Competitor research from today's web, not last year's memory
Generic AI tools answer competitor questions from a stale training snapshot. Idam AI's Competitor Research agent searches the live web - pricing pages, changelogs, reviews, job postings - and assembles a decision-ready brief with every claim sourced.
every brief, freshly researched
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Six signals, read together
You could read all of this yourself - and lose an afternoon per competitor doing it. The agent reads it in one pass, cross-checks claims between sources, and cites where each finding came from.
Pricing & packaging pages
Current tiers, limits, and how their packaging changed since you last checked - the page sales keeps asking you about.
Changelogs & launch posts
What they actually shipped, week by week. Velocity and direction matter more than the marketing site headline.
G2, Capterra & review sites
Where their customers complain - recurring gripes in reviews are your differentiation opportunities, pre-validated.
Job postings
Hiring is strategy in public. Three enterprise AE openings or a new ML team tells you where they are headed next.
Press & analyst coverage
Funding rounds, partnerships, and customer wins that change the competitive math for your category.
Community discussions
What users say about them on forums and social - unfiltered sentiment the review sites smooth over.
The same research, shaped for the decision at hand
Tell the agent what the brief will inform - a prioritization call, a sales enablement push, or a board narrative - and it structures the output for that audience instead of dumping everything it found.
Feature Prioritization
Before committing a quarter to a feature, see who already has it, how mature their version is, and whether customers actually like it. The brief separates table-stakes gaps from genuine differentiation openings, so parity work and bet work stop competing for the same slot.
What PMs ask before their first brief
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