Search your social feed history with AI-powered repost retrieval

Many creators, social managers, and marketing teams—part of an estimated 200 million paying creator/professional users—waste hours hunting for past posts when trying to repurpose content, comply with campaigns, or monetize evergreen material. Search within each native platform is slow or imprecise for short, noisy posts, and cross-platform lookup is practically non-existent, creating friction for consistent publishing and quick monetization. You could build an AI-powered repost retrieval product that ingests users’ feeds via connectors, encodes posts with up-to-date embeddings into a vector database, and provides fast semantic search, deduplication, relevance scoring, and export/scheduling workflows. Practical features would include date/engagement filters, content snippets with provenance and permission metadata, one-click repost templates, and team collaboration controls so users can find, verify, and reuse content in minutes rather than hours. The market is attractive now because the creator-economy needs efficient repurposing to boost lifetime value, embeddings and vector DB costs/performance have improved, and cross-platform workflows are a rising priority; together these support a realistic $12.0B TAM assuming $60 ARPU/year. Strengths include low direct competition and clear product/monetization levers, but challenges are real: API rate limits and platform TOS, privacy and consent requirements, scaling index costs, and the risk of larger platforms copying core features; based on these factors the opportunity scores highly (market score 90/100, revenue potential 82/100) and merits a focused, compliance-first MVP to validate retention and willingness to pay.