We remove friction.

// THREE DECISIONS THAT DECIDE IT

1. Test the hard part first. Before any infrastructure, point an AI at a real piece of the work — an actual document, ticket, or record — and ask it to do the step. Imperfect output is still proof the core is possible. Validating the foundation before the scaffolding saves months.
2. Build the evaluator before the features. An agent that scores output against known-good examples is the highest-leverage thing in the project. Every improvement after it is measurable instead of guesswork.
3. Keep knowledge out of code. Business rules, domain vocabulary, and customer-specific formats belong in Markdown, not source. A rule change becomes a file edit — no deployment, no collateral breakage. The AI reads Markdown as fluently as Python.

// WHAT CLOSES THE LAST STRETCH

The distance between mostly-right and dependable is rarely a better model. It is the right data plus a real fallback strategy. When a lookup fails, the agent follows a defined escalation path — search the raw files, scan history for similar cases, re-read the original input. Not improvising: following auditable instructions with direct file access.

// WHAT GOOD LOOKS LIKE

// WHAT WE’D TELL YOU

Build the evaluator in week one, not month two. Design knowledge separation into the first architecture, not the second. Don’t confuse “the AI is smart” with “the system is reliable” — reliability comes from structure, not capability. The AI is a powerful primitive; the system design is the hard part.

The same shape fits any repetitive toil — invoices, support tickets, contracts, forms, data entry, reconciliation, routine reports. If something in your organization is still manual because “it’s too complex to automate,” it is probably worth a conversation.

// OR LEARN TO BUILD IT

Some teams would rather own the automation themselves. We run hands-on AI training at three levels, built around your team’s real work rather than toy examples.

// HOW IT WORKS

1. Tell us about your audience, the feeling you want them to have, and what you need — a website, a product catalog, order and invoice tracking, project demos, and so on.
2. We build a prototype and send you a preview link to review.
3. If it doesn’t feel right yet, we keep talking and keep adjusting — nothing is settled until the direction is one you’re happy with.
4. Once it feels right, we meet in person for a 1-hour collaborative session and fine-tune every detail live.
5. At that meeting, we sign a contract covering the initial development fee and ongoing annual maintenance (hosting, domain).
6. We keep refining until you’re satisfied — the bar for “done” is set in the contract.

// SOFTWARE

// CUSTOMERS

// WHERE WE HELP

// HOW IT WORKS

1. Reach out describing the engagement — full-time or part-time, the period, and the concrete problems you want solved, whether product, technical, or hiring.
2. We evaluate the requirements and present a rate card.
3. You issue a consulting contract documenting responsibilities and rates.
4. We execute the work, log hours, and invoice according to the contract terms.

// HOW IT WORKS

1. A church coworker reaches out with a concrete technology problem and who will benefit from solving it.
2. We evaluate the case and, if capacity permits, follow up with in-person meetings to plan a solution.
3. We track the case, develop the solution, and sync with the reporting coworker on a weekly or bi-weekly cadence.
4. Both parties keep working together to realize the vision behind the case — for the people we care for and love.

// PROJECTS