Inspiration
- $24 B influencer-marketing market but tools are fragmented & priced for enterprises
- Micro-creators lack data & automation; brands drown in manual vetting
- Generative AI can collapse search, briefing, and forecasting into minutes
What it does
- AI Match Engine → top creators scored on style, engagement, brand safety
- “Briefing Wizard” (Gemini) → campaign brief, CTAs, sample captions in 30 sec
- AI Clone Preview → mock post shows how a creator would frame the product
- Live Dashboard → predicted reach + real-time sentiment / toxicity flags
How we built it
- Front-end: Next.js + Firebase (auth, real-time sync)
- Back-end: .NET APIs orchestrate matching, briefs, forecasts
- ML micro-services (Python on GCP Cloud Run) – Sentence-Transformers + CLIP for multimodal embeddings – Gemini AI for briefs, outreach, captions – Prophet-style models for view/engagement forecasts
- Vector DB: Pinecone (<300 ms similarity search)
Challenges we ran into
- No official IG/TikTok APIs → hybrid of public scraping + mock data
- Early ranking overweighted followers; re-balanced for content fit
- Cold-start latency on Cloud Run broke first user flow
- Ethical AI Clone: avoided deep-fake; used past posts + brand overlays
Accomplishments that we're proud of
- End-to-end campaign setup demo in < 5 min
- 90% human-validated precision on top-5 creator matches using only public data
What we learned
- Multimodal similarity > keyword filters for authentic brand alignment
- Marketers need explainability as much as accuracy
- Small creators want the same AI toolkit for self-promotion
- Strict MVP scoping beats feature sprawl in a 48-hour sprint
What's next for AI Power Social Influencer Platform
- Integrate official TikTok, Instagram, YouTube APIs for real metrics
- Launch creator portal: deal pipeline, e-sign contracts, payout analytics
- Real-time sentiment & brand-safety alerts on published content
- Reinforcement loop: campaign outcomes feed back into match engine
- Judges cited AI Clone as “game-changing creative preview”
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