AI-Powered Legal Search Prototype for Tax Law
100K+
Court rulings analysed
The database the tool compares an inquiry against.
6–8
Week delivery window
The timeframe the prototype had to fit inside.
6
People on the project
The team that scoped, built and shipped it.
The client
An established law firm specialising in tax advisory and restructuring for commercial law companies. It advises on mergers, divisions and corporate transformations, and delivers legal solutions its clients can actually execute.
The challengeWhat the teams actually needed
The firm wanted to work through large volumes of legal documents — court rulings in tax law above all — with fewer human errors, and to automate the research its interns and junior associates were spending their days on.
Challenge 01Research that runs itself
Analysis of legal inquiries and court decisions had to be automated, with faster and sharper insight reaching the analysts.
Challenge 02Sources attributed correctly
Legal sources needed correct attribution and the handling of data had to stay compliant — non-negotiable when the output becomes an argument.
Challenge 03First time with AI
This was the firm’s first AI-driven project, so the work had to build trust and provide technical guidance alongside the build, and adapt as legislation changes.
What we did
Support for the decision, never a substitute for the lawyer
Scoping came first, with the team defining the prototype’s goals, its legal context and the expected outcome against demanding requirements for accuracy, scalability and data sensitivity.
Goals set with the firm
Netguru worked with the client to pin down what the prototype had to do and what counted as a good answer, inside a six-to-eight-week window.
Rulings across VAT, CIT and PIT
The prototype automates search and analysis across tax rulings in areas such as VAT, CIT and PIT, parsing an inquiry and weighing it against a database that now holds more than 100,000 decisions, to surface the closest precedents.
Structured insight for a professional
The system supports a decision rather than making one, giving lawyers organised findings that shorten the response time without lowering the standard of the legal work.
Security the firm could sign off
Data security protocols were met in full and legal sources attributed correctly, with room to scale as the volume of legal data grows.
Tech stackThe tools that made it possible
01
OpenAI
The natural language engine reading and reasoning over legal text.
02
AWS
Scalable cloud infrastructure and the security that sensitive legal data requires.
03
Python
Backend logic, data handling and integration of the ML models.
04
Custom ML models
Built specifically around tax inquiries and the reasoning they need.
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What’s next