intelligence creates that data from the executed agreements themselves, reading the prose, extracting each term with a citation, and answering questions across the set. Analytics needs structured data to count. Contract intelligence is how the structured data gets built.
Who on an In-House Team Uses Contract Intelligence Most?
Commercial counsel use it to answer business questions about the signed base, legal ops use it to build the standing views the department checks every quarter, and the GC uses it for board-level and diligence questions that used to require a paralegal sprint. GC AI supports more than 2,000 legal teams across 53 countries, and the pattern holds across department sizes.
Who Outside Legal Uses the Answers From Contract Intelligence?
Finance wants renewal dates and payment terms before the quarter closes. Procurement wants every vendor agreement with an auto-renewal or a price escalator. Sales wants to know which customers hold a most-favored-nation clause before pricing changes. Those questions land on legal, and contract intelligence lets legal answer them from the Vault in minutes, with the clause behind each answer.
Is Contract Intelligence Secure Enough for Confidential Agreements?
GC AI is SOC 2 Type II and SOC 3 certified, GDPR compliant, and encrypts data with AES-256. GC AI works with leading AI providers such as OpenAI and Anthropic, none of which train on your data, and maintains zero-data-retention agreements with its LLM providers wherever feasible. Every vendor that processes your data is SOC 2 compliant, and the full Subprocessor List is public. Original documents stay in place at the source system, so connecting a Drive or SharePoint reads from your repository without moving it. Ask every vendor you evaluate for the same certifications in writing.
