Forward deployed GTM engineers build your engine on the platform: a model of your market, plays ranked against your rivals, and agents that run them. Every result makes the next move sharper.
From onboarding to a weekly report, in one loop that gets sharper every week.
Get a demoIn a week of onboarding we map your market, tier every account and agree the strategy with you.
Each play has a signal, a message and a forecast, and runs against accounts left alone.
Leads, replies and next moves land in your CRM and a shared Slack channel, with the why.
Once a play books meetings, we roll it out to more founders, reps and channels.
A weekly alpha report shows what worked against the control, and what changes next.
Market Signals
Your engineers set up watches on buyers, rivals and your own data across 75+ sources. Every signal is dated, comes with evidence and links to the people, accounts and rivals it touches, so outbound, ABM and content work from the same picture.
Buyer Intelligence
Signals add up per person and per account. You see who is ready, the pains they and their own buyers face, and which rival is closest. Each account goes to the right founder, rep or agent with the reason attached.
GTM Alpha
GTM Alpha ranks plays across your whole market and games them out against your rivals. Each one runs against accounts left alone, so you see real lift. Winners scale across founders and channels, the rest stop, and every result recalibrates the model.
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
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
Most teams calling themselves AI-native are at L1. It's the same scattered go-to-market, just typing faster. The AI Maturity Framework has six rungs: Manual, Assisted, Integrated, Owned, Connected, Autonomous. Each rung has a specific wall above it. No context graph, no named owners, no command centre, no trust in long-horizon loops. Locate your rung honestly, find the wall directly above you, and build the one thing that clears it. Adding more agents is the generic wrong move at every level.
Sebastian Lourenço
The average LinkedIn outreach campaign gets about 1 reply in 10. Our micro campaigns for a B2B services firm got 7 to 9 in 10. Here's how we build a micro campaign: tens of people, one strong shared signal, a message that names it, and a small offer. Then a setter team turns the replies into booked calls.
Roman J. GeorgioWe look at your market together and show you the moves worth making first, on your own or with our engineers.
FAQ
They join your team, learn how you sell today, and build your engine on the platform: signals, plays, agents and routes in the tools you already use. Then they run it with you and review the results every week.
No. You agree the strategy and the rules for each tier of accounts. You see every message in a shared Slack channel, and nothing goes out in your name until you have approved it.
The work runs on a platform that models your market and tests every play against a control. You get a working engine and the evidence behind each move, not a list of tactics, and it keeps learning after setup.
