◆ AI / LLM APPS × FINTECH

AI / LLM apps development for fintech

We build LLM products that ship — not chat demos. Cost ceilings, fallback paths, evals, observability, and a real moat beyond the prompt. Tuned for fintech — Payments, lending, custody, neobank rails, embedded finance. Engineered for regulated environments — FCA, FinCEN, MiCA, MAS.

◆ WHY MIR

Why teams pick us

Fintech-grade engineering

Payments, lending, custody, neobank rails, embedded finance. Engineered for regulated environments — FCA, FinCEN, MiCA, MAS.

AI / LLM apps where it counts

We build LLM products that ship — not chat demos. Cost ceilings, fallback paths, evals, observability, and a real moat beyond the prompt.

Senior team, no pyramid

9+ years building outsourced product teams. Every engineer is a senior shipping production code — not a 5-person team with one architect on top.

◆ FINTECH PAIN POINTS WE SOLVE

Where AI / LLM apps meets fintech

Double-entry ledgers that survive audits

We've shipped this in production. We design for it from day one — not as a retrofit.

Idempotent payments + reconciliation

We've shipped this in production. We design for it from day one — not as a retrofit.

KYC/KYB integrated without UX collapse

We've shipped this in production. We design for it from day one — not as a retrofit.

Regulator-ready audit trails

We've shipped this in production. We design for it from day one — not as a retrofit.

◆ STACK

What we build with

OpenAI Anthropic Claude Vercel AI SDK LangChain / LlamaIndex (when justified) Postgres + pgvector Inngest / Trigger.dev Braintrust / Langfuse evals
◆ PROCESS

How we ship

  1. Define the eval set before you write the prompt.
  2. Ship a thin vertical slice in week 1 to learn the real failure modes.
  3. Add cost ceilings, retries, and human-in-the-loop where reliability matters.
  4. Instrument every call — latency, tokens, $, eval pass-rate.
◆ START A PROJECT

Tell us what you're building

We respond within 24 hours. NDA available on request.