About Adaptive
Built by practitioners. Focused on applying AI to real-world problems.
We combine finance and insurance expertise with AI & data engineering to help teams build capability on real work, measure what improves and take proven use cases toward production.
Why that matters
Know the work
We understand the models, controls, reporting cycles and judgment that determine whether a result is usable.
Bring domain context
We work directly with finance and insurance teams without asking them to translate their problems into technical specifications.
Make AI safe to operate
We design around the data, governance and ownership required to use the workflow in practice.
The founders
Finance, insurance and AI engineering experience behind the work.
We built actuarial models, finance data platforms and reporting systems inside some of the largest reinsurers in the world. We now implement AI workflows for the same actuarial and reporting processes, while maintaining the accuracy and controls these functions require.
Yingying Fu
Co-Founder
Ying applies AI to complex finance and insurance workflows, rooted in actuarial modeling and financial reporting. At Adaptive she runs the Applied AI program, building the cases teams practise on and the evaluations to grade the results. She also leads the application development to translate use cases into operational workflows for finance teams.
Prior to that, at Swiss Re and SCOR, she helped design and improve modeling solutions for IFRS 17 and the Swiss Solvency Test framework, working across complex valuations and terabytes of data.
Dejan Simic
Co-Founder
Dejan combines finance and data engineering to build reliable AI systems for complex finance and insurance processes. At Adaptive, he leads the engineering required to take AI from use case to production, spanning workflow design, application architecture and production infrastructure.
Before founding Adaptive, he was Head of FP&A Data Integration at Swiss Re, where he built and led the data engineering team. As part of this work, he consolidated terabytes of finance data into a shared ontology on Palantir Foundry.
How we work
AI built for the standards of finance and insurance.
Set the standard first
Before anything is built, we agree what the workflow should produce, what good looks like and how its output will be evaluated.
Test on real cases
We test against representative finance and insurance cases, review where the workflow fails and improve it until it performs reliably.
Engineer for production
We build in evaluations, controls, monitoring and clear ownership so teams can use the workflow confidently and improve it over time.
Discuss your AI priorities
Tell us which finance or insurance work you want to improve. We’ll help you decide whether training or a use-case accelerator is the right next step, and say so if neither is.
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