Research discovery friction — AI-driven visual, citation-aware search

Research discovery friction — AI-driven visual, citation-aware search targets a $40.0B = 200M knowledge workers × $200 ARPU (global professionals who pay for research/search tools and subscriptions) total addressable market with medium saturation and a year-over-year growth rate of 25% YoY — driven by adoption of AI search and knowledge-work automation (source: McKinsey/IDC analysis of knowledge-worker tooling market).

Key trends driving demand: Trend — Increasing adoption of retrieval-augmented generation and vector search is enabling higher-quality, context-aware answers that can be tied to sources.; Trend — Demand for provenance and auditability in research outputs is rising, driven by reproducibility concerns, regulatory scrutiny, and corporate compliance needs.; Trend — Visual tools for exploring networks of knowledge (citation graphs, topical maps) are gaining traction as teams prefer interactive discovery over linear lists.; Trend — Subscription and API models for AI-first tooling are expanding as teams buy tools to speed time-to-insight rather than build in-house..