Integrate and reason over mixed modalities (text, charts, diagrams, images) for richer insights and retrieval using LLMs and multimodal fusion.
Reasons across text, tables, charts and diagrams together, where the answer requires combining what a chart shows with what the surrounding text says.
Report-heavy corpora where meaning is split between narrative and exhibit — annual reports, technical documentation, research output.
Where the underlying data behind the chart is available. Reading a chart to recover numbers you could have queried is a poor trade.
Values read from a chart must be marked as approximations, because they are. Presenting a chart-derived figure with the same confidence as a queried one is misleading.
Misreading axis scales, particularly logarithmic or truncated ones, producing figures that are wrong by an order of magnitude while looking reasonable.
Answering a question about a subsidiary's performance from an annual report where the trend is in a chart and the explanation is three pages away in the narrative.
Two different absences share this shape. Foundational solutions get built whatever the domain, so no domain links them; the rest are solutions this domain genuinely does not reach for. v_ai_solutions_unlinked separates the two.