Marketing intelligence, agent-run.
One platform that listens to your customers, learns which creative makes money, makes the next round, and proves it works — with a human hand on every trigger.
Nikhil Mani · built with Claude
Every review & support chat becomes an enriched signal. Spikes raise alarms with proof.
Which creative themes bring high-value customers — not just installs. Fatigue gets a dollar figure.
Winning themes become on-brand variants per channel & market — graded before spend.
Real test design, real statistics. Ship, iterate, or kill — never gut.
Results and customer reaction feed back into LISTEN. The loop compounds.
Reviews, CS chats, social → one enriched feed: sentiment, topic, intent, severity, incentivized-flag. Vietnamese native, accuracy eval-gated.
Detects spikes vs baseline → investigates the cluster → writes root cause citing actual reviews → routes to the right team. In hours, not weeks.
Rivals run through the identical pipeline from public reviews — share of voice & sentiment by topic. Steal their post-mortems.
Replaces the monthly deck. Top movers, emerging issues, competitor deltas — evidence linked.
"Top delivery complaints this month vs competitors?" — answers with charts and cited reviews.
Vision on review photos — damaged products spotted automatically.
Creatives clustered by theme, joined with spend, ROAS and predicted lifetime value — per channel, per segment.
Flags winners, fatigue and payer-depth patterns with cited creatives and real numbers. Thresholds are code; the model explains, never invents math.
"This theme burned $12.4k in 30 days." The number that moves the meeting.
Move $X/day from fatigued theme on Facebook to the TikTok winner — projected ROAS delta included.
Approved shifts pushed through Meta/TikTok APIs — human click required.
Winning themes → concept briefs + copy variants, constrained per channel and market, obeying your brand kit.
Every variant pre-flight graded against winning evidence: SHIP / REVISE / KILL + a predicted ROAS band from historical quartiles.
Standalone evaluator — drop any ad copy in, get the verdict. Try it on yours.
Nothing is A/B-ready until a human approves it. The agent proposes; your team disposes.
Static and video creative generation against the same brand kit and evidence.
Market-specific variants with back-translation QA.
Hypothesis in → metric, sample size (real power calculation), duration at your traffic. Statistics live in code, not in the model.
Significance checked in code; the agent writes the plain-language narrative and calls it: ship / iterate / kill — with what to change if it's ambiguous.
Institutional memory: every test, every decision, searchable.
Peek-safe early stopping for fast-moving campaigns.
Ad exports (Meta, TikTok, Google), MMP/pLTV feed, marketplace & Google reviews, app stores, CS webhooks. API connectors COMING SOON
Tone rules, banned claims, format constraints — enforced by the generator and evaluator, not suggested.
Owner, Analyst, Creative, Reviewer. Agents recommend; humans click.
Every agent step traced in Langfuse — inputs, decisions, cost. Your analysts can check the math.
Slack, Zalo, email routing per team.
Retailer today, game studio tonight — same platform, different workspace. No code changes.
manual reporting effort — the exec summary replaces the monthly deck
not quarters, to kill fatigued creative — with the burn in dollars
budget follows winning themes — proven by statistically-sound tests, not gut
Issue spikes caught in hours protect retention; competitor benchmarks show commercial where to attack.
Listen. Learn. Make. Prove. Repeat.
Nikhil Mani · AABW 2026 · live demo + source available