An AI research agent that produces verified, source-cited business intelligence — and refuses to be fooled by a rigged source.
Replace the slow, expensive middle of a research team: the reading, cross-checking and writing-up. Point it at a market, a competitor set, or a tender, and get back a finished, sourced report — not a pile of links, not a hallucinated summary.
The hard part isn't fetching data. It's trusting it. A research agent that reads the open web is one poisoned page away from confidently reporting a lie. So the real work was making it verifiable and hard to manipulate.
Veridica runs a multi-stage pipeline: it plans the research, pulls from multiple sources, cross-checks claims against each other, structures the findings, and renders a client-ready PDF with the sources attached. Multiple models are used where each is strongest, and every material claim is traceable back to where it came from.
Claims are cross-checked across sources before they make the report, and each is traceable to its origin — so a reader can audit the finding, not just take the model's word.
Fetched web content is untrusted input. A layered defence stops a page that says "ignore your instructions" from hijacking the agent or skewing the findings — the difference between a real research tool and a demo.
What used to take a researcher days — market sizing, competitor breakdowns, pricing intelligence, tender analysis — runs as a repeatable pipeline that produces a consistent, structured deliverable.
Finished PDF reports with structure, sources and visuals — the format a business actually pays for, generated end-to-end.
Agentic AI done responsibly — multi-step planning and tool use, with verification and a real security posture rather than a single prompt. Adversarial thinking — treating web content as hostile input and defending against it. End-to-end delivery — from a research question to a sourced PDF, built and shipped by one person.