Legal request intake
Capture purpose, parties, urgency, documents, risk and required decision before substantive work begins.
Legal AI for in-house legal teams
Increase legal service capacity.
Keep decisions governed.
Gotham helps Indian corporate legal teams structure intake, contract review, research, disputes and regulatory work while keeping business context, source support, approval boundaries and human accountability visible.
Primary valueService capacity, consistency and business visibility
Control pointLegal owns judgment and escalation
First stepOne recurring request with an observable outcome
The buying problem
In-house legal work rarely arrives as a clean prompt. Requests come through email, chat and meetings with missing context, compressed deadlines and unclear approval authority. Automating only the answer can make the bottleneck worse if intake, handoff and decision ownership remain undefined.
A useful legal AI business case connects the full service path: request, triage, source or document work, lawyer verification, business decision, approval and retained evidence. Value may appear as faster service, more matters handled, reduced outside-counsel dependence or fewer operational exceptions—not simply reduced headcount.
Where Gotham can enter the work
Contract review
Apply playbooks, flag deviations, route escalations and retain the source language behind each issue.
Indian legal research
Build source-linked answers across relevant courts, statutes, tribunals and regulators for counsel review.
Dispute and chronology work
Organize the matter record, events and issue views while preserving provenance and competing accounts.
Regulatory obligations
Connect identified obligations to owners, triggers, evidence and review rather than creating unsupported reminders.
Legal operations visibility
Track workflow state, reviewer corrections and handoffs without exposing privileged content unnecessarily.
What to require in evaluation
End-to-end service fit
Test the path from business request to reviewed legal output and accountable next action.
Playbook governance
Confirm approved positions, fallbacks and escalation rules can be represented and changed safely.
Business usability
Validate whether non-legal requesters can provide context and receive controlled outputs without bypassing Legal.
Integration boundary
Identify systems of record for contracts, matters, documents, identity, approvals and reporting.
Data controls
Verify residency, retention, model providers, subprocessors, permissions, logs and customer-data use.
Realized economics
Measure internal capacity, turnaround, avoided external spend and exception reduction separately.
Align the buying committee before the pilot
Questions to resolve
- Which legal leader owns the workflow and professional decision boundary?
- Which business function supplies inputs and acts on the reviewed output?
- Which security, privacy, procurement and IT gates must be passed?
- Which system remains authoritative for documents, contracts and approvals?
Rollout controls
- Publish permitted, restricted and prohibited use cases.
- Train users on verification, escalation and confidential data handling.
- Keep business self-service within approved templates and decision bounds.
- Review adoption, exceptions, quality and value before adding workflows.
Good first pilot candidates
A useful pilot has bounded inputs, a known reviewer and an output whose quality can be scored. Consider:
- Review a recurring vendor or customer agreement against the legal playbook.
- Answer a bounded regulatory question using a defined source universe.
- Build an issues list or chronology from a controlled dispute record.
Start with the workflow, not the licence count.
Use a private assessment to choose the first test and its success measures.