How does NeuroGTM pricing work?

Every engagement is scoped to your specific stack and goals. We walk through what you need on a 30-minute discovery call and give you a clear proposal — no black-box pricing, no surprises.

Does NeuroGTM work with Salesforce or just HubSpot?

Both. We also integrate with Slack, Gmail, Outlook, Calendly, Gong, Fireflies, Apollo, Clearbit, ZoomInfo, n8n, Make, Zapier, and more. If it has an API, we can connect it.

What happens after NeuroGTM builds the system? Who maintains it?

You own everything — no vendor lock-in. The system runs autonomously. If something in your stack changes or you want to add new workflows, you can bring us back on a Sprint or move to Ongoing Ops for continuous optimization.

How is NeuroGTM different from hiring a RevOps contractor?

A RevOps contractor configures your existing tools. We build AI systems that run on top of them — scoring, routing, enrichment, alerts, and forecasting that execute autonomously. It's the difference between setting up a workflow and building an intelligence layer.

How long does a NeuroGTM implementation take?

Sprints ship in 3–5 days. Full System Builds take 1–3 weeks. No committees, no lengthy SOWs. We go heads-down and build the actual system.

Do I own what NeuroGTM builds?

Yes. Infrastructure, workflows, intelligence layer — all yours. No recurring platform fees, no proprietary lock-in. If you want to part ways, everything keeps running.

Can I start small with NeuroGTM and expand later?

That's what Sprints are for. Pick your biggest bottleneck — lead scoring, deal alerts, CRM enrichment — and we build a production system for that one problem. Most clients come back for more once they see it running.

Stop Holding Weekly Pipeline Reviews

The weekly pipeline review isn’t a meeting. It’s a patch for a broken information architecture.

Every Monday morning someone pulls a HubSpot export, pastes it into a spreadsheet, formats it, shares their screen, and walks the team through deals that changed three days ago. Decisions get made on stale data. Action items get written down and half of them don’t happen. Seven people blocked an hour to learn things the system already knew.

The intelligence was there the whole time. Nobody built the layer to surface it.

What is the weekly pipeline review actually doing?

Strip the pipeline review down to its function and it’s doing three things: identifying what changed, flagging what’s at risk, and deciding what to do next.

All three of those are solvable outside a meeting.

What changed: your CRM knows. Every stage update, every last activity date, every contact that went dark - it’s all in there. The problem isn’t that the data doesn’t exist. The problem is nobody built a system to push it to you when it matters instead of waiting for you to pull it once a week.

What’s at risk: calculable. Deal age versus average sales cycle, days since last activity, MEDDIC completeness score, champion engagement rate - these are numbers. An agent can score every deal against them in real time and flag the ones that need attention before they become problems.

What to do next: this is the one part that actually needs judgment. Which is exactly why it shouldn’t be buried in an hour-long review of deals that are fine.

What should you build instead of pipeline reviews?

A deal change digest that arrives Monday morning. Not a report someone generated Sunday night - an automated Slack message, built from live CRM data, that shows every deal that changed stage, every deal where last activity crossed 14 days, every new deal that entered the pipeline, every deal that slipped close date. Two minutes to read. Everything relevant. Nothing that didn’t move.

Real-time risk alerts, not weekly risk reviews. When a deal goes cold, you find out that day - not at the next pipeline call. When a champion changes jobs, an alert fires with their LinkedIn update and a suggested next action. When a deal has been in the same stage for three weeks and average cycle time is two, someone gets a Slack message. The system notices before the human does.

A live forecast that doesn’t need a meeting to exist. If your MEDDIC fields are being populated by agents from call transcripts, if deal health scores are running continuously, if stage progression is being tracked against benchmarks - your forecast is always current. The CRO can open HubSpot on a Thursday and see an accurate picture of the quarter without waiting for someone to compile it.

A weekly exception list, not a full review. The only deals that need human attention are the ones the system flagged as exceptions - high risk, stalled, missing key qualification data, champion gone dark. That’s a 20-minute conversation about five deals, not a 60-minute review of forty.

What does this look like for a team of 8 reps?

You probably have 60+ open deals. Maybe 12 of them actually need attention this week. The other 48 are progressing normally or are in early stages with no action required.

Your current pipeline review treats all 60 the same. An hour to find the 12.

A properly wired system already knows which 12 they are. It told your sales manager at 8am. By the time your Monday meeting starts, three of those deals already have tasks assigned and two reps have already sent follow-ups because they got a Slack alert Friday afternoon.

The meeting didn’t find those deals. The meeting would have found them 72 hours later.

What do you do with the time you get back?

Better 1:1s. Actual deal strategy on the complex opportunities. Coaching conversations based on call transcript analysis, not vibes from a pipeline review. Time to think about the quarter instead of reacting to last week.

The weekly pipeline review isn’t a ritual worth preserving. It’s a workaround that became a habit.

The intelligence is already in your systems. The only question is whether you’ve built the layer that gets it to the right person at the right moment - or whether you’re still scheduling a meeting to go find it.

See how autonomous GTM agents execute without being asked, or why AI belongs in operations, not outbound. For call-level prep that feeds better data into your pipeline, read about the pre-call brief agent.

The pipeline review doesn’t tell you what’s happening. It tells you what happened. Build systems that know the difference.