Straight answers on getting stalled AI into production.

I turn AI experiments into reliable systems your business can run on. Getting an AI prototype into production means turning something that works in a test into a system that is integrated, reliable, deployed, documented, and owned by someone. That is a separate body of work from building the demo: real data, failure cases, integration with existing systems, deployment, monitoring, and a handoff a new person can read. At T2C that work is Build, and it runs on the Path to Prod method: scope the problem and the definition of done, deliver and ship it, then run and measure it. The plan ends in production, not a deck.

Prototypes got cheap. Shipping them never did. Building a demo and running a system in production are different disciplines. A demo runs once, on clean data, on a happy path, with no integration, error handling, deployment, or owner. Everything it skipped is production work. A prototype stalling is not a sign anyone did a bad job. It is a sign the second job has not started.

Yes. I connect AI automation, agentic workflows, and chat systems to the data and tools your people already use. The work includes integration, controls, deployment, documentation, and measurement so the system supports a real workflow instead of becoming another silo. A defined system starts with Build.

The ClearPath Technology Map is T2C's front door: a flat $1k paid engagement, the single entry to every engagement. I audit your whole technology operation, map your systems and how work flows through them, and hand you a plan with the opportunities I see, the risks worth knowing, quick wins and bigger bets in order, and a recommended engagement. It is technology-agnostic, so if AI is not the answer I say so. It is not a sales call and it is not credited toward later work. You keep the map whether or not you engage.

Manage gives one AI initiative an accountable owner from definition to measured operation. It fits when the work crosses teams, systems, or vendors and needs ongoing prioritization, architecture, implementation, controls, rollout, and measurement. The engagement covers one initiative on a defined operating cadence. It is not staff augmentation or leadership across the entire organization.

Lead is senior, fractional AI leadership for an organization that needs direction, delivery discipline, and technical judgment without a full time executive hire. The role owns what is worth building, what production requires, how work gets reviewed and released, and who owns it once live. The deliverable is shipped software and a team that keeps shipping, not a strategy document that ends the engagement. At T2C the seat is held by someone who ran a 50 engineer, three continent delivery organization and turned it into a release train: 13 consecutive on time releases, defects down from about 170 to under 60.

Every engagement starts with the ClearPath Technology Map, a flat $1k, which maps your operation and gives you the exact number for the work it recommends. After that, pricing is floor only, with no fixed per-engagement tag: focused builds start around $2k as a project, and ongoing partnerships (Manage and Lead) run as monthly retainers. Scope and outcome set the price, and the Map is where the scope gets settled.

Tim Gemoll, directly. You work with the same senior, US based engineering leader from the first conversation through delivery, with no handoff between the person who understands the problem and the person accountable for solving it. That is 20 years on the delivery and operations spine, including running a 50 engineer organization across three continents, and production AI running today, including the AI receptionist that answers T2C's own phone at (262) 333-3510. The person who scopes the work does the work and answers the email.

Path to Prod is the delivery method every T2C engagement runs, at any depth. Scope: agree on the problem, the boundaries, and the definition of done before work starts (the ClearPath Technology Map is where Scope begins). Deliver: build it and ship it. Run: monitor it, measure whether it moved the number, and keep it working. The method gives the buyer a visible path and clear status from definition through operation.

T2C ships production AI systems that work inside real business operations, and leads teams to keep shipping them. It is not a generalist web shop, a staffing agency, or a strategy practice that ends in a deck. It does not build surveillance tooling or automation whose purpose is to replace people rather than make them more capable. If the work is not about getting real AI into production and keeping it there, it is not a fit, and you will hear that on the first call rather than three weeks in.