Is there an AI that extracts deadlines, fees and clauses from PDF contracts?

Who asks this

Procurement, legal and finance, when supplier contracts are scattered across folders and inboxes and, before a renewal, a termination or a cost review, someone needs to know what they actually say. AI can read a contract. Working out what is worth doing takes more evidence.

The problem underneath

Deadlines, fees, renewals and clauses can become structured data. To identify an economic opportunity you have to connect them to invoices, real usage, processes and responsibilities. These are three separate problems:

• Read: does the PDF contain the data? OCR and extraction models turn pages and scans into text and fields.
• Understand: is that data still valid? Orders, addenda and attachments can change price, term and obligations.
• Decide: is there an economic opportunity? You need to connect contract terms, actual spend, usage and alternatives.

Extraction is a solvable problem, as long as the result stays verifiable. Official documentation covers PDF import, OCR on scans, custom models and structured field extraction. The point is not an elegant summary. It is being able to go back to the page that supports every value.

• OCR makes scans readable. It recovers text from PDFs and images. Quality, tables, watermarks and handwriting remain variables to measure.
• Extraction fills a register. Counterparty, dates, amounts and custom fields can become structured data to check and export.
• A CLM manages the cycle over time. Repository, search, permissions, obligations and workflows matter when the register has to stay alive after the first upload. For a one-off register it is not required: an extraction service with a review process can be enough.

Then there is the risk OCR does not see. The contract is in a folder. The addendum is in an email. The invoice tells a third figure. The extracted value can be correct and the decision still wrong. Signature, start date, expiry and the last date to give notice are not the same thing, and a later attachment can change what the main contract says. Before talking about savings, you have to rebuild the position in force and make the exceptions visible.

How Brain50 approaches it

Not another place to upload PDFs. A way to work out what is worth verifying.

Brain50 by Streetbeat starts from the evidence the company chooses. It connects contracts, costs, processes and procedures and builds a reading management can check. Every conclusion separates what is observed from what is stated, inferred, estimated or still open. Opportunities remain proposals to verify. The shareable text stays under the user’s control.

• Sources stay visible. A number without a document, a date and context does not become a decision.
• Uncertainty is not hidden. Exceptions and open questions stay part of the result.
• Management decides what to share. Working material stays separate from the approved report.

What you need to start

The contract says what was agreed. The decision depends on what is happening. When looking for economic opportunities, the contract register is only the first layer. The other data explains whether a cost is current, used, duplicated, avoidable or tied to a real constraint.

• Contract, attachments and addenda. Nominal rights and obligations: price, term, renewal, termination, penalties and responsibilities. Confirmed by legal and procurement.
• Invoices and credit notes. Actual spend: differences between contract and charges, frequency and changes. Confirmed by finance and accounts payable.
• Licences and usage. Value consumed: active users, unused capacity, overlaps and dependencies. Confirmed by the service owner and IT.
• Process and procedures. Cost of change: manual steps, exceptions, controls and the people involved. Confirmed by operations and the process owner.
• Alternatives and constraints. A workable opportunity: replacement time, operational risk, market and negotiating power. Confirmed by procurement, legal and management.

If the contracts are scattered across email, start with an inventory. The system has to keep origin, version and the links between documents. Moving incomplete files into a new repository does not rebuild the contractual position on its own.

If you are evaluating an extraction tool, make the pilot fail on the hard cases. Do not let it shine on the easy PDFs. A useful test includes scans, contracts in your own language, tables, addenda and incomplete documents:

1. Define the register. Entity, supplier, owner, start date, expiry, renewal, termination, fee, indexation, minimums, penalties and attachments.
2. Build a reference truth. Procurement or legal verify a small sample and point to the source passage for every material field.
3. Measure the remaining work. Accuracy per field, correctly linked documents, exceptions, review time and a usable export.

Bring the problem, not the whole archive.

What it does not do

Brain50 organizes the evidence the company chooses, separates facts from hypotheses and builds opportunities to verify. It does not replace a CLM, a legal opinion or management’s decision. AI can suggest signals and questions, but a saving is not a field inside the PDF.

Five things not to delegate to AI:

• Which document prevails. The hierarchy between master agreement, order and addendum can require interpretation.
• The date that triggers a decision. Expiry and the last date to give notice must be confirmed.
• Whether the upload is lawful. Personal data, trade secrets and sensitive attachments require an authorized environment.
• Quantifying the benefit. An estimate must show baseline, assumptions, range and confidence.
• The final choice. Renewal, termination, dispute and negotiation remain the responsibility of the company and of qualified professionals.