Agentic market intelligence for industrial opportunity mapping
LiveCorehigh effect
Core capability
Teams can access needed knowledge faster and prepare structured technical outputs with less manual searching, which improves speed in documentation-heavy workflows.
How it works
The system first gathers the most relevant knowledge from internal and reference sources, then assembles it into a usable answer or draft document so the user does not need to search and combine everything manually.
Application here
An AI agent continuously scans internal notes, analyst reports, and vendor landscapes and produces structured opportunity briefs ready for strategy review.
Business impact
This replaces weeks of manual analyst work with near-real-time scanning, giving strategy teams structured briefs instead of raw information.
Limitations
The agent can draw false connections or miss context hidden behind inaccessible sources. It helps strategy work, but does not replace strategic judgment.
In production
This is already practical for reducing the time engineers spend searching through documentation and assembling first drafts of structured outputs.
Research
The frontier is toward assistants that can carry much more of the standards and compliance workload themselves, including evidence gathering, structured interpretation, and preparation of draft outputs.
Examples
McKinsey launched Lilli (2023), an internal AI agent searching 100 000+ firm documents and returning cited market-intelligence answers; ~70 % of consultants adopted it for faster desk research (McKinsey internal data). In industry, Honeywell uses a similar knowledge-agent for vertical market intelligence — .