We build the systems behind your pipeline
We map your entire real TAM, build the data, scoring, and CRM systems behind your pipeline, and run them on the floor with your reps.
- GTM engineering & RevOps
- Embedded with your reps
- Everything pre-outreach
- 20+ yrs combined experience
From your real TAM to pipeline your team can close
- 01
Map TAM
Define the ICP and capture your entire real market as data — not the slice a database happens to index.
- 02
Build
Source, enrich, and score it, then build the AI agents, custom software, and automations around it.
- 03
Report
Wire HubSpot or Salesforce into dashboards with real pipeline analysis you can forecast against.
- 04
Execute
Embed with your reps — on the floor and in Slack — and iterate the system until the leads close.
Four parts of one system
Each works on its own. Together they're the engine that turns data you can't buy into pipeline you can.
- 01TAM mapping & prospecting dataDefine the ICP, map the whole market, and capture it as scored, ready-to-work data.
- 02AI agents & custom softwareCustom agents, scoring, and automations built for the motion your team actually runs.
- 03RevOps integrations & reportingHubSpot and Salesforce, wired up and reported on — analysis you can forecast against.
- 04Embedded pipeline managementWe work the floor with your reps and iterate the system until the pipeline closes.
Most agencies hand you a deck and leave. We embed — in your CRM, in your Slack, on the floor with your reps — reverse-engineer what already closes, and turn it into systems that scale. Built inside your stack. Everything pre-outreach.
Why teams embed us instead
Instead of onboarding juniors on a budget, embed senior operators with 20+ years of combined GTM experience.
| Dimension | Buy more toolsZoomInfo · Clay · Outreach | Hire in-houseA RevOps / GTM engineer | Embed DatumGTM engineering, executed |
|---|---|---|---|
| Your real TAM | Only what's already in the index | As far as one person can map it | We map and capture all of it |
| Time to first pipeline | However long you take to build it | 3–6 months to hire and ramp | We execute from week one |
| Who runs it day to day | Your reps, off the side of their desk | One seat, one point of failure | Embedded with your reps, in your Slack |
| Reporting | Dashboards you wire up yourself | If they get to it | RevOps reporting, actually analyzed |
| When it breaks | Your problem | Their problem, then yours | We own it and iterate |
90%+
of your real TAM, captured and scored
75%
higher conversion from ML scoring vs rules
28%
of a rep's week is actually spent selling
2.8×
more pipeline when AI augments reps
Built for the hard ICPs
Capturing the TAM databases miss
Market sizing pulled from a single database inherits that database's gaps. For mainstream software that's tolerable. For most other markets it means your "TAM" is really "the slice one vendor happened to catalog."
Selling into data-poor markets
Most GTM advice assumes your buyers are already cataloged. For a lot of real businesses they aren't. If you sell into the trades, local operators, regional brands, or a category that didn't exist three years ago, the databases everyone pays for are mostly blanks where your ICP should be.
Senior operators instead of a junior team
When you're lean, every hire is a bet. A junior RevOps or data hire is cheaper on paper but slow to ramp and easy to misdirect; a senior one is expensive and hard to find. Either way, while you decide, outbound runs on whatever a single tool happens to have.
Enterprise data ops & augmentation
Enterprise GTM doesn't lack tools — it lacks coverage in the corners and the engineering time to keep data clean and scored. Licensed databases have ceilings, and the records you hold decay roughly 30% a year.
Data infrastructure for GTM agencies
Every new client is a new ICP, and the markets that are hardest to reach are often exactly the ones that hired an agency because in-house couldn't crack them. Re-solving sourcing and systems per account eats your margin.
Not sure which fits?
Tell us the market your data doesn't cover — we'll say straight whether it's sourceable.
Book a discovery call
Straight answers, real numbers
- When is scraping the right solution?6 minScrape when the data you need isn't in any database you can buy — a niche or data-poor market, a field no vendor sells, or freshness a static file can't match. For mainstream, well-covered B2B, buying is faster and cheaper; custom scraping is the right tool in maybe 10–20% of cases. And it's a commitment, not a one-off: a scraper costs roughly 20–30% of its build in maintenance every year as sites and anti-bot defenses change. Scrape for the gap, buy for the bulk — and never scrape what's already a column you can purchase.
- What is GTM engineering?5 minGTM engineering is the practice of building the data, software, and automation systems behind a go-to-market motion — instead of throwing more headcount at it. A GTM engineer maps the TAM, sources and scores the data, wires the CRM, and automates the busywork that consumes reps, who spend only about 28% of their week selling. It's RevOps with a builder's toolkit: reverse-engineer what's already closing, turn it into a repeatable system, and let AI augment the team for roughly 2.8× the pipeline of teams that just hire more juniors.
- Does lead scoring actually work?4 minYes — when it's built on real outcomes rather than guessed point values. Machine-learning lead scoring reaches 40–60% accuracy versus 15–25% for rule-based systems, and converts up to 75% better; adding behavioral signals lifts MQL-to-SQL rates by up to 40%. It matters because only 27% of leads handed to sales are actually qualified. Scoring sorts that 27% from the noise, so reps spend their limited selling time on accounts likely to close instead of working a list top to bottom.
- What is waterfall enrichment?4 minWaterfall enrichment chains data providers in sequence: the first source fills what it can, the next takes the misses, then the next, until coverage is maxed. It exists because single-source data has a hard ceiling — contact accuracy plateaus near 78–84%, and a single database has no fallback when a record isn't in its index. A well-configured waterfall regularly pushes match rates past 90% and lifts direct-dial coverage 20–40% above any one provider.
Let's map your real TAM
A 30-minute working call. We'll tell you straight how much of your market is sourceable and where your pipeline is leaking. We reply within one business day.