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AI Integration Services in San Francisco, CA

San Francisco is the most technical AI buyer market in the country. Every founder is one degree from a senior AI engineer. Every CTO has shipped LLM features before. Contract pitches that lean on AI buzzwords die fast on the technical screen. What survives is engineering depth — eval-first prompt development, clean abstractions, and the ability to ship.

The problem with off-the-shelf AI in San Francisco

Bay AI buyers see through demoware fast. The competition is in-house engineers and ex-FAANG ML leads. The partner that wins has to clear a technical bake-off the same week they pitch.

Real AI integration means picking the right model for the right step, wiring it into your existing data layer, and building eval-first so prompt regressions get caught before they reach production. For San Francisco buyers specifically, that means AI shaped for peer-credible AI integration — not a generic chatbot.

What we ship for San Francisco buyers

Eval-first prompt development

Real test sets scored against real customer data, with regression runs on every prompt change.

LLM-vendor-agnostic abstractions

Clean module boundaries between OpenAI, Anthropic, Bedrock, Azure, and open-source providers.

Cost + latency budgets

Per-call cost and latency budgets enforced at the integration layer.

Algorithmic-ops integration

We build trading bots — low-latency inference wired into operator dashboards is in our DNA.

Tech stack

OpenAI (GPT-4 class)
Anthropic Claude
AWS Bedrock
Azure OpenAI
Ollama / vLLM
Postgres + pgvector
TypeScript
Next.js 15
Docker

LLM-vendor-agnostic abstraction so you can switch providers without a rewrite. Postgres + pgvector for RAG.

Reference builds

Bay-relevant AI reference work spans operations platforms (J5 Sales OS, UEhub), trading systems (TypeScript/Node broker integrations), and the AI features across our portfolio. Technical bake-offs work in our favor — code walk-through or live architecture session on request.

Reference work: J5 Sales OS, contractor estimating engine, and multi-strategy trading system.

How we work remote from Georgia

QUANT LAB USA is founder-led from Macon, Georgia. William Beltz runs every AI engagement from kickoff through handoff. Discovery is a structured workflow-mapping session; eval-first prompt development from week one; staging is live from week two.

For San Francisco buyers, that means full Eastern-time overlap, fixed-scope contracting against milestones, and on-site work when scope warrants. Book a scope call to walk through your workflow.

Pricing for San Francisco AI integration

SF AI engagements typically scope between $30,000 and $135,000 for a production-grade integration with senior-engineering bake-off included.

We quote fixed-fee scope after a 30-minute discovery call. Engagements include the integration code, eval test sets, prompt versioning, and runtime cost-and-latency budgets. Source-code handoff at delivery. See our parent AI service page for the broader engagement model.

What you get

  • Full source code repository (yours, no lock-in)
  • Prompt library + eval test sets
  • LLM-vendor-agnostic abstraction layer
  • Cost + latency budgets at integration layer
  • Audit logging on AI workflow events
  • 30-day post-launch support included

San Francisco AI integration FAQ

Technical bake-off?

Yes.

Quant-adjacent AI?

Yes.

Pacific time overlap?

Morning through early afternoon.

Eval-first prompt development?

Yes — real test sets, regression runs.

Closed vs open-source?

Depends on workflow.

Who owns the prompts and code?

You do.

Ship a real AI integration in San Francisco.

Call William Beltz directly at (770) 652-1282 or book a 20-minute scope call. Founder-led from quote to handoff.