For Fintech Operators

Per-employee AI stack for compliance-blocked teams. Compliant-AI architecture review before model risk says no.

Fintech operators (B2B payments, embedded finance, neobanks, lending platforms) get caught in a specific bind: your eng team wants to ship AI features fast, but your CCO/legal team blocks ChatGPT for customer data. We architect the compliance-safe stack that lets you ship.

Run a free audit for your firmBook a 20-min scoping call

What we'd ship for you

Specific tools we build for fintech operators firms.

Not generic AI consulting word salad. Concrete, named deliverables with integration points, ship timelines, and expected impact.

1

Compliant AI Customer-Support Stack

~21-day ship

What it does: End-to-end AI stack for customer support: PII-scrubbing pre-processor → Claude classification + response drafting → confidence-scored auto-send for routine, human-routed for sensitive → full audit log.

Why this for you: Fintechs need AI in support but can't paste customer financial data into ChatGPT. Custom stack solves the compliance angle.

Integrations

Zendesk / Intercom / FrontClaude API via private computePII detection layerAudit log to S3 with retention

Expected impact: Support team capacity 2-3x; ticket cost down 40-60%.

2

Token Cost Optimization Audit + Implementation

~14-day ship

What it does: We audit your firm's current Anthropic/OpenAI spend, identify the 5 highest-impact savings (prompt caching, model downselection, batching), and implement them.

Why this for you: Most fintechs running AI at scale waste 40-60% of their token budget. The audit pays for itself in the first 60 days.

Integrations

Anthropic / OpenAI / Azure usage dashboardsYour existing prompt repo

Expected impact: Typical fintech: 40-60% spend reduction.

3

Model Risk Documentation Generator

~14-day ship

What it does: For each AI feature you ship, AI generates a model card, validation report, monitoring plan, and change log in your firm's required format — so your CCO can review faster.

Why this for you: Model risk doc burden is real and slow. Templating it (with audit trail) cuts the approval cycle.

Integrations

Your model registryClaude with NIST AI RMF as contextPDF / Confluence export

Expected impact: Model risk approval cycle: 6 weeks → 3 days.

Regulatory frameworks we map to

Every build comes with compliance documentation tied to the frameworks your firm is examined against.

  • Money transmitter licensing requirements
  • GLBA + UDAAP
  • NIST AI RMF 1.0
  • SOC 2 Type II / ISO 27001
  • PCI DSS for card data

Common tooling we wire into

We integrate with the systems your team already opens every day — not yet-another-dashboard.

  • AWS / GCP / Azure cloud
  • Anthropic / OpenAI / Cohere
  • Datadog / Splunk (observability)
  • Snowflake / BigQuery (data warehouse)

How fintech operators firms typically engage

  • Token cost audit + 1-quarter savings implementation
  • Production AI feature stack with private compute + compliance layer

Every engagement starts with a free AI audit + a 20-minute scoping call. We quote fixed-price after we understand your firm's actual workflows and regulatory environment.

Ready to ship AI in fintech operators?

Start with a free audit — we'll show you exactly what we'd build for your firm with dollar-recovery math and a 14-day timeline. No call required.

Run free auditBook a scoping call