AI Development in Seattle.
We build AI systems for Seattle companies. Custom AI agents, LLM integrations, and automation built into your business. As a remote-first studio, we work with Washington businesses the same way we work with clients anywhere in the US.
[ AI Development in Seattle ]
Seattle companies do not need an AI pitch, they need implementations that survive technical scrutiny in the most cloud-literate city anywhere. We build LLM systems with retrieval over your own data, evaluation pipelines, and private deployment in your AWS accounts, for tech firms clearing internal backlogs and for the maritime, manufacturing, and health organizations whose document loads dwarf their tooling.
Seattle evaluates AI the way no other market can, with people who built the underlying platforms sitting in the room. Demand splits in two here. Tech companies around Amazon and the broader cloud economy hold AI initiatives their product engineers cannot get to, integrations and internal assistants stuck behind roadmap priorities. Meanwhile the city's older economy, marine services around Fishermen's Terminal, aerospace suppliers carrying Boeing's paperwork legacy, health organizations in the orbit of UW and Fred Hutchinson, moves staggering volumes of documents through processes that have barely met software, let alone language models.
Init One Solutions builds AI systems designed to survive Seattle scrutiny: retrieval over your own data with citations, evaluation pipelines that measure behavior before launch instead of after an incident, and deployment inside your own AWS accounts so nothing sensitive leaves your tenancy. For document-heavy operators we build extraction pipelines that turn settlement sheets, quality records, and grant paperwork into structured data. We work remotely on Pacific time, which in this city mostly means we behave like the distributed teams Seattle companies already run, with the difference that our roadmap is yours.
[ Sectors we build for ]
- cloud & enterprise software
- aerospace & manufacturing
- maritime & fishing
- global health & biotech
- ports & trade
- retail & consumer brands
[ What we build ]
AI Development for Seattle
Private LLM deployment and document extraction match a Seattle economy split between cloud-fluent tech firms and maritime, aerospace, and health organizations drowning in operational paperwork.
- Custom AI agents and assistants trained on your data
- LLM integration with retrieval and guardrails
- Document processing and data extraction
- Workflow and process automation
- Private, secure deployment in your own cloud
[ More for Seattle businesses ]
Custom Software Development in Seattle
Full-stack web applications, platforms, and internal tools built to fit your business.
Web Development in Seattle
Fast, modern websites and web apps engineered for performance and search.
Cloud Infrastructure in Seattle
Serverless AWS architecture, CI/CD, and integrations your team can maintain.
Mobile App Development in Seattle
Native and cross-platform mobile apps built for performance.
[ Working with us from Seattle ]
Where do the models actually run, and can we keep everything inside our own AWS account?
Inside your account is our default, not an upsell. Retrieval indexes, orchestration, and where feasible the models themselves run in your AWS tenancy, using Bedrock or self-hosted options depending on requirements. For Seattle companies whose security teams grew up at the cloud providers, we document every data path and expect the review to be thorough.
Our documents include fishing settlements and vessel records going back decades. Is that usable?
Usually yes, and it is often the highest-value data in the building. We build extraction pipelines that handle scans, faxes, and inconsistent formats, validate results against known fields, and flag low-confidence pages for a human. Seattle's maritime firms sit on operational history that answers pricing and planning questions, once it stops living in filing cabinets.
How do you prove an AI system works before we put it in front of Seattle engineers?
With evaluations, not demos. We build test sets from your real questions and documents, measure accuracy and refusal behavior on every change, and share the numbers. When your staff includes people who have shipped ML systems, and in Seattle it often does, the review conversation is about metrics we brought, not vibes.