Store per-model reasoning & tool-use metadata alongside content (model-aware layer)

Store per-model reasoning & tool-use metadata alongside content (model-aware layer) targets a $24.0B = 1,000,000 potential orgs x $24K ACV (AI-driven apps & infra needing reasoning provenance) total addressable market with medium saturation and a year-over-year growth rate of 40%+ in AI infrastructure and tooling adoption driven by enterprise LLM projects.

Key trends driving demand: Multi-model pipelines -- teams compose models (Claude/Gemini/OpenAI) for strengths which requires maintaining model-specific state and reasoning continuity.; Agent/tool use explosion -- increased tool calls and chained reasoning amplifies the need to persist intermediate reasoning and tool outputs for continuity and debugging.; Enterprise provenance & compliance -- regulators and internal audit want reproducible reasoning trails and provenance of model decisions.; Specialized model signals -- vendors expose thought-signatures or extended-thinking formats that are meaningful only if captured and correlated with content..