Terriqon
Collect field data offline. Get AI reports in minutes.
5 followers
Collect field data offline. Get AI reports in minutes.
5 followers
Most field data tools stop at collection — you still spend weeks manually turning submissions into reports. Terriqon doesn't. It's an offline-first platform for field teams (NGOs, construction, conservation, research) that collects data without internet, then uses AI to generate ready-to-use reports instantly - no analyst, no spreadsheet wrangling. What used to take weeks now takes minutes. Built for teams who need field data to become a decision, not just a dataset.
The offline-first angle is really appealing for our remote project sites. One thing that would make it even better for us - a simple way for field staff to flag data quality issues or missing info right in the app, so the AI knows what to double-check or exclude when generating reports.
@accessibility Thank you for your comments.
Field-side flagging isn't in the product yet the way you're describing it - right now, review happens on the manager side through the submission queue rather than at the point of capture. Letting a field officer mark "this is estimated" or "site was inaccessible" and having that carry into the AI's exclusion logic is a smart addition. What kind of sites are you running, and how does bad data usually surface for you today?
The offline-first angle is genuinely useful for field work. One thing that would help teams like ours a lot is a simple approval workflow inside Terriqon, where a field lead can review the AI-generated report, leave comments on specific sections, and lock it before sharing with donors. Right now "instant report" sounds great but my program managers would still want a quick checkpoint to catch tone or numbers that look off before it goes external.
Thanks @finneganclark - you're describing exactly the failure mode we designed against. "Instant" doesn't mean "unreviewed" in Terriqon: AI-generated reports run through a confidence-gated review step before they're shareable, and low-confidence sections get flagged rather than quietly published. Section-level comments and a hard lock before external sharing is the direction we're building toward. What size is your program team, and who signs off today?