Fintech AI development for US lenders, payments, neobanks, and wealth platforms.

No, and we would not pretend to be. Aiinfox is an AI development company; we are not a registered investment adviser, broker-dealer, money services business, lender, mortgage originator, or any other regulated financial entity under federal or state law. What we do is build AI systems for regulated firms in a way that respects the firm's regulatory perimeter — SOC 2-aligned engagement controls, audit logs your CFPB and FINRA examiners can read, deterministic mode for regulator-facing decisions, refusal layers on out-of-scope queries that could constitute regulated activity, and human-in-the-loop patterns wherever ECOA, FCRA, Reg B, Reg E, Reg Z, or FINRA conduct rules expect a human owns the decision. We work alongside your compliance function, your BSA officer, and your CCO; we do not replace any of them.

Honest answer: Aiinfox does not currently hold a SOC 2 Type II report as an organization. What we provide is engagement-level alignment: the controls applied to your build are SOC 2-aligned and mapped to the Trust Services Criteria your auditor cares about — CC6 logical access, CC7 system operations, A1, C1, and PI1 where customer data routes through the model. Your CISO can drop our work into your existing Type II scope without re-engineering the posture. If your procurement contract requires a vendor with its own Type II report, we will tell you on the first call and recommend a vendor who has one. Wasting your timeline on a posture we cannot meet is not in either of our interests.

The MSA covers IP assignment (your code, your IP), capped limitation of liability, mutual indemnification, confidentiality, subprocessor obligations, audit rights, and the 30-day production warranty. The SOW covers scope, acceptance criteria, six-week timeline, USD fixed price, and the specific Trust Services Criteria and regulatory frameworks (CFPB, NY DFS Part 500, FINRA) the engagement is aligned to. The DPA covers processing instructions, security controls, breach notification timing tied to your 72-hour NY DFS clock where applicable, and deletion or return of customer data at the end of the engagement. All three are signed before any code is written or customer data is shared. We work from your templates or provide ours.

Inside your AWS, Azure, or GCP account by default, in a US region you specify — us-east-1 (N. Virginia), us-west-2 (Oregon), or any region your existing SOC 2 boundary covers. For inference: one, managed LLMs pinned to US regions — Anthropic Claude via AWS Bedrock with US endpoints, OpenAI via Azure OpenAI Service with US endpoints. Two, self-hosted Llama 3 or 3.1 on vLLM inside your VPC with autoscaling GPU groups — zero third-party LLM exposure, full control of logging and retention, the default pattern for any deployment touching SSN, full bank account numbers, or other high-sensitivity PII. Three, hybrid — non-customer-data prompts route to managed LLMs, PII-bearing prompts route to self-hosted Llama. We do not silently introduce a new subprocessor your CISO has not approved.

Yes, and for adverse-action outputs it is the default. For credit denials, account closures, payment freezes, and any model output that becomes evidence in a Regulation B notice or a CFPB enforcement file, we run the LLM in deterministic mode with temperature=0, pinned model version, pinned prompt version logged per output, and pinned retrieval sources. The same input plus the same model version plus the same prompt always produces the same output, and the full chain is reproducible from the audit log months or years later. The structured output includes specific reason codes your compliance team reads directly into the adverse-action notice template — not free-text the consumer compliance attorney has to re-engineer for clarity and completeness under the rule.

Where the engagement is under a New York DFS-supervised entity, the engagement defaults shift. Multifactor authentication is required on every access path. Encryption is mandatory in transit and at rest with customer-managed KMS keys. The incident notification path is wired into your 72-hour reporting clock to the Superintendent of Financial Services and you have the evidence pre-staged for the notification. Annual cybersecurity attestation evidence — risk assessments, access reviews, training records — is wired into the build's standard control output so your CISO is not chasing artifacts the week the attestation is due. The CISO role on your side owns the program; we provide the engineering substrate that makes the controls demonstrable rather than declarative.

Yes — examiner-aware takeovers are routine. Step one is a regulatory data-flow audit: where does customer data actually touch storage, inference, and logging, and which of those endpoints is inside your existing SOC 2 boundary versus a new uncovered subprocessor your CISO has not approved? Step two is reading the code, prompts, evals (if any), refusal layer, audit-log schema, and the deterministic-output guarantees (if any) for adverse-action and other regulator-facing outputs. Step three is shipping the smallest valuable change that does not expand your audit scope, then the longer-term plan. Most takeovers we see did not need a full rewrite; they needed an examiner-readable audit log, a refusal layer on out-of-scope queries, and deterministic mode wired into the Reg B path.

Senior engineering rates at Aiinfox land roughly 30 to 50 percent below equivalent US fintech AI consultancies — useful, but it is not the headline. The headline is the delivery model: senior engineers only, fixed-price six-week scope, overrun cost on us if we miss for reasons on our side, MSA + SOW + DPA in hand before kickoff. Most US fintech AI consultancies bill timesheets, run multi-month discovery while the SOC 2 audit window slips, and either churn senior staff onto bigger accounts or staff a junior pool behind a senior nameplate. We bill shipped systems; the engineer on your kickoff call writes your code through launch. Most v1 US fintech AI engagements at Aiinfox land between $40,000 and $180,000 fixed-price depending on integration depth and regulatory scope.