research

Multimodal research with source attribution is performed by routing queries across diverse data types via modality-aware dispatch, aggregating findings with verifiable provenance, and explicitly highlighting any remaining information gaps.

Root-cause analysis using live sources is executed by dispatching investigations across multiple modalities, verifying findings against active data, and generating remediation-scope artifacts that clearly document verifiable sources and missing information.

Yes, multimodal discovery supports exhaustive research by routing queries to the best available models per modality and explicitly reporting gaps, ensuring thorough corroboration from diverse data types with verifiable source attribution.

Modality-aware routing handles cross-modal investigations by dynamically dispatching information queries to specialized models based on the data type, then aggregating the findings with explicit source provenance and detailed gap reporting.

Gap reporting is needed during multimodal investigations to explicitly identify missing information after aggregating findings from diverse data types, ensuring the final root-cause analysis or remediation scope retains verifiable trustworthiness.

No, cross-modal discovery requires verifiable source attribution for all findings, ensuring that every piece of information aggregated from diverse data types includes provenance alongside explicit gap reporting.