Scale RAG for 10M+ docs, .md agent memory, and code-driven motion-graphics

Scale RAG for 10M+ docs, .md agent memory, and code-driven motion-graphics targets a $24.0B = 1,000,000 potential buyers (global SMBs + enterprises using AI) x $24K ACV total addressable market with medium saturation and a year-over-year growth rate of 35%+ CAGR in enterprise AI tooling and vector search adoption.

Key trends driving demand: RAG adoption -- enterprises use retrieval to control hallucination and connect LLMs to live data, increasing demand for scalable pipelines.; Vector DB commoditization -- multiple managed and OSS vector stores lower time-to-launch but emphasize performance and integrations as differentiators.; Markdown-native developer workflows -- teams prefer .md and git-first flows for knowledge and agent memory, creating an interface gap with existing memory solutions.; Generative media automation -- programmatic code-driven motion graphics are becoming viable with model-based code (e.g., Claude Code), increasing demand for end-to-end tooling..