Your General Counsel has fifteen years of courtroom experience, a sharp legal mind, and spends half the week extracting indemnity clauses from vendor contracts.
We build AI systems that automate contract review, monitor regulatory changes in real time, accelerate due diligence, and structure legal knowledge. Your legal team gets to do the work they were actually hired for.
Your legal team is the most expensive document review department in the company.
Contract review is a bottleneck that slows down every deal
Your legal team reviews 40-60 contracts a month: vendor agreements, NDAs, client MSAs, renewals. Each takes 2-4 hours of manual reading, clause extraction, and redline markup. That is 120+ hours a month on first-pass review. Sales waits three weeks for sign-off on deals that should close in five days. Every contract sitting in the review pile is revenue delayed or risk unassessed.
Regulatory changes hit you after the deadline has passed
SEBI, RBI, and MCA publish hundreds of circulars and amendments annually. Your legal team is supposed to track applicability, update policies, and ensure compliance on top of contract review and business advisory. The reality: regulatory changes are tracked in a shared spreadsheet nobody updates. Your team discovers 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 team reviews hundreds of contracts, corporate filings, compliance records, and litigation histories manually. Half that time is spent on document organisation and data extraction, work that requires no legal judgement.
Legal knowledge walks out the door every time someone leaves
Your senior counsel knows which contracts have 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 new hire spends three months figuring out what exists. No searchable contract repository, no clause library, no precedent database.
From diagnosis to deployed system in six weeks
We do not sell you a generic legal tech platform. We study your legal workflows, identify the highest-ROI automation opportunities, and build custom AI systems that integrate with your existing tools and local regulatory requirements.
Legal Workflow Audit
Days 1-3
We sit with your legal team. Not the GC alone, but the associates and paralegals doing the actual review work. We map every manual process: contract review workflows, regulatory tracking methods, due diligence procedures, document management practices. We measure time spent per task, error rates, and bottleneck costs. Most companies find they have far more automatable legal work than they expected.
Deliverable: Legal Process Map with time-cost analysis and automation opportunity scoring
Data & Document Assessment
Days 4-7
We assess the state of your legal documents: contracts, compliance records, board resolutions, regulatory filings. What formats are they in? How is the metadata? How are they stored and organised? We design the document ingestion pipeline and AI architecture. This is where most legal AI projects fail. They train models on poorly structured documents and get unreliable outputs. We do not make that mistake.
Deliverable: Document readiness report, AI architecture blueprint, and integration mapping for your legal tech stack
System Build & Integration
Days 8-30
We build the AI system, whether it is a contract review engine, a regulatory change monitor, a due diligence accelerator, or a legal knowledge base. Every system is trained on your jurisdiction's legal context: corporate law, securities regulations, central bank directives, and sector-specific compliance requirements. We integrate with your existing tools, including document management systems, contract repositories, email workflows, and compliance platforms.
Deliverable: Working AI system deployed in your environment with integration to existing tools and applicable regulatory frameworks
Validation, Training & Handover
Days 31-42
We run the AI system in parallel with your existing review process for two weeks. Your legal team validates outputs, checks clause extraction accuracy, and tests edge cases against their domain expertise. We calibrate the system based on their feedback. By handover, your team owns the system. They understand its capabilities, its limitations, and how to handle exceptions.
Deliverable: Parallel run report with accuracy metrics, team training completion, monitoring dashboard, and operations playbook
Legal Workflow Audit
Days 1-3
We sit with your legal team. Not the GC alone, but the associates and paralegals doing the actual review work. We map every manual process: contract review workflows, regulatory tracking methods, due diligence procedures, document management practices. We measure time spent per task, error rates, and bottleneck costs. Most companies find they have far more automatable legal work than they expected.
Deliverable: Legal Process Map with time-cost analysis and automation opportunity scoring
Data & Document Assessment
Days 4-7
We assess the state of your legal documents: contracts, compliance records, board resolutions, regulatory filings. What formats are they in? How is the metadata? How are they stored and organised? We design the document ingestion pipeline and AI architecture. This is where most legal AI projects fail. They train models on poorly structured documents and get unreliable outputs. We do not make that mistake.
