The Challenge
A mid-sized legal services firm in India specializing in verifications, contract drafting, and legal filings was processing thousands of contracts monthly — each document running to 100 or more pages.
Volume vs. quality — Associates were spending 30+ hours per case on manual review. The workload was unsustainable and was creating hiring pressure the firm couldn’t afford.
Compliance risk — Manual vetting was inconsistent. Missed obligation clauses and overlooked compliance requirements were a recurring risk, with potential liability implications for both firm and clients.
Data sovereignty — Client contracts contained highly sensitive information. Any AI system had to run entirely on private infrastructure — off-the-shelf cloud-based tools were ruled out.
Fragmented workflows — Multiple teams working across disconnected systems meant context was lost between review stages, slowing resolution and increasing rework.
The Solution
Superteams deployed a fractional AI pod comprising LLM engineers, solution architects, and MLOps engineers with specific expertise in on-premise deployment.
Within 30 days, a working prototype was delivered with four core capabilities:
OCR + Vision-Language Models — Extracted structured data from contracts regardless of format: digitally created PDFs, scanned documents, or mixed formats.
Named Entity Recognition — Identified parties, dates, obligations, penalty clauses, and jurisdiction-specific compliance requirements automatically.
RAG integration — Allowed associates to query against the firm’s historical contract library to surface precedents and flag deviations from standard terms.
Private deployment — The entire stack ran on the firm’s own infrastructure, meeting data sovereignty requirements without compromise.
A 100-page contract that previously required 3+ hours of manual review could be processed in 45 minutes, with flagged clauses, extracted obligations, and compliance gaps surfaced automatically for final associate sign-off.
Results
The efficiency gains were realized across all three problem dimensions. Review time dropped 40%. Compliance accuracy improved through consistent automated clause detection. Operating costs fell as the same team could handle significantly higher volume.
Associates shifted from document assembly and clause hunting to judgment-intensive review and client advisory work — the work they were hired to do.