Founder of AdFlint — AI ad management for founders and small businesses
The angle of searching your own ATS in plain language instead of Boolean strings is a genuinely useful wedge. Boolean recruiter search is notoriously painful, and natural-language querying over a database you already own (rather than re-sourcing) is a smart, focused use of AI. The 'paste a job description and surface matching candidates' flow in the screenshots is the kind of concrete, time-saving workflow recruiters will get instantly. My main questions: how does it handle messy or duplicate ATS data, and which ATS integrations are supported at launch? That'll make or break adoption for agencies.
The 'creative ops from brief to launch in one place' positioning is sharp for DTC teams who currently juggle a brief doc, a separate DAM, an approval thread, and an analytics tool. Consolidating brief, asset storage, approvals, launch, and analytics into one workflow is a real pain point for in-house teams shipping high volumes of Meta/TikTok creative. The screenshots lean on asset storage and approval workflows, which feels like the strong core today. My one question: what does 'launch' actually mean here, does it publish creatives straight into the ad platforms or stop at handoff? Native publishing would be the real differentiator versus a standard DAM.