Create • Support • Protect
AI Integration
Selective AI features for FileMaker—useful, optional, and grounded.
AI is being marketed as a solution to everything, and that has made many people (rightly) cautious. My approach is simple: treat AI as a tool, not a magic button. When it clearly improves speed or reduces repetitive work, I’ll help you implement it. When it doesn’t, I’ll say so.
Most of my AI work is integrated directly into FileMaker solutions, where the results are practical and tied to real workflows.
Where AI can help
The most successful projects are narrow and measurable: the AI does one job, and you can tell if it’s working. Examples of “good fit” tasks include:
- Summarization: turn long notes or imported data into a concise summary
- Extraction: pull out names, dates, identifiers, or key facts from structured text
- Classification: assign tags or categories to incoming information
- Search improvements: natural-language search and semantic search over your existing data
- Drafting assistance: generate a first draft that a human reviews and edits
In all cases, the goal is productivity: reduce manual work while keeping a human in control of decisions.
Examples from real projects
- Legal Cases – natural language search: integrated natural-language searching and semantic search on case-related data to help users find information quickly without needing exact keywords.
- Online Content Generation – summarization and publishing: summarized data and generated draft posts for a WordPress site (reviewed before publishing).
There are many powerful AI services available online, but not every use-case is a good fit for sending sensitive data to third-party platforms. Where privacy matters, I focus on approaches that keep data controlled and scoped—using in-house processing or carefully limited integrations rather than “send everything to the cloud.”
Setting realistic expectations
AI can be very useful, but it does not always produce the same result from the same input. For that reason, I help clients choose use-cases that remain safe even when the AI output needs review.
- Best for: assisting humans, drafting, searching, sorting, summarizing
- Not ideal for: fully-automated decisions, anything high-stakes without verification
- Always recommended: a human review step for anything external-facing
Privacy and control
Many clients are concerned about privacy—and that concern is reasonable. AI integration should be planned with data sensitivity in mind, including what data is sent out, what stays local, and what is logged or retained.
When AI is a good fit, I aim for a careful approach: send only what is necessary, keep prompts and data scoped, and design workflows so that private or sensitive information is handled responsibly.
How we start
The best first step is usually a short conversation and a small pilot. If the pilot proves value, we expand it. If it doesn’t, we stop—without having invested in a giant “AI project” that doesn’t pay off.