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AI Integration Services in Seattle, WA

Seattle is anchored by Amazon and Microsoft, with a deep SaaS and dev-tools ecosystem and a steady current of bootstrapped founders. Most companies here speak fluent cloud — what they want from an AI partner is Docker-native, cloud-portable, API-first AI integration that does not lock them into a specific LLM vendor.

The problem with off-the-shelf AI in Seattle

Generic AI shops bring vendor SDKs that lock you into a specific model provider and a specific cloud. Seattle technical buyers want LLM-vendor-agnostic integration — clean module boundaries, documented endpoints, no lock-in.

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 Seattle buyers specifically, that means AI shaped for dev-tools and cloud-native AI integration — not a generic chatbot.

What we ship for Seattle buyers

LLM-vendor-agnostic integration

OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, and open-source via Ollama or vLLM — all addressable through a thin abstraction layer.

Docker-native AI deployment

Container-first AI integration that drops into AWS, GCP, Azure, or your own Kubernetes.

API-first AI surface

Every AI workflow is a documented REST or GraphQL endpoint. Your dev tools and SaaS product call it like a peer service.

IAM-grade access for AI

OIDC, SAML, fine-grained RBAC on AI endpoints.

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

Seattle-relevant AI reference work includes operations platforms (J5 Sales OS, UEhub) and developer-tool patterns we ship — Docker-native deploys, OpenAPI-documented endpoints, vendor-agnostic LLM abstractions. The architecture meets what a Seattle-grade engineering reviewer expects.

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 Seattle 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 Seattle AI integration

Seattle AI engagements typically scope between $25,000 and $110,000 for a production-grade integration. 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

Seattle AI integration FAQ

AWS Bedrock or Azure OpenAI?

Yes, both supported.

AI as a peer service?

Yes — every workflow is a documented endpoint.

Pacific time overlap?

Morning through early afternoon Pacific from a Georgia HQ.

Bake-off against in-house engineers?

Yes.

SAML/OIDC on AI endpoints?

Yes.

Who owns the prompts and code?

You do.

Ship a real AI integration in Seattle.

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