Artificial Intelligence, used carefully
AI is a broad term for software that performs tasks we used to think required human intelligence — reading documents, spotting patterns, summarising information. The interesting question is not whether to use it, but where.
Artificial intelligence covers a wide range of techniques, from simple pattern recognition to large language models that can read and summarise text. In insurance, the most useful applications tend to be unglamorous: turning a broker's submission into structured data, flagging anomalies, drafting a summary an underwriter can check.
The risk with AI isn't that it's too clever — it's that it can be confidently wrong. That's why the design decision that matters most is keeping a person in the loop on anything consequential.
Some problems are better solved without AI at all. Where predictability and auditability matter more than flexibility, a well-designed rule engine beats a model every time.
AI that assists, not replaces
Document intelligence
Extracting and summarising information from broker submissions and documents, saving underwriters time on data entry.
Pattern and anomaly detection
Surfacing things worth a closer look across large volumes of risk data.
Human review, always
Every AI output is checked by a person before it informs a decision — assistance, not automation of judgement.
Honest about what AI is for
We use AI where it genuinely saves time and use rules where predictability matters. We don't claim AI does more than it does, and we don't hide where a human made the call.
Good AI in insurance is boring in the best way: it removes drudgery, shows its working, and never quietly decides something a person should have.
See what a live platform looks like
Most demos show you a concept. Ours shows you something already running.