Your legal team was hired to advise the business. Instead, they read the same NDA for the four hundredth time.
AI systems for legal teams stuck in contract review, regulatory tracking, and due diligence. Custom AI that cuts review time by 70-85% for mid-market companies.
The Problem
Your legal team is the most expensive document review department in the company
Contract review slows down every deal: Your legal team reviews 40-60 contracts a month: vendor agreements, NDAs, client MSAs, renewals. Each one takes 2-4 hours of manual reading, clause extraction, and redline markup. That is 120+ hours monthly on first-pass review alone. Sales waits three weeks for sign-off on deals that should close in five days. Every contract in the review pile is revenue delayed or risk unassessed.
Regulatory changes hit you after the deadline: SEBI, RBI, and MCA publish hundreds of circulars and amendments annually. Your legal team is supposed to track applicability and update policies on top of contract review and business advisory. The reality: regulatory changes sit in a shared spreadsheet nobody updates. You find out about new requirements when auditors flag them, not when they are published.
Due diligence takes weeks when it should take days: Due diligence for a $6-12M deal takes 4-6 weeks and costs $12-25K in external counsel fees. Your associates review hundreds of contracts, corporate filings, compliance records, and litigation histories by hand. Half that time goes to document organisation and data extraction, work that requires zero legal judgement.
Legal knowledge leaves when people leave: Your senior counsel knows which contracts carry uncapped liability and where the regulatory risk sits. That knowledge lives in their head, scattered email threads, and 200 folders on a shared drive with no naming convention. When they leave, the replacement spends three months just figuring out what exists. No searchable repository, no clause library, no precedent database.
Our Approach
From diagnosis to deployed system in six weeks We do not sell you a generic legal tech platform. We study your legal workflows, find the highest-ROI automation opportunities, and build custom AI systems that plug into your existing tools and local regulatory requirements.
Phase 1 — Legal workflow audit (Days 1-3): We work with your legal team directly, the associates and paralegals doing the review work, not just the GC. We map every manual process: contract review workflows, regulatory tracking, due diligence procedures, document management. We measure time per task, error rates, and bottleneck costs. Nearly every team discovers they have far more automatable legal work than they assumed. Deliverable: Legal process map with time-cost analysis and automation opportunity scoring
Phase 2 — Data & document assessment (Days 4-7): We assess your legal document corpus: contracts, compliance records, board resolutions, regulatory filings. What formats? How is the metadata? How are they stored? We design the ingestion pipeline and AI architecture. Most legal AI projects go wrong here because they train models on poorly structured documents and get unreliable outputs. We sort out document quality before we build. Deliverable: Document readiness report, AI architecture blueprint, and integration mapping for your legal tech stack
Phase 3 — System build & integration (Days 8-30): The deliverable is a working AI system: contract review engine, regulatory change monitor, due diligence accelerator, or legal knowledge base. Each system is trained on your jurisdiction's legal context, including corporate law, securities regulations, central bank directives, and sector-specific compliance requirements. It plugs into your document management system, contract repositories, email workflows, and compliance platforms. Deliverable: Working AI system deployed in your environment with integration to existing tools and applicable regulatory frameworks
Phase 4 — Validation, training & handover (Days 31-42): The AI system runs alongside your existing review process for two weeks. Your legal team validates outputs, checks clause extraction accuracy, and tests edge cases against their domain knowledge. We calibrate based on their feedback. By handover, your team owns the system. They know what it can do, where its limits are, and how to handle exceptions. Deliverable: Parallel run report with accuracy metrics, team training completion, monitoring dashboard, and operations playbook
Deliverables
Discovery phase (week 1)
- Legal process map with time-cost analysis for every manual workflow
- Automation opportunity matrix scored by ROI, feasibility, and document readiness
- Document corpus assessment across contracts, compliance records, and regulatory filings
- Integration architecture blueprint for your legal tech stack
Build phase (weeks 2-4)
- Custom AI system built and deployed in your environment
- Clause extraction and risk flagging models trained on your contract corpus
- Integration with your document management, email, and compliance systems
- Jurisdiction-specific regulatory framework built in
Validation phase (weeks 5-6)
- Two-week parallel run with documented accuracy metrics against human review
- Legal team training and adoption support
- Operations playbook for system management and model updates
- Performance baseline for measuring ongoing ROI
Who This Is For
Right for you if: Your legal team spends more time on contract review and document management than on actual legal advice. You have at least $1.2M in annual revenue and enough contract volume to justify AI investment. Your regulatory compliance tracking is manual: spreadsheets, email alerts, or reactive discovery during audits. You are going through or planning M&A activity and need to cut due diligence timelines. You need a working system in six weeks. You cannot wait twelve months..
Not right if: Your legal function is one external counsel on retainer handling ten contracts a year. You do not need AI; you need a good lawyer.. You are looking for off-the-shelf legal tech software. We create custom systems, not resell SaaS products.. You are not willing to share contract and compliance data during the build process. We cannot build what we cannot see..
Use Cases
M&A / Private Equity: A mid-market PE fund running 6-8 acquisitions per year was spending $18-$25K per deal on external counsel for legal due diligence. Each deal required reviewing 200-400 contracts, corporate filings, and compliance records. The process took 4-6 weeks per transaction, and the fund's two-person in-house legal team was buried in document organisation and data extraction instead of risk assessment. — Built an AI due diligence system that ingests target company document rooms, classifies and organises documents, extracts key terms from contracts, flags risk clauses (change of control, non-compete, uncapped liability), and produces structured due diligence summaries. Trained on local corporate law requirements, statutory register verification, and regulatory filing checks.. Outcome: Due diligence cycle time dropped from 5 weeks to 11 days. External counsel costs fell by 60% per deal, saving roughly $11-$15K per transaction. The in-house team moved from document processing to risk analysis and deal structuring.
Financial Services / NBFC: A mid-sized NBFC with $25M in AUM was managing regulatory compliance across RBI, SEBI, and MCA requirements with a three-person compliance team. They tracked 200+ RBI circulars annually, filed quarterly returns by hand, and maintained compliance registers in Excel. Two consecutive RBI inspections had flagged compliance gaps from circulars the team had missed entirely. — Built a regulatory change monitoring system that tracks RBI, SEBI, and MCA publications in real time, checks applicability against the company's regulatory profile, creates compliance action items with deadlines, and routes them to the right team member. Added a compliance document generator that pre-fills regulatory returns and board reporting templates from structured data.. Outcome: Regulatory change detection went from weeks-after-publication to same-day. Compliance filing prep time fell by 70%. Zero regulatory gaps flagged in the next RBI inspection. The compliance team reclaimed 15 hours per week previously spent on manual circular tracking and return preparation.
SaaS / Technology: A B2B SaaS company with 280 enterprise clients was drowning in contract management. Their solo in-house counsel reviewed 50+ contracts monthly (client MSAs, vendor agreements, DPAs, partnership deals) while also handling DPDP Act compliance, employee contracts, and board-level advisory. Average contract turnaround was 12 business days, and the sales team had started bypassing legal review on smaller deals to avoid the backlog. — Built a contract review engine that runs first-pass analysis on incoming contracts: extracts key commercial terms, flags deviations from standard positions, identifies high-risk clauses (unlimited liability, broad IP assignment, unfavourable termination terms), and produces redline suggestions based on the company's approved clause library. Plugged into their existing contract workflow in Google Workspace.. Outcome: First-pass contract review time dropped from 3 hours to 20 minutes per contract. Average turnaround fell from 12 days to 3 days. Sales team contract bypass rate went from 30% to zero. The in-house counsel put 60% of recovered time into DPDP Act compliance and strategic advisory.
Results
What legal AI delivers
M&A / Private Equity: 78% shorter due diligence cycles, $60,000 annual saving across deal pipeline. A mid-market PE fund running six acquisitions per year was outsourcing due diligence to external counsel at $18-$25K per deal. Each transaction meant reviewing 200-400 documents over 4-6 weeks. We built a due diligence system that ingests entire virtual data rooms, classifies documents, extracts key terms from every contract, and produces structured risk summaries. The fund's legal team now runs first-pass diligence internally in 8-11 days instead of outsourcing a 5-week exercise. External counsel involvement dropped to targeted review of flagged risks only, cutting per-deal costs from $22,000 to $8,500. Across six annual deals: $60,000 in direct savings, plus closing three weeks faster.
Frequently Asked Questions
How accurate is AI contract review compared to human review?
In our deployments, AI first-pass review catches 94-97% of the clauses and risks that human reviewers identify. It also flags items that humans miss due to fatigue or time pressure. The review layer handles extraction and flagging; your lawyers focus on judgement calls. Every flagged item goes through human review before action.
Can the system handle jurisdiction-specific legal language and regulatory frameworks?
Yes. We build for your jurisdiction. We have deployed systems covering corporate law, securities regulations, central bank directives, data protection frameworks, tax filings, and sector-specific regulations for financial services, fintech, and other regulated industries. It handles local contract conventions alongside US and UK legal language.
How long does it take to see results?
Most legal AI systems are deployed and running within six weeks. You will see measurable impact within the first month: reduced review time, faster turnaround, better regulatory tracking. Full ROI typically shows within one quarter.
What if our contracts are in multiple formats (PDFs, scans, Word documents, emails)?
That is the norm. Our systems handle PDFs, scanned documents with OCR, Word files, email attachments, and photographs of signed agreements. Part of discovery is assessing your document corpus and building ingestion pipelines for your format mix.
Will this replace our legal team or external counsel?
No. AI handles the high-volume, repetitive work: first-pass review, clause extraction, document classification, regulatory tracking. Your legal team focuses on work that requires judgement: risk assessment, negotiation strategy, business advisory. Most clients reduce external counsel dependency by 40-60%, not eliminate it.
How do you handle confidential legal documents?
All data stays within your environment. We deploy on your infrastructure or your private cloud instance. We sign NDAs and data processing agreements before any engagement begins. Our systems include audit trails, role-based access controls, and privilege-aware document handling.
What is the typical cost of an AI for Legal engagement?
Engagements range from $10-$30K depending on scope and complexity. A single-function build like contract review automation sits at the lower end. Multi-function builds covering contract review, regulatory monitoring, and due diligence sit at the higher end. Most clients recover the investment within one quarter through reduced external counsel costs and recovered team capacity.
What happens after the system is deployed?
We offer ongoing AI Operations support: monitoring, model updates as regulations change, performance tuning, and feature additions. Regulatory monitoring systems in particular need maintenance as new circulars and amendments come out. Many clients start with a build engagement and move to a monthly operations retainer.
