See every rival side by side: offers, prices, positioning, who engages with them and what buyers say about them. Then know where you can win, and which buyers are ready to switch.
From a map of every rival to a weekly read on where you win, in one loop.
Get a demoWe propose the rivals in each segment and region. You confirm the list.
Offers, prices, positioning and channels next to yours, each linked to the page it came from.
Reviews, Reddit and LinkedIn turned into a SWOT for you and for every rival.
People engaging with a rival, or complaining about one, go to your team with the reason.
Prices you hear on calls feed back in. A weekly read shows where you win, and why.
Market Signals
Market Signals watches rivals' pages, offers, posts, hires and reviews across 75+ sources, next to what buyers say on Reddit and LinkedIn. Each change is dated, carries its evidence, and links to the rival and the accounts it touches.
Buyer Intelligence
Signals add up per person and account. You see who is engaging with a rival, who is complaining about one, and which rival is best placed to win the deal. Ready buyers are routed with the reason and the rival to position against.
GTM Alpha
GTM Alpha ranks plays across the market, like a switch offer to a rival's unhappy buyers or a quote pitched against theirs. It games each one out against the rivals most likely to respond, tests it against accounts left alone, and every result recalibrates.
Connectors
Your agents, your CRM, your outreach tools and your team’s chat, all reading from one model of your market. If the connector doesn’t exist yet, our engineers build it.
Codex
OpenClaw
Attio
beehiivWhat our team has built
Case study · goal
Grew a subreddit from zero to 100K+ members, making it the go-to community in the category.
Case study · goal
Built a 20K+ engaged following and achieved GEO ranking within the first week of launch.
Case study · goal
Achieved first-page AI citation placement across ChatGPT, Claude, and Perplexity within one week.
Case study · goal
$100K in prizes. NYC Agent Hacker House.
Case study · goal
Senior engineers from top companies in real product conversations.
Resources
Fit tells you which companies could buy. Only a signal tells you when. A buying signal is a change, at a named company, on a known date, that you can go and check for yourself. This is the full landscape of 27 signal types in nine groups, the public record behind each one, and why several signals landing on the same company inside a week is the thing worth acting on rather than any single alert.
Harshil Jani
Every revenue channel has a period where it is underpriced, underexploited, or not yet saturated. Whoever finds that window first gets an advantage, whoever executes it better turns the advantage into revenue, and whoever systemises it makes the whole thing repeatable. Traders have had a word for this for a long time, and alpha turns out to be the most useful way to think about gtm as well.
Roman J. Georgio
Marketing leaders are experimenting with AI agents but building in silos. The true advantage comes when you have a clear strategy. From AI-assisted persona targeting to competitor signal scanning, these 10 applications show how a unified agent layer transforms B2B marketing performance.
Sebastian LourençoWe look at your market together and show you the moves worth making first, on your own or with our engineers.
FAQ
Every rival in each segment and region: their offers, prices where they can be found, positioning, channels, who engages with them, and a SWOT built from reviews, Reddit and LinkedIn. Each point links back to its source.
We use what is public, and proxies where it isn't. Prices your team hears on calls feed back in, so the benchmark gets sharper every time and your next quote is set against the real market.
A report is out of date soon after it lands. Here every rival stays watched. Changes arrive as dated signals and link straight to the buyers and plays they affect, so you can act on them, not just read them.
