Preference Learning
Every time you accept or reject a suggestion, Clause Labs learns. Over time, the AI understands your preferred language, risk tolerance, and clause priorities — delivering suggestions that match your style from the first click.
30%
Improvement after 10 reviews
60%
Improvement after 50 reviews
Per-user
Personalization
Private
Learning is yours alone
Overview
The more you use it, the better it gets.
Generic AI gives the same suggestions to every user. Clause Labs's Preference Learning observes your individual review patterns — which suggestions you accept, which you reject, which you modify — and adapts future suggestions to match your style. A corporate M&A lawyer and a real estate attorney will get different suggestions for the same clause, because their preferences differ.
- Learns from every accept, reject, and edit across all your reviews
- Per-user model — your preferences don't leak to other users
- Adapts risk sensitivity, language style, and clause preferences
- Improvement is measurable: track your acceptance rate over time
- Reset preferences at any time if your practice focus changes
- Works across all contract types and playbooks
How It Works
4 simple steps
Review contracts normally
Use Clause Labs as usual — upload contracts, review findings, accept or reject suggestions. No special setup required.
AI observes patterns
The system tracks which types of suggestions you consistently accept, reject, or modify. It identifies your preferred language patterns and risk thresholds.
Suggestions improve
After just 10 reviews, you'll notice suggestions start matching your style. After 50, the AI captures most of your preferences consistently.
Continuous refinement
The model keeps learning with every review. As your practice evolves or you take on new contract types, the AI adapts alongside you.
Benefits
Why Preference Learning
Truly personal AI
Not one-size-fits-all. Your Clause Labs learns YOUR preferences, YOUR language, YOUR risk tolerance.
Continuous improvement
Gets measurably better with every review. Track your suggestion acceptance rate climbing over time.
Private by design
Your preference model is yours alone. It's never shared with other users or used to train a global model.
Zero setup
No configuration, training sessions, or preference questionnaires. Just use the product normally and it learns.
Resettable
Changing practice areas? Reset your preference model and start fresh with a clean slate.
Measurable progress
Dashboard shows your acceptance rate trend, top learned preferences, and time saved through improved suggestions.
Use Cases
Built for how you work
Employment Lawyer
An employment attorney always strengthens non-compete scope limitations and adds specific geographic restrictions. Generic AI keeps suggesting broad enforcement.
Outcome
After 15 reviews, Clause Labs learns to suggest narrow, geographically limited non-competes by default — matching the lawyer's consistent preference.
IP-Focused Counsel
An IP lawyer consistently rejects AI suggestions that assign background IP to clients, preferring license-only provisions.
Outcome
Clause Labs learns the IP assignment preference and starts suggesting license grants instead of assignments for technology contracts.
Multi-Practice Team
A small firm has partners in different practice areas sharing a Clause Labs account. Each has different preferences for the same clause types.
Outcome
Per-user learning means each partner gets personalized suggestions. The M&A partner sees different indemnification suggestions than the real estate partner.
Platform Integration
Works with everything else
Preference Learning enhances Smart Suggestions by personalizing the AI's output to your style. Combined with Playbooks, it creates a two-layer customization: playbooks define WHAT to look for, preferences define HOW to suggest fixes. Clause Library entries serve as strong preference signals, ensuring the AI reuses your preferred language.
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