Inside AgentTIM's AI‑powered Age‑Inference pipeline — from thousands of candidate apps down to a hand‑picked, brand‑safe inventory.
Inside AgentTIM's AI Powered Age‑Inference pipeline — from thousands of candidate apps down to a hand‑picked, brand‑safe inventory. Scroll to dive into AgentTIM's neural core.
AgentTIM doesn't guess. It identifies, scrapes, infers, validates, scores, filters, and reports — every step logged, every decision traceable. Here's the recap, side-by-side.
DSP / client uploads candidate list
Platform detect · fuzzy match scoring
Metadata · reviews · multi-country iOS
Slang · Linguistic AI · Validation · Aggregation
Levels 1–5 with confidence metrics
UKGC / ASA / geo rules applied
App + review level, fully auditable
The Age Inference Engine deliberately uses four cooperating layers — local slang detection, OpenAI psycholinguistic analysis, evidence validation, and weighted aggregation. No single layer can call an age on its own; they have to agree.
A short, generic review barely moves the needle. A long, specific, life-stage-heavy review counts for 20× more. That's how we avoid blanket over-classification while still catching real youth exposure.
When data is too thin or signals conflict, AgentTIM downgrades confidence rather than guessing. Insufficient evidence pushes an app into Level 5 — flagged for review, not silently passed.
Every review's score, evidence tier, and contribution to the final tier is logged. Every app gets a row. Your finance team and compliance officers are looking at the same file.
Tier-1 operators stay locked behind the strictest filters. Tier-2 and Tier-3 brands can dial the risk threshold up to scale faster — with full visibility on what they're buying.
If you're spending on media and not seeing clear, attributable returns — we should talk.
We build growth funnels with measurable KPIs, full spend and inventory transparency, and results that hold up to scrutiny.
Join other high growth brands scaling their app acquisition & achieveing positive ROAS that beats all your other media spend.