FileMaker now ships AI as part of the platform: semantic search, AI script steps and functions, connections to language models. From these, we build features your users work with directly in the solution they already know - no new software, no tool switching.
Users search in natural language instead of exact field values. The search understands meaning: a query for «complaints about delivery delays» also finds the entry that says «goods arrived three weeks late» - without anyone having to guess the right keyword.
This works across records, notes, and attached documents, within the existing access privileges.
An assistant right inside the solution answers questions from your records: «Which orders are critical this week?» instead of five filters and three layouts. The answer references the records it came from - one click, and you are there.
If the system finds nothing, it says so. It does not invent an answer.
Incoming feedback, emails, or documents are categorized, tagged, and prioritized on arrival. What's urgent sits on top; similar items are grouped. Your people start the day with a sorted list instead of a full inbox.
You define the categories - the solution does the assignment, correctable with one click.
Incoming goods, inventory, construction-site documentation: one photo with an iPhone, and the solution suggests a category and assignment. The image library becomes semantically searchable - «damaged packaging» finds the matching photos, without anyone ever having entered a keyword.
Your solution knows what normal looks like - order volumes, throughput times, consumption. AI flags what deviates from it and estimates where a series of numbers is heading. Right in the dashboard your people open anyway.
A plant retailer documents deliveries with iPhone photos. AI assigns each image to an inventory category and helps decide whether a delivery is accepted or rejected - incoming inspection became noticeably faster.
An HR solution compares incoming applications with the job profile, ranks the best-fitting candidates on top - and recognizes when someone is a better fit for a different open position.
Product reviews are automatically grouped and ordered by need for action. Customer service starts with a finished report instead of hundreds of unread responses.
Examples from the FileMaker ecosystem, documented by Claris (claris.com).
Agentic development, prototypes from conversations, automated tests - how we build with AI.