11 days, 70% improvement
How SNOMED International proved that AI agents can translate industry specific terms with speed, precision and accuracy
Case Study
In just 11 days of working with Veratai, SNOMED proved that an AI agent could accurately translate precise clinical terms into native languages (even languages that are low on reference material), paving the way for SNOMED to increase adoption worldwide.
A Deep Research Agent for Underwriting
How Sompo International fast-tracked their deep research agent, slashed underwriting research time and improved risk management.
Case Study
The fundamental limit to the quantity of business this client can write is the time it takes underwriters to triage submissions and then to research pertinent risks affecting the insured. By developing a deep research agent, the time to search for and collate the risks dropped dramatically, leaving underwriters to focus on analysis and risk management, shortening their key metric – time-to-bind.
“Veratai are a fabulous partner for us. Not only are they highly skilled and proficient at what they do, the thing that really sets them apart is there customer-centric approach. The care, thought and empathy that they put in to solution design and build means they always deliver efficiently, accurately and with great value and utility.”
Insurance Matching
We helped a global re-insurer automate the matching of prospects to know corporate entities.
Our fuzzy matching system was capable of efficient “any-to-any” matching over datasets in excess of 100,000 records each.
Medical Entity Linking
We helped a multinational healthcare organisation execute a machine learning challenge to advance the state-of-the-art in medical entity linking.
The competition attracted over 500 participants. Winning entries included the first use of Generative AI models in the field. The post-competition analysis was published in the Journal of the American Medical Informatics Association.
The project created what is now the largest, publicly available dataset of clinical annotations.
Predicting Flight Times
We developed algorithms to enable airports in Europe and the USA to accurately predict the turn-around and departure times of aircraft.
The algorithms are used to enable more accurate scheduling and resource allocation, improving the rates of on-time departures.
Revenue Management
We worked with a global ticketing platform to develop a pricing, forecasting and reporting system to optimize revenues and yields.
The result was a bespoke analytical capability to which the client has attributed a 3% revenue uplift annually.
AI Strategy
Our client sought to understand how AI technologies could be harnessed to increase the adoption, integration and value delivered by their market-leading data product.
We integrated findings from interviews (staff, customer and wider ecosystem stakeholders) with deep industry knowledge and AI-specific research to develop a set of structured roadmaps and benefits cases for the high impact themes we identified.