Role: Lead Product Designer
Timeline: 7 Months
Company: Wolters Kluwer
Product Category: Enterprise B2B SaaS | LegalTech Platform
Core Team: Lead Designer (myself), 1 UX Researcher, 1 Engineer, and 1 Product Manager
Impact & Benefits
Impact at a Glance
Reduced manual proposal review time by up to 40% through AI-generated summaries and scoring.
Improved consistency and fairness in firm selection by standardizing how proposals are evaluated against RFP criteria.
Increased trust in AI-assisted decisions via transparent scoring, confidence indicators, and traceable source references.
Business & User Benefits
Faster, Higher-Quality Decisions: Managing attorneys and legal ops can move from reading lengthy PDFs to comparing concise, structured summaries—freeing more time for strategy and risk assessment.
More Consistent Evaluations: AI scoring frameworks apply the same criteria (pricing, expertise, risk profile, D&I metrics, etc.) across firms, reducing subjectivity and bias in selection.
Reduced Risk Through Predictive Insights: Forecasting likely success based on historical engagements helps teams select firms that are more likely to deliver on budget, timeline, and outcomes.
Richer Context at the Point of Decision: Contextual retrieval from past matters, billing, and benchmarks brings institutional knowledge into each decision without manual research.
Explainable AI for Legal: Confidence indicators, traceable sources, and human‑in‑the‑loop review support auditability and give legal, procurement, and finance stakeholders confidence in AI-assisted recommendations.
Cross‑Functional Alignment: Shared dashboards and common data views make it easier for legal, procurement, and finance to align on which firm to choose and why.
Product Overview
As part of LegalCollaborator’s evolution, we introduced Generative AI-powered summarization and analysis tools that enhance how corporate legal teams evaluate law-firm proposals.
The system uses natural language processing (NLP) and machine learning to synthesize key proposal details — highlighting alignment to RFP criteria, surfacing differentiators, and predicting success likelihood.
This innovation transforms complex RFP evaluations into data-driven, insight-rich decisions that reduce manual review time and strengthen transparency.
The Objective
Empower legal departments to:
Automate the comparison of law-firm proposals using Gen AI summarization and contextual analysis
Accelerate decision-making through AI-driven scoring, predictive insights, and visual analytics
Improve accuracy and consistency in law-firm evaluations
Enhance collaboration between legal, procurement, and finance teams through transparent data presentation
Key Features & Enhancements
AI-Generated Proposal Summaries
Automatically condenses lengthy proposals into concise, comparable summaries.
Highlights scope alignment, methodology, pricing model, and differentiators.
Integrates human-in-the-loop review to verify critical details.
Impact: Reduces evaluation time by 40% while maintaining accuracy and auditability.
Comparative Analysis & Scoring
Evaluates proposals against predefined RFP criteria (e.g., pricing, expertise, risk profile, D&I metrics).
Scores proposals based on both quantitative (cost, timeline) and qualitative (experience, approach) data.
Impact: Enables fair, consistent, and evidence-based selection decisions.
Predictive Insights & Success Forecasting
Uses historical engagement data to forecast likelihood of project success for each firm.
Highlights patterns in efficiency, budget adherence, and outcomes.
Impact: Provides forward-looking insights to reduce risk and strengthen strategic partner selection.
Contextual Knowledge Retrieval
Pulls relevant information from past matters, billing data, and industry benchmarks to inform recommendations.
Surfaces similar case references and performance patterns.
Impact: Adds depth to AI summaries by combining historic and current context.
Visual Decision Dashboards
Displays AI-generated summaries, comparative scores, and predicted outcomes in an interactive dashboard.
Includes confidence indicators and traceable source links for auditability.
Impact: Improves transparency and stakeholder trust in AI-assisted decisions.
Use Cases
Managing Attorneys
Review AI summaries to quickly identify the best fit law firm based on expertise and pricing efficiency.
Legal Operations Managers
Use predictive insights to forecast budget impact and optimize firm allocations.
Procurement & Finance Teams
Validate pricing and efficiency metrics through AI-generated comparative data and visual dashboards.
