Automate Contract Review: From 45 Minutes to 90 Seconds
Law firms use AI to automatically extract clauses and identify non-standard terms. This reduces manual review time from hours to seconds per document.
We built a system for an 8-person real estate firm that processes lease agreements in 90 seconds. The task previously took a paralegal 45 minutes. The system was live in four weeks and integrated directly with their email for document intake, requiring no change to their existing workflow.
A custom AI system learns your firm's specific risk tolerance from its existing contracts. The scope depends on the number of document types and the quality of your firm's clause library. A real estate firm that only handles commercial leases is a direct build. A general practice firm reviewing 15 different agreement types requires a more extensive setup.
What Problem Does This Solve?
Many firms try contract lifecycle management (CLM) platforms. But tools like Ironclad or ContractWorks are built for large corporate legal teams, not small law firms. Their per-seat pricing models are too expensive for a 10-attorney firm, and their features for collaboration across enterprise departments are unnecessary.
A small real estate firm gets a 20-page lease agreement as a PDF via email. A paralegal opens it, reads every clause, and manually compares it against the firm's standard template stored in a Word document. They highlight any deviations, write a summary, and forward it to the attorney. This takes 45 minutes of focus. At 10 leases a day, that is 7.5 hours of a paralegal's time spent on a repetitive, non-billable task that is also prone to human error.
The fundamental problem is that off-the-shelf software cannot learn your firm's specific legal judgment. A generic CLM flags any deviation from a generic template. A custom system learns what your firm considers a standard indemnification clause versus one that needs an attorney's review. These platforms force you into a one-size-fits-all workflow, undermining the bespoke expertise that is a small firm's primary value.
How Does It Work?
The process begins when a contract arrives as a PDF in a dedicated email inbox. An AWS Lambda function triggers, downloads the attachment to an AWS S3 bucket, and runs optical character recognition (OCR) using the PyMuPDF library. The system then classifies the document into one of 14 matter types. This entire intake and pre-processing pipeline executes in under 10 seconds.
We send the extracted text to the Claude API with a structured prompt engineered to identify and pull specific clauses: Term, Rent, Indemnification, Subletting, and so on. For each extracted clause, we generate a vector embedding and compare its semantic similarity to the embeddings of your firm's approved clauses, which are stored in a Supabase PostgreSQL database. This database becomes your firm's private, intelligent clause library.
If a clause's similarity score falls below a 0.92 threshold, it is flagged as non-standard. The system then prompts the AI model to explain the deviation. A final summary report is generated, listing all clauses and highlighting the 2-3 flagged items with the AI-generated explanations. The report is delivered to the responsible attorney's inbox. From initial email to final summary, the process takes 90 seconds.
We build the entire workflow as a FastAPI service. Every decision, from the document classification to the 0.92 similarity check, is logged in a Supabase audit trail table with a confidence score. To maintain attorney-client privilege, the system is deployed entirely within the client's own cloud infrastructure. Your documents never touch our servers or any third-party AI service's storage.
What Are the Key Benefits?
Review Contracts in 90 Seconds, Not 45 Minutes
Free up hours of paralegal time per day. Our system processes a standard 20-page lease agreement and delivers a summary report in under two minutes.
One-Time Build, Not Per-Seat SaaS Fees
Avoid expensive monthly subscriptions of enterprise CLM tools. You pay for the initial build and a minimal AWS hosting cost, typically under $50 per month.
You Own the Code and the Clause Library
We deliver the full Python source code in your private GitHub repository. Your custom-built clause library, stored in Supabase, becomes a valuable firm asset.
Audit Trails for Every AI Decision
Every automated action is logged with a confidence score and the source data. This provides a full audit trail for compliance and makes troubleshooting straightforward.
Connects Directly to Email and DMS
The system ingests documents from a Microsoft 365 or Google Workspace inbox and can push summaries to your existing Document Management System.
What Does the Process Look Like?
Clause Library & Workflow Mapping (Week 1)
You provide access to your standard contract templates and 10-15 recent examples of completed reviews. We map your current manual review process step-by-step.
Core AI Engine Development (Week 2)
We build the Claude API integration for clause extraction and the Supabase vector store for your clause library. You receive a prototype that can process a sample document.
Integration and Deployment (Week 3)
We deploy the system on AWS Lambda and connect it to your email intake. We test the end-to-end flow with 20 live documents to tune the flagging threshold.
Monitoring and Handoff (Week 4)
The system runs in production under our supervision. You receive the complete source code, a runbook for maintenance, and training for your team on the workflow.
Frequently Asked Questions
- What's the typical cost and timeline for a contract review system?
- A standard system for one primary document type, like commercial leases, typically takes 4 weeks to build. Pricing depends on the number of contract types, the complexity of clauses to track, and the quality of your existing templates. We can provide a fixed-price proposal after a 30-minute discovery call at cal.com/syntora/discover.
- What happens if the AI misinterprets a clause or fails?
- Every AI decision includes a confidence score. If the score is low, or if the OCR fails, the document is flagged for full manual review. The system is designed with human-in-the-loop gates; an attorney always makes the final call on flagged items. No legal advice is ever automated, ensuring professional standards are always met.
- How is this different from using a tool like Kira Systems?
- Kira is a pre-trained model for M&A due diligence, designed for large deal rooms. It is not trained on your firm's specific clause preferences. Our system is built from scratch around your private clause library and risk tolerance. It's a bespoke tool for your core practice area, not a general-purpose e-discovery platform.
- Where is our confidential client data stored?
- Nowhere we can access it after handoff. We deploy the entire system within your own AWS account. Documents are stored in your S3 bucket, and the clause library is in your Supabase instance. Syntora does not use any multi-tenant databases or store client data on our servers. You hold the keys to all your data.
- How accurate is the clause extraction and flagging?
- For well-defined clauses from scanned documents, we achieve over 95% accuracy in extraction. The flagging accuracy depends on the quality of your clause library. During the first month, we work with your team to tune the similarity threshold to match your desired balance between catching every deviation and avoiding false positives.
- Can we add new contract types later?
- Yes. The system is designed to be modular. Adding a new contract type, like a purchase agreement, involves creating a new schema for its key clauses and populating a new table in your Supabase clause library. This is a smaller follow-on project, typically taking 1-2 weeks, since the core infrastructure is already in place.
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