AlliCrew is a small Seattle practice building AI systems for specialty and engineered-to-order manufacturers across the Pacific Northwest. We focus on engineering knowledge, customer documentation, service support, and cross-system handoffs.
Taking on a limited number of engagements in 2026 · First call is 30 minutes, no deckSpecialty and engineered-to-order manufacturers accumulate years of engineering decisions, customer requirements, prior configurations, and service history. The knowledge is there — it just lives across drawings, file shares, ERPs, service records, project folders, and long-tenured people.
We build AI systems that make that knowledge usable inside the work your team already does: sizing new configurations, drafting customer documentation, supporting service calls, coordinating handoffs from quoting to shipping.
The hard part isn't the AI. It's the engineering that makes it work in your environment.
Anyone can wire up a chatbot. Four things separate working systems from demos that fall apart:
Turning your engineering files, archives, and documentation into something an AI can reason over reliably. Most projects succeed or fail here.
Connecting agents to the systems your people actually use — ERPs, file shares, project tools — so the work moves through your operation, not around it.
Making sure agents do what they're supposed to and stop when they shouldn't. Critical in regulated environments where mistakes are expensive.
What the agent decides, what gets escalated, what a person reviews — defined upfront. Agents do the work; a person stays accountable for it.
This is platform engineering work, not chatbot work. The difference is what makes the system useful after the demo.
Most first engagements take one of these four shapes.
An agent that searches prior projects, drawings, customer requirements, service notes, and configuration history — so engineers see how similar problems were solved before, while they're working, not three days later.
Your engineers stop re-deriving things you already know.
An agent that drafts customer-specific proposals, specifications, validation documents, manuals, or compliance packets from your existing engineering data — leaving your people to review and refine, not start from blank pages.
Your team stops being the bottleneck on documentation cycles.
An agent that finds the right manual, part, drawing, prior fix, or customer history while the technician is on the call — pulling from the engineering archive and service records, not from memory.
Service answers happen on the first call instead of the third.
An agent that watches work move from quoting to engineering to scheduling to production — flagging missing inputs, stuck decisions, and handoffs that need attention before they slow things down.
Work moves through your operation instead of waiting on someone.
Most engagements start with one of these. Some end there; others reveal the next useful system to build.
The most useful engagements often start as something a founder, CEO, or CTO has been carrying around in their head for months. If that's you, this is the conversation we're best at.
You describe the operational problem. We share an honest read on whether AI is the right tool for it, and whether there's a project worth doing.
We spend time with your team, look at the data, find where the leverage actually is, and come back with a written proposal — what we'd build, how, and what it would cost. You can stop there.
We design the system, integrate it with the systems your team uses, test it on real data, and walk your team through how it runs. You own what we build.
Some projects end cleanly. Some reveal the next useful problem to solve. When continued involvement makes sense, it's a focused retainer or a separately scoped follow-on — never a default.
We use the right AI platform for each job — Claude, GPT, Gemini, and others when appropriate. The model is rarely the hard part.
The hard part is preparing the knowledge, connecting the systems, defining the guardrails, and making the output reliable enough for real operational use. That's where our technical depth lives.
Each engagement is scoped to the work. We figure that out together in the scoping phase, before you commit to anything.
The scoping engagement produces a written proposal — what we'd build, how, and what it would cost. You can stop there.
You own the systems we build. No vendor lock-in. Continued involvement only when both sides want it, never as a default.
AlliCrew brings twenty-five years of enterprise platform engineering experience — across Accenture, Cognizant, Deloitte, Infosys, PwC, Tata Consultancy Services, and Wipro. Today, that experience is focused on agentic AI for industrial manufacturers.
The work has always been about making technology run inside real businesses — real data, real users, real accountability for outcomes. The "Crew" in AlliCrew is the AI agents we build for you. We work with a small number of clients at a time, close enough to meet in person.
No pitch deck, no pressure. A 30-minute conversation about the operational problem you've been thinking about — and an honest read on whether AI is the right tool for it.
We reply personally, usually within one business day.