A Seattle AI specialist who ships into production
Search for an AI specialist in Seattle and you will find strategy firms, productized agencies, and offshore teams pitching the same chatbot. Most Puget Sound operators need something narrower: someone who sits with how the business actually runs, picks one or two AI bets that pay for themselves, and ships them into software staff can trust.
That is me. Hands-on Seattle AI consultant and implementer: custom AI development, LLM integrations, document automation, and optimization for tools you already own. Solo senior operator, 27 years, Pacific hours. Not a research lab. Not a black-box agency.
Who this is for
Operations-heavy SMBs drowning in email, PDFs, and spreadsheet handoffs that a careful AI workflow can clean up in weeks. If the handoffs are still pure Excel, start with when spreadsheets become a business liability before you buy a model bill.
Founders and product leads who want AI inside a portal, CRM, or internal tool without hiring an ML team or trading equity for a technical co-founder.
Teams mid-experiment who tried plugins, got noisy results, and need reliability, measurement, and guardrails.
Agencies that need custom AI in client delivery without building an internal AI practice from scratch.
Who this is not for
Buyers who want a 40-page AI roadmap and a workshop series. I build working features.
Companies that need full-time model research, training pipelines, and a data science org. Hire specialists or a productized ML vendor.
Anyone treating AI as a press release. If a spreadsheet formula or a plain API solves it, I will say so and save you the model bill.
What I deliver
Conversational AI that knows your business. Support bots, internal copilots, sales assistants grounded in your docs and tickets, with escalation when confidence drops.
Document intelligence. Extract, summarize, classify, route invoices, applications, contracts, and forms.
CRM and portal features. Drafts, next actions, lead scoring, account insights inside HubSpot, custom portals, and admin tools. See HubSpot integration.
Workflow steps with AI where it earns keep. Combine rules and models. Larger process design lives under workflow automation. The non-model playbook is in put routine work on autopilot.
Optimization and cost control. Prompt redesign, retrieval quality, eval sets, caching, model selection, monitoring so spend does not silently explode.
Local, on purpose
When a production prompt regresses at 2 PM Pacific, you need someone online. Seattle buyers also inherit high UX expectations from a dense tech market; a mediocre chatbot does not survive comparison. Optional in-person sessions on the Eastside often beat ten async threads. Same reason local product work tends to win for evolving systems: why Seattle businesses choose local custom software development.
| Approach | What you get | Where it fails |
|---|---|---|
| Consumer ChatGPT alone | Fast drafts | No system access, no audit trail |
| Generic AI SaaS | Quick demo | Rigid workflows, weak brand fit |
| Large AI agency | Strategy decks | Slow, expensive, junior build after pitch |
| Me (Seattle specialist) | Integrations in your stack | Scoped to ROI; you keep the code |
Engagement
- Discovery. Pain, data sources, risk, success metrics.
- Proof of concept. Thin vertical slice in 1–3 weeks.
- Production. Auth, logging, rate limits, human review, fallbacks, docs.
- Optimize. Expand only where numbers justify it.
Most SMB AI features land in weeks inside broader custom work often in the $30K–$100K range, not multi-year transformation programs. Related catalog: AI Integration Services.
Next step
Schedule a free consultation. Bring the messy workflow. I will tell you whether AI is the right fix, what it should cost, and what to leave alone.
