Case Study: AI-Powered Docketing Assistant for Legal Professionals
Transforming time-consuming legal docketing into a seamless AI-driven workflow
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The Challenge
For lawyers, accurate docketing is an essential but tedious part of everyday work. Each task—from preparing legal matters to writing client emails—must be carefully tracked and logged. Traditional “clock-in/clock-out” software provides partial help, but it fails to solve the real problem: lawyers still spend valuable time manually entering and categorizing their activities.
Our client, a legal tech startup, set out to radically change this process. The founding team envisioned a solution that would:
- Automate time tracking and docket creation end-to-end.
- Reliably recognize different types of legal activities.
- Free lawyers from administrative overhead so they can focus on client work.
They partnered with us to turn this ambitious idea into a working MVP.
The Solution
Working closely with the founders, our team designed and developed a desktop application powered by AI at its core. The app takes the form of a lightweight widget that runs on the lawyer’s computer, continuously monitoring and interpreting work activity.
Automated activity recognition
The app captures screenshots and monitors desktop activity. Using GPT models, it distinguishes between tasks such as drafting contracts, conducting research, or meeting with clients.
Smart docket creation
Activities are automatically translated into structured daily dockets.
Review & edit flow
At any point, a lawyer can view the current day’s docket, make quick edits, and submit it for approval.
End-to-end product delivery
From product discovery and UI/UX design to full implementation, we supported the startup in bringing the MVP to life.
The Results
The MVP successfully demonstrated that AI can eliminate one of the most painful bottlenecks in legal work.
Lawyers no longer need to manually log hours—dockets are generated automatically.
The product recognizes and categorizes different work activities with high accuracy.
The streamlined review process ensures both convenience and compliance.
The startup now has a functional, investor-ready product to present to law firms.
Project challenges
Evolving AI models
Large language models produce non-deterministic outputs. To ensure reliable performance, we designed flexible integrations that could adapt to model changes. Different models were used for distinct tasks—lightweight ones for screenshot analysis and more powerful models for reasoning.
Strict budget & timeline
With only 700 total hours allocated, efficiency was key. We optimized development by engaging engineers strategically and heavily leveraging AI-assisted coding tools. This allowed us to deliver the MVP without compromising on quality.
Conclusion
Together with the client’s founding team, we transformed a bold idea into a tangible AI product that addresses a long-standing pain point in legal practice. The AI-powered docketing assistant shows how automation can reshape traditional workflows, freeing professionals to focus on higher-value tasks.
With the MVP completed, the startup is now positioned to validate the solution with law firms and prepare for scale.
Tech Stack
- Frontend: React + Next.js
- Desktop App: Electron wrapper
- Backend & Hosting: Node.js deployed on Heroku
- Database: PostgreSQL
- AI integration:
GPT-4.1-mini & GPT-4.1-nano for screenshot reading
GPT-4o for summarization and reasoning
- Engineering efficiency: Development accelerated using Cursor with Sonnet 3.5
Budget
- Product discovery & UI/UX: 200 hours — $10,000
- Software development: 500 hours — $25,000
- Total investment: $35,000