Investigations, data reports, deep dives, and analysis from the INFLXD newsroom.
Model Context Protocol has moved from developer curiosity to enterprise wiring in under a year. The research-vendor stack is next.
Recording consent is migrating from PDF cover sheets and verbal preambles into typed transcript-header fields, and the expert networks that publish the schema first will shape how agent runtimes route their content.
As agents chain transcripts, earnings calls, and licensed research inside a single workflow, the recordkeeping burden is landing on vendors, and 2026 renewals will show it.
Re-embedding a decade of expert-call and earnings transcripts is the six-figure bill nobody puts in the vendor RFP. It is becoming the durable moat in primary research infrastructure.
Synthetic personas are landing in the same agent runtime as human expert calls. Respondent-type disclosure is the next provenance field, and no one has shipped it.
Underwriting, not regulation, is emerging as the first hard commercial gate on how expert networks handle AI-ingested primary research.
Vendor selection is migrating from procurement RFPs to agent-runtime endpoint resolution, and the registry is where placement is decided.
C2PA-style content credentials are moving from newsroom deepfake defense into buy-side research infrastructure. The transcript vendors that ship signed manifests will own the compliance conversation for agent-mediated research.
As agents pull from earnings and expert calls through the Model Context Protocol, the next provenance layer the buy-side will demand is a citation that resolves to a specific second of source audio.
A $47M Series C and a published accuracy gap sharpen the argument that the data layer, not the model, is now the binding constraint on agent-driven research.
Human-in-the-loop AI isn't a fallback for financial transcription. It's a quality architecture that targets review where ASR fails most: entities, numbers, and names.
Expert network transcription demands more than generic ASR. Learn why speaker diarisation, MNPI compliance, and domain accuracy define transcript quality for expert calls.
Sub-5% WER on conversational benchmarks is impressive. It's also irrelevant to the part of the workflow that matters.
