AI development company for San Francisco SaaS, AI startups & healthtech.

We do not operate a Bay Area office. Aiinfox runs from our Mohali, India HQ and a Frisco, TX office. For SF clients that need Pacific business-hours coverage, our Frisco pod runs a US-Hours rotation on a late-CT shift that covers PT 9am-to-6pm with senior engineers live on Zoom, and the Mohali team picks up SF afternoons via an early-IST start. For on-site engagements (kickoff, milestone reviews, security walk-throughs), we travel to SF on a scheduled cadence rather than maintaining a sub-scale local team at Bay Area rates.

Honest answer: yes, with a planned shift. Our Frisco, TX office runs Central Time — two hours ahead of Pacific — so our default 9am-to-5pm CT only covers your morning. For SF clients we run a US-Hours rotation: a late-CT shift (typically 11am-to-8pm CT) covers PT 9am-to-6pm on Zoom in full. Twice-weekly demos run in PT business hours; written async updates land before your SF standup; the senior engineer on your kickoff is the senior engineer through launch. If your engagement genuinely cannot survive without a Bay Area-based team on the ground at all hours, we will tell you on the first call and recommend a local consultancy.

Yes. Our engagement defaults are aligned with the California Consumer Privacy Act and the California Privacy Rights Act amendments. DPAs are signed before any personal information is shared; data-subject rights workflows (access, deletion, correction, opt-out of sale or sharing) are mapped at scope; audit logs on every model and tool call are exportable for a California Privacy Protection Agency inquiry. For SF clients with operations in multi-state SaaS, we map the CCPA + CPRA controls in parallel with NY SHIELD, NY DFS Part 500 where financial services apply, and the Colorado / Virginia / Connecticut state privacy obligations — one audit-log schema, multiple regulator-facing exports.

Your call. We default to AWS US-West-2 (Oregon) for SF clients because it is the lowest-latency west-coast region with full AWS service coverage, with US-West-1 (N. California) as a second region option when California-only residency is a customer ask. We will run inside your AWS, Azure, or GCP account in any US region you specify. For inference, Claude (Anthropic) and GPT-4o (Azure OpenAI) have US-West endpoints we route to explicitly; for AI-first startups with strict no-third-party-API positioning, we self-host Llama 3 on vLLM inside your VPC with zero data egress to non-customer endpoints. Your DPA spells out the exact data path.

Yes. We work with MSA-plus-SOW structures for ongoing engagements and single-document fixed-price agreements for pilots. Standard terms cover IP assignment (your code, your IP), limitation of liability tuned to scope, indemnification, data handling, breach notification, and a 30-day production warranty. NDAs are mutual and signed before any technical detail is shared. BAAs are signed before any PHI is shared. We are a registered Indian entity (Aiinfox Pvt. Ltd.) invoicing US clients in USD via wire transfer as a foreign corporation — no W-9 or 1099 entanglement on your side.

Yes — takeover audits are routine. Step one is reading the code, the data pipelines, the eval results (if any exist), the prompts, and the cost telemetry. Step two is shipping the smallest valuable change to prove we understand the system in a way the previous vendor did not. Step three is the longer-term plan — incremental stabilization, a parallel rewrite, or shutting it down and starting over. We will be honest on the first call. Most Bay Area takeovers we have seen did not need a full rewrite; they needed evals, guardrails, observability, and a senior engineer who stayed on the build past the discovery phase.

Senior engineering rates at Aiinfox are roughly 50 to 70 percent lower than equivalent SoMa, Mission, Mid-Market, or Peninsula AI consultancies — real, but it is not the headline. Most Bay Area AI consultancies bill at $400-to-$700 per hour on timesheets, run multi-month discovery phases, and either burn a junior pool behind a senior nameplate or lose senior staff to a foundation-model lab mid-engagement. We bill shipped systems on a fixed-price six-week scope; the senior engineer on your kickoff call stays on the build through launch; the overrun cost is on us if we miss for reasons on our side. SF clients typically save 60 to 75 percent on equivalent scope while getting the senior engineer in every standup.

A working v1 in production six weeks after kickoff, with evals, guardrails, observability, and audit logs wired in from week one — not retrofitted after launch. For SF SaaS scale-ups, success is typically a shipped AI feature embedded in the product that moves a customer metric and survives security review at enterprise buyers. For AI-first startups, success is a fine-tuned model or RAG pipeline that clears a custom eval bar at production latency and cost. For SF healthtech, success is a BAA-covered RAG or ambient scribe with zero policy-violating answers in 90 days of production traffic. We measure against your acceptance criteria, written into scope before kickoff.