Software, AI, and cloud engineering for fintech.
Payments, lending, wealth, and embedded finance.
How we work in fintech.
FinTech teams operate under constraints that most generic software shops underestimate — regulatory, operational, or commercial. We have shipped enough in this sector to know which corners can be cut and which cannot.
Every engagement begins with mapping those constraints explicitly. From there we build in production-shaped slices, with the security, compliance, and observability posture you will eventually be audited against in place from week one.
The non-negotiables are part of the architecture.
Compliance
KYC, AML, payments, and lending controls are encoded into release criteria and operational runbooks.
Latency
Authorisation, decisioning, and servicing paths get SLOs because delays quickly become financial risk.
Auditability
Money movement, approvals, model decisions, and customer communications are reconstructable for review.
Data security
Financial data, credentials, and partner API access are protected through strong identity and segmented tenancy.
User adoption
Risk, operations, and customer teams get interfaces that reduce manual exceptions instead of hiding them.
A pragmatic path from discovery to production.
We avoid theatre by shipping one auditable, observable workflow first, then using real adoption and operating data to guide the next slice.
Map
Make constraints explicit
Document the journeys, systems, controls, and metrics that decide whether the work is safe to ship.
Slice
Build the first production path
Deliver one valuable workflow end to end with integrations, security, telemetry, and support in place.
Scale
Expand with evidence
Use adoption, latency, quality, and business metrics to decide what to automate or modernise next.
Software patterns we see repeatedly in fintech.
Payment orchestration
Lending cores
Risk and decisioning platforms
Customer servicing portals
We choose stacks for reliability, hiring depth, integration fit, and long-term ownership.
PostgreSQL
Ledger data
Kafka
Events
Terraform
Controls
Datadog
SLOs
The capabilities most often combined for fintech teams.
A representative outcome, not a vanity demo.
We anchor industry work to measurable operational, commercial, and adoption outcomes.
Replatforming a Series C lending core without a single missed disbursement
Series C consumer lender
Strangled a ten-year-old PHP monolith and migrated 1.2M live loans onto an event-driven core, with zero downtime and a 60% drop in P95 latency.
- P95 latency
- −62%
- Disbursements lost
- 0
- Cutover window
- 9 months
What we typically deliver.
Custom platforms
Core systems built around how your operations actually work, not a vendor template.
AI & data products
Models and pipelines that survive contact with production, with the evaluation harness to prove it.
Cloud & platform
Landing zones, replatform projects, and developer platforms tuned for your compliance footprint.
Modernisation
Strangler-pattern moves off ageing systems, with measured cutovers and no big-bang surprises.
Security & compliance
Secure SDLC, threat modelling, and audit-ready evidence baked into delivery — not bolted on.
Embedded teams
Senior engineers and SREs embedded with your team for the time it takes — and not a day longer.
Ready when you are
Talk to a fintech engineer.
A senior engineer with industry experience will follow up within one business day.