Fintech systems where the ledger is always right.
Payments, lending, and banking products where every transaction reconciles and every action is traceable. For fintech companies and finance teams that need software to be correct first and fast second.
Who we work with in Fintech & Banking
- A payments or lending product moving from a prototype to real money movement.
- A neobank or wealth platform that needs a mobile app customers trust with their balance.
- An onboarding flow losing customers to manual KYC checks and slow reviews.
- A finance team reconciling by spreadsheet across a growing number of providers.
What slows Fintech & Banking down, and what we build for it
Four problems we see in nearly every Fintech & Banking engagement. Pick one to see how we approach it and what you would have at the end.
The problem
Balances drift from the payment provider, retries create duplicate transfers, and month-end reconciliation is a spreadsheet exercise nobody trusts.
How we approach it
A double-entry ledger as the source of truth, idempotent payment APIs so a retry can never move money twice, and reconciliation that runs every night and pages someone when it fails.
What you get
- Double-entry ledger with immutable entries
- Idempotent payment and transfer APIs
- Nightly reconciliation against provider reports
- Discrepancy alerts with a review queue
A typical Fintech & Banking scope. Tick what you need.
The artefacts most Fintech & Banking projects end up with. Tick the ones yours needs and send the list with your enquiry; we reply with a written scope in your vocabulary.
Related reading
- LLM application architecture: the layers that don't change with the modelModel, harness, data layer, and product surface: the four layers of a production LLM application, and which ones survive the next model upgrade.
- RAG vs fine-tuning: what should your business use?They get pitched as competitors and usually are not. How to tell which problem you actually have, and the cases where the right answer is both.
- LangGraph vs CrewAI vs AutoGen: a practical comparisonThree popular agent frameworks, compared on what actually differs in production: control over the loop, debugging, and how much they decide for you.
Questions Fintech & Banking clients ask
Which payment providers do you work with?
Stripe, Adyen, Checkout.com, and the open-banking providers in your market. We keep card data out of your systems through tokenisation so PCI scope stays small.
Can you build a ledger, or should we buy one?
Both are reasonable. For simple products a hosted ledger is faster; for products where the ledger is the business, we build a double-entry ledger you own. The scope call ends with a recommendation and the reason.
How do you handle regulatory requirements?
We design for the rules your compliance team names in the scope: audit trails, retention, access control, and evidence generation. We do not give regulatory advice; we build the controls your advisers specify.
Can AI be used in onboarding or fraud detection?
Yes, for scoring and triage, with rules that can be explained to a regulator and a reviewer deciding every case the model is unsure about. Every model decision is logged with its inputs.
Tell us what you are building.
We reply within one business day with how we would build it, what it would cost, and which engagement model fits.
- 01Tell us what you are building
A short form or an email. No deck required, and "not sure yet" is a fine answer.
- 02A call with an engineer
Within one business day. Technical questions get technical answers, from the person who would build it.
- 03A written scope and quote
Fixed price where the scope is defined. The document is yours whether or not you go ahead.