Calculate the ROI of AI Automation for Your Law Firm
An AI automation agency delivers a production system in under 6 weeks. An in-house hire requires 6 months for ramp-up, build, and deployment.
This comparison assumes the goal is a live system for a core legal process like contract review or document intake. The timeline for an in-house hire includes recruiting, onboarding, and their first project cycle. An agency skips the 3-month recruiting and onboarding phases, starting the build on day one.
We built a system for an 8-person real estate law firm that uses the Claude API to extract clauses and flag non-standard terms. The system processes lease agreements in 90 seconds, down from 45 minutes of manual paralegal review. The entire project took 4 weeks.
What Problem Does This Solve?
Most small firms try to solve this with features inside their existing practice management software, like Clio or MyCase. These tools offer 'workflows' that are just glorified task checklists. They can create a sequence of tasks, but cannot read a document, classify its contents, or route it based on extracted data. A workflow can remind an attorney to review a lease, but it cannot perform the initial review, leaving 95% of the manual work untouched.
The next step is often hiring a generalist developer from a freelance platform. They can build a script, but lack the experience to build a secure, production-grade system for sensitive legal data. We have seen prototypes built on a personal laptop that send privileged client documents to a public API, creating a massive security risk. These scripts work on perfect data but have no audit trail, no human review gate, and break silently when an email format changes.
A 12-attorney firm handling residential closings tried to automate their intake process for 50 PDF packages a day. They hired a freelancer who built a Python script using a free OCR library. The script failed silently on 30% of scanned documents, which were then lost. They discovered the missing files two weeks later, nearly missing a critical closing deadline because the system had no logging or error handling.
How Does It Work?
We start by collecting 50-100 examples of your executed contracts and your firm's standard clause library. We load these into a Supabase database to create a searchable vector index of your approved legal language. This database runs on your own AWS infrastructure, ensuring client data never leaves your control. We use the pgvector extension for efficient similarity search.
A FastAPI service we build accepts a new contract as a PDF. The service uses an OCR engine to extract raw text, then calls the Claude API with a detailed prompt. The prompt instructs the AI to identify key clauses (indemnity, liability, termination) and compare each one against the top 5 most similar clauses from your Supabase library. Non-standard or missing clauses are flagged, and this entire process is logged with confidence scores for every AI decision.
The system does not automatically approve anything. The FastAPI service generates a summary report highlighting the flagged clauses with a side-by-side comparison against your standard language. This report is delivered to the reviewing attorney through a secure web portal built with Vercel. The attorney makes the final decision, and their approval is logged, providing a complete audit trail. This human-in-the-loop review takes under 90 seconds.
The entire system is deployed on AWS using Lambda for the API and S3 for secure document storage. This serverless architecture costs less than $50 per month to run while processing hundreds of documents. We configure CloudWatch alarms that trigger a Slack notification if the API's error rate exceeds 1% or latency surpasses 500ms. All code is delivered to your private GitHub repository.
What Are the Key Benefits?
A Production System Live in 4 Weeks
An in-house hire takes 3 months to onboard before writing a single line of production code. We start building in week one.
Fixed Project Cost, Not a 6-Figure Salary
Avoid the $150k+ annual cost of a senior developer. Our projects are a one-time build fee plus a small monthly hosting cost.
You Get the Full Source Code and IP
We deliver the entire Python codebase in your GitHub repository with a detailed runbook. You own the intellectual property completely.
Proactive Monitoring with CloudWatch Alarms
We build health checks and logging into the system. If latency exceeds 500ms or errors spike, an alert is sent before it impacts your workflow.
Connects Directly to Email and S3
The system ingests documents from a dedicated inbox or an AWS S3 bucket. Processed files and summaries are routed to the correct attorney.
What Does the Process Look Like?
System Scoping (Week 1)
You provide 50 sample documents and access to your clause library. We deliver a detailed system design document outlining the AI logic and data flow.
Core System Build (Weeks 2-3)
We build the core FastAPI service and connect it to the Claude API and Supabase vector store. You receive a link to a staging environment to test with real documents.
Integration and Deployment (Week 4)
We deploy the system on your AWS infrastructure and connect it to your firm's email or document intake channel. You receive credentials and access to the live system.
Monitoring and Handoff (Weeks 5-8)
We monitor the system for performance and accuracy, making adjustments as needed. At the end of week 8, you receive the full source code and a runbook for ongoing maintenance.
Frequently Asked Questions
- What factors determine the project cost and timeline?
- The primary factors are the number of document types and the complexity of the clauses. A system for one document type, like a residential lease, is a 4-week project. A system handling 14 different matter types with unique data points for each requires more development, typically a 6-8 week engagement. Book a discovery call at cal.com/syntora/discover for a specific quote.
- What happens when the AI makes a mistake or a document fails to process?
- Every AI decision is logged with a confidence score. If the score is below our 95% threshold, the document is automatically flagged for human review. If a document fails OCR, it is moved to a manual review queue and a notification is sent. No document is ever lost or acted upon without high confidence.
- How is this different from using an off-the-shelf legal tech AI product?
- Off-the-shelf products process your data on their servers, creating data privacy risks. Syntora builds the system on your own infrastructure so you control the data. These products are also a black box. Our system provides a full audit trail, showing exactly which clauses were compared and why one was flagged, which is critical for defensibility.
- Can this system handle scanned, low-quality documents?
- Yes. We use commercial-grade OCR tuned for scanned legal documents, which often have stamps and low-contrast text. Our OCR pipeline successfully processes over 98% of scanned documents that are legible to the human eye. The remaining 2% are automatically flagged for manual entry.
- Who provides the cloud infrastructure like AWS?
- You do. We build the system within your firm's AWS account. This ensures you own the infrastructure and data from day one. We provide a setup guide and can walk your team through creating the account and necessary permissions. The monthly AWS bill is paid directly by you and is typically under $50.
- What kind of ongoing maintenance is required after handoff?
- Minimal. The system is built on serverless components that require no patching or server management. The primary maintenance task is updating the clause library if your firm adopts new standard language. This is a documented process in the runbook that a paralegal can perform. We also offer an optional support retainer.
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