Deliverable: Document readiness report, AI architecture blueprint, and integration mapping for your legal tech stack
System Build & Integration
Days 8-30
We build the AI system, whether it is a contract review engine, a regulatory change monitor, a due diligence accelerator, or a legal knowledge base. Every system is trained on your jurisdiction's legal context: corporate law, securities regulations, central bank directives, and sector-specific compliance requirements. We integrate with your existing tools, including document management systems, contract repositories, email workflows, and compliance platforms.
Deliverable: Working AI system deployed in your environment with integration to existing tools and applicable regulatory frameworks
Validation, Training & Handover
Days 31-42
We run the AI system in parallel with your existing review process for two weeks. Your legal team validates outputs, checks clause extraction accuracy, and tests edge cases against their domain expertise. We calibrate the system based on their feedback. By handover, your team owns the system. They understand its capabilities, its limitations, and how to handle exceptions.
Deliverable: Parallel run report with accuracy metrics, team training completion, monitoring dashboard, and operations playbook
Systems, not slide decks
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 specific 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 ongoing system management and model updates
- Performance baseline for measuring ongoing ROI
Scope boundaries
This engagement focuses on AI systems for your legal and compliance function. For broader automation, model customisation, or governance needs, see our related services.
AI governance frameworks and policy development
We build legal AI systems that are auditable and explainable. But if you need a full AI governance framework (responsible AI policies, risk assessments, bias auditing, regulatory compliance programmes) that is a separate engagement.
AI GovernanceCustom model training and fine-tuning for domain-specific legal language
Our standard legal AI systems use pre-trained models with prompt engineering and retrieval-augmented generation. If your use case requires fine-tuning a model on your proprietary legal corpus (specialised contract language, industry-specific clauses, or vernacular legal documents) that falls under our LLM fine-tuning practice.
LLM Fine-TuningEnd-to-end business process automation beyond legal
If you need automation across procurement, HR, finance, and operations in addition to legal (cross-functional workflow orchestration, beyond legal AI) that falls under our broader Automation practice.
AutomationIs this right for you?
Right for you if
- Your legal team spends more time on contract review and document management than on strategic 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 accelerate due diligence timelines
- You want a working system in six weeks, not a twelve-month digital transformation programme
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 build 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.
What these engagements look like in practice
Problem
A mid-market PE fund conducting 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.
What we did
Built an AI-powered due diligence system that ingests target company document rooms, automatically classifies and organises documents, extracts key terms from contracts, flags risk clauses (change of control, non-compete, uncapped liability), and generates structured due diligence summaries. Trained the system on local corporate law requirements, statutory register verification, and regulatory filing checks.
Outcome
Due diligence cycle time reduced from 5 weeks to 11 days. External counsel costs dropped by 60% per deal, saving approximately $11-$15K per transaction. The in-house team shifted from document processing to risk analysis and deal structuring.
Problem
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 were tracking 200+ RBI circulars annually, filing quarterly returns manually, and maintaining compliance registers in Excel. Two consecutive RBI inspections had flagged compliance gaps related to circulars the team had missed entirely.
What we did
Built a regulatory change monitoring system that tracks RBI, SEBI, and MCA publications in real time, assesses applicability against the company's regulatory profile, generates compliance action items with deadlines, and routes them to the responsible 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 preparation time reduced 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.
Problem
A B2B SaaS company with 280 enterprise clients was drowning in contract management. Their solo in-house counsel was reviewing 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.
What we did
Built a contract review engine that performs first-pass analysis on incoming contracts: extracting key commercial terms, flagging deviations from standard positions, identifying high-risk clauses (unlimited liability, broad IP assignment, unfavourable termination terms), and generating redline suggestions based on the company's approved clause library. Integrated with their existing contract workflow in Google Workspace.
Outcome
First-pass contract review time reduced from 3 hours to 20 minutes per contract. Average turnaround dropped from 12 days to 3 days. Sales team contract bypass rate fell from 30% to zero. The in-house counsel reallocated 60% of recovered time to DPDP Act compliance and strategic advisory.