Automation and data cleanup

A spreadsheet is often the right answer, and I have talked people out of this before. If one person owns the file and the format changes as often as the work does, automation buys you rigidity instead of time. What changes the math is repetition across people: the same export re-keyed every week, two systems that disagree about the same customer, or a file that quietly became the system of record for something that matters.

An engagement starts with me watching the real process, including the steps nobody wrote down. Then I clean and migrate the existing data, because automating a mess only produces the mess faster. The recurring piece gets built last: a Python job, a Postgres function, or a small internal screen, with a written handoff so you are not dependent on me to run it. Scope is fixed per project, and the number lands after the audit rather than before it. See how pricing works.

I do this at scale. GrantCue, the grant-funding SaaS I built, rebuilds its catalog on a schedule from the full federal Grants.gov corpus plus more than 100 state and state-agency sources, normalized through per-source adapters, deduplicated by content hash and title similarity, then upserted only where something changed. WellStockd applies the same discipline in a kitchen: cooking a recipe atomically subtracts its ingredients from inventory, and anything that runs out lands on the shopping list. Those kitchen flows run as Postgres functions, so the numbers never drift.

When the data only lives on a website, extraction is still solvable. I have built a multi-tenant web crawler and SEO auditor in Python and Flask with Playwright rendering for exactly that case. I work from Lock Haven, though this kind of job runs remotely more often than not; the data does not care where either of us sits.

• A written map of the current process, including the manual steps and the places where two sources already disagree
• A cleaned, deduplicated dataset with the matching rules written down where you can read them
• Data migration into Postgres, Supabase, or whatever system is meant to hold it, with the old source left readable until you sign off
• Scheduled import and export jobs in Python, with retries, run logs, and an alert when a run fails
• A spreadsheet-to-database move that can still hand back a spreadsheet view for the people who want one
• Small internal screens for the steps a person genuinely has to review or approve
• Extraction from a website or another vendor's tool when there is no export and no API worth using
• A runbook you can hand to someone else, including how to turn the whole thing off

Fit. For the office where one person loses a morning a week moving the same data between two systems by hand, and the errors that slip through cost something.

Engagement. Priced after the audit, not before it. The number of source systems and the condition of the input data do most of the moving.

1. Map the work. We sort the real workflow from the wish list, identify users, and write down what success needs to look like.
2. Scope the first release. You get a clear proposal, timeline, and build plan with the risky parts pulled forward instead of hidden at the end.
3. Build in the open. I share progress, ask focused questions, and keep the work testable so feedback arrives while it can still shape the product.
4. Launch and hand off. Deployment, documentation, and training are part of the work, so the finished system is something your team can actually run.

See the full process

• GrantCue — A multi-tenant platform that syncs Grants.gov and 100+ state sources on a schedule, matches each organization to grants and to foundations that fund work like theirs, and drafts proposals in a team pipeline.
• WellStockd — A touch-first recipe and fridge-inventory app that lives on a fridge-mounted tablet. Cook a recipe and the ingredients subtract themselves; run out of something and it lands on the shopping list.

• Build log: how GrantCue ingests grant data

• Custom business management systems
• Nonprofit & civic tech
• Chamber and county partnership platforms
• Websites and rebuilds