40% Faster Contract Vetting with AI-Powered Document Processing

Introduction

A mid-sized legal services firm in India specialized in verifications, contract drafting and vetting, and legal filings. The firm managed thousands of documents every month across multiple formats, but their workflows relied entirely on manual processing, resulting in slow turnaround times, compliance risks, and increasing operational costs.

The leadership team recognized the growing challenge of handling large volumes of unstructured legal data spread across PDFs, scanned filings, emails, and exhibits. While they were exploring ways to modernize their processes, they remained uncertain about the applicability of AI and whether it could deliver measurable ROI. To evaluate the potential, they partnered with Superteams.ai for a targeted solution.

Challenge Faced

The firm’s most pressing bottleneck was contract vetting, a critical service offering that required high accuracy and faster turnaround times. Key challenges included:

• High Document Volume & Complexity – Thousands of contracts monthly, often exceeding 100+ pages per case, spread across PDFs, scans, and emails.
• Slow Manual Review – Legal associates spent 30+ hours per case highlighting obligations, clauses, and cross-references.
• Compliance Risks – Inconsistent vetting and missed clauses often led to regulatory exposure and costly downstream filing errors.
• Data Sovereignty Concerns – Strict confidentiality requirements meant data had to remain on private infrastructure, ruling out third-party SaaS tools.
• Fragmented Workflows – Separate teams handled drafting, vetting, and filings, leading to duplication of effort and inefficiencies.

Our Approach

At Superteams.ai, we adopt a pilot-first delivery model designed to minimize risk and prove value quickly. Instead of transforming the client’s entire operation, we focused on one high-impact use case — AI-powered document processing for contract vetting.

Step 1. Assembling a Fractional AI Pod

We deployed a dedicated AI engineering pod comprising:

• LLM Engineers to fine-tune models on domain-specific legal data.
• Solution Architects to design the blueprint of the document analysis system.
• MLOps Engineers to ensure on-premise deployment with strict data sovereignty and compliance controls.

Step 2. Co-Creating the Solution Blueprint

We collaborated closely with the client’s partners and senior associates to:

• Map pain points within the contract vetting workflow.
• Design a solution architecture integrating OCR, vision-language models (VLMs), NER, and RAG.
• Address data sovereignty by deploying the system within the client’s private infrastructure.
• Incorporate domain knowledge through iterative consultations to ensure legally sound AI outputs.

Step 3. Delivering a Prototype in 30 Days

We committed to delivering a working prototype within 30 days:

• Built in sprint cycles with weekly feedback loops from the client.
• Tested on real client contracts to validate classification, clause detection, and summarization accuracy.
• Delivered transparent benchmarks, ensuring every feature was aligned with compliance and security expectations.

A Real-World Scenario Solved

Before deploying the AI prototype, vetting a 100-page vendor contract required 3+ hours of manual review by two senior associates. Tasks included:

• Identifying termination clauses and obligations.
• Highlighting risk points and jurisdictional dependencies.
• Preparing an executive summary for partner-level review.

With the AI-powered prototype:

• Contracts were classified instantly into relevant categories.
• Key clauses and obligations were extracted into structured, machine-readable tables.
• A concise 2-paragraph executive summary flagged critical risk areas automatically.

Result: A task that took 3+ hours was completed in 45 minutes without compromising accuracy.

Conclusion & Roadmap

After experiencing tangible ROI from the prototype, the client gained confidence in AI’s real-world applicability. They have since expanded adoption across other core workflows:

• Verification services → Automating KYC and due diligence checks.
• Drafting assistance → AI-generated first drafts for complex agreements.
• Legal filings → AI-powered error detection and cross-referencing against statutory requirements.

By starting with a single high-impact use case and delivering a working prototype in just 30 days, Superteams.ai helped the firm accelerate contract vetting, ensure compliance, and reduce costs. The engagement has now evolved into a multi-use-case AI adoption roadmap, positioning the client as an AI-first legal practice.