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A new technology company has harnessed data science and case law analytics to rank legal practitioners based on their courtroom track records.
Mona Chiha, founder of pioneering legal technology company Juris Techne, has combined her deep expertise in legal analytics with an innovative approach to referrals to create a network that puts high-performing practitioners at the forefront of client opportunities.
Speaking at Lawyers Weekly’s Tech Innovate 2026, Chiha revealed how sophisticated case law analytics can provide powerful insights into the performance of solicitors and barristers across different areas of litigation.
“What we decided to do was build a tool that helps people decide which lawyer or barrister they want to go with, and that’s all through analytics so you can see how people have performed,” Chiha said.
“Now, it’s not as simple as a win or loss; there’s also a level.
“If you look at the penalties or remedies and you look at maximum and minimum and see where those particular cases for that particular lawyer or barrister sit, that makes a difference.”
The soon-to-be-released tool, Your Legal Team, spans multiple areas of litigation, including personal injury, criminal, commercial and family law.
In addition to mapping historic judgments, the platform will continue to be updated as new judgments are handed down.
Each lawyer’s profile will provide insights into the frequency and recency of their court appearances, their position on sentencing or remedy scales across matters, and their breakdown of wins, losses and procedural outcomes.
These data points will be supported by direct citations to the underlying judgment, allowing users to explore the source material for themselves.
“We wanted to create this referral network that says, ‘hey, we don’t specialise in everything, nobody does, but here’s a list of people that have done this, this, this and these are their outcomes, these are their area of law, these are the types of matters’,” Chiha said.
“It becomes a really powerful tool.”
For Chiha, the integrity of the data underpinning legal technology is critical.
JurisTechne deliberately steers away from large language models and generative artificial intelligence, instead focusing on data-driven tools designed to give users smarter, cleaner and more trustworthy information.
Chiha said a pillar of algorithmic law is ensuring that credible datasets underpin the technology, rather than relying on information sourced from places like “Wikipedia, or Reddit, or some rando’s blog post”.
“When we empower ourselves with the right data, we can make really great and informed data-driven decisions,” Chiha said.
