Deliver safe, retrieval-grounded assistants for legal teams and client
Legal chatbots must be narrow, retrieval-grounded, and transparent. They should not give final legal advice, but assist with navigation, FAQs, intake, and drafting starters.
Mandatory safeguards include source display, escalation to attorneys, and logging. Improve responsiveness, reduce attorney interruptions, and provide consistent answers with clear boundaries and escalation.
Feedback loops, human review for low-confidence, prompt/version contro
Collect deal details, parties, and route to attorneys.
Policy/templated answers with citations. This allows for continuous improvement based on user interactions and expert oversight.
Index KM, templates, and policies; segregate client/matter data; integ
Governance, Safety, and Explainability are key considerations. Show sources and confidence; highlight when unsure.
This layered approach ensures accountability and allows for traceability of information within the legal system.
Frequently asked questions
What structured intake data fed into CLM, speeding drafting?
Structured intake data fed into CLM, speeding drafting.
How are low-confidence answers auto-escalated, reducing risk?
Low-confidence answers auto-escalated, reducing risk.
What are Frequently Asked Questions?
Frequently Asked Questions
Can it give legal advice??
Can it give legal advice??
▶ Try it live
Everything above runs in your browser — open Gradient Descent Visualiser and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.