RAG over your data for Fintech & Payments.
Retrieval-augmented generation grounded in your internal corpus — vector search, hybrid retrieval, chunking strategies that preserve meaning. Applied to retail trading, cashback, payment rails, kyc, escrow and payouts — the engine room beneath modern consumer fintech.
Production AI, not demoware.
Retrieval-augmented generation grounded in your internal corpus — vector search, hybrid retrieval, chunking strategies that preserve meaning. We wrap it in the evals, observability and cost ceilings that make rag over your data viable for fintech & payments operators — not just impressive in a demo.
- Multi-model routing (GPT-5, Claude 4.5, Gemini 3)
- RAG grounded in your data
- Cost ceilings and rate-limit handling
- Offline + online evals
- PII redaction and safety layering
- Full observability on every LLM call
FAQ
Can Origami build rag over your data for fintech & payments?+
Yes. Origami has been shipping rag over your data for fintech & payments operators since 2020. We ground every AI feature in real product surfaces — no demoware.
Which models do you use?+
We are multi-model. Typical stacks include OpenAI GPT-5, Anthropic Claude Sonnet 4.5, and Google Gemini 3 — routed per workload with cost ceilings and evals wrapped around every call.
How do you handle data and privacy for Fintech & Payments?+
RAG-grounded, tenant-isolated retrieval; PII redaction where required; regional processing where regulations demand it; and full observability on every LLM call.
How quickly can we go live?+
A scoped rag over your data pilot typically ships in 4–8 weeks. Production hardening (evals, rate limits, cost caps, monitoring) is another 2–4 weeks.