Fintech engineering capabilities
Regulated cores, market data and brokers, and how AI has to fit them.
AI for financial products only works when it respects the system of record and shows where its numbers came from. These are the systems we have worked with and how the team works.
The team
Who builds it.
Product and workflow analysis
Business analysts who write each user flow out step by step and confirm which fields fill themselves, and from where, before building.
AI engineering
Agents with tools, document extraction, retrieval with citations and knowledge graphs, evaluated on your own cases.
Platform engineering
Services beside .NET and other cores, roles for admins, issuers, investors and sub-clients, plans gated on the server.
Data engineering
Pipelines for prices, fundamentals, filings, news and social data, with scheduled jobs for slower sources.
Systems
Systems we have worked with.
Built in client products. We scope yours in the Product Review.
| Area | Systems |
|---|---|
| Core systems | .NET and SQL Server cores reached through APIs, with Python and FastAPI services beside them |
| Broker | Robinhood, connected only with the investor's consent |
| Prediction markets (data) | Kalshi, Polymarket |
| Market data | Financial Modeling Prep, Yahoo Finance, news and filings APIs, posts from X, Reddit and StockTwits, macro indicators |
| Sign in and billing | Clerk sign in, Stripe billing |
| Cloud and AI | AWS and Azure, Azure OpenAI and OpenAI models, Azure AI Search, Neo4j with LlamaIndex, Perplexity for web research |
How the team works
One team across product, AI, platform and data.
A named lead engineer and US-hours overlap, from the first Product Review to production.
Every engagement
- We add AI beside your core and never rebuild the system of record.
- Every change goes through your pull request review and a separate QA environment.
- We verify inherited code on a live run before we change it.
- We work in your AWS or Azure accounts, with access you grant and can revoke.
See it on your own platform.
Bring one product, workflow or AI feature. In 30 minutes we tell you which of the three ways to start fits, what it would cost to serve per user and what your compliance team will ask.
Calls run in US Central time. No generic AI presentation: we discuss your product, users and production constraints.