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.

The MCP Stack for B2B Sales: HubSpot + Slack + Gong + Calendar

The reason most AI in sales doesn’t work isn’t the AI. It’s that the AI can’t see anything. Your