Automated data collection for the deadlines that never move.

Automated data collection is using software — increasingly AI agents — to gather external data on a schedule instead of by hand: pulling from surveys, filings, portals, and public sources, normalizing the formats, checking quality, and landing it in one structured store. Done well, an analyst starts at the analysis; done generically, it fetches pages nobody can use.

Tools fetch pages; they do not know your source list, your normalization rules, or what QC means for your data — so the collecting gets faster and the cleaning stays manual. We build AI agents on rules encoded from your analysts and run them in your cloud, so what lands in the store is already checked against how your firm actually works.

Same pattern, different data type. Publisher survey files and public-company filing reading are specific collection problems, each covered on its own page; this page is the general layer — any external source your firm collects from, on any schedule. All three run the same way: encode your rules, let AI agents apply them, route only exceptions to people.

That is the normal case, not the exception. Where a portal or a legacy system offers no API, AI agents work through it the way a person does — browser sessions and scheduled exports — so collection runs without waiting on an integration project. Legacy systems slow the work down; they do not block it.

QC is encoded, not eyeballed. Every pull is checked against your rules — expected ranges, required fields, source citations — and anything that fails lands in an exception queue with the reason attached, so a person reviews a short list of real problems instead of re-checking every record.

You do. The agents run in your cloud, the structured store is yours, and the encoded rules — source lists, schedules, QC checks — are documented IP you keep. We advise, build, and run the machine; nothing about it is rented back to you.

Design for the moment, not the follow-up email. The surveys that come back are anonymous and no-login — a link or QR code that opens on the phone already in the attendee’s hand, no sign-up wall in front of the first question, short enough to finish between sessions, and forgiving when people drop off halfway and come back. The ones that fail go out by email days later and land after the decisions they were meant to shape. We build event data collection the first way: feedback captured live, then cleaned and structured by AI before your team opens a spreadsheet.

Event survey software does one thing well — it collects. It does not chase. It will not get a busy attendee to open the survey, decide which questions matter to your research, or turn a pile of verbatim comments into themes you can act on. The tool is the easy part; the work is the design around it and the pipeline after it. We build and run that whole layer — the no-login feedback moment, the AI that cleans and themes every response, the structured store it lands in — so you get the answers, not another login to manage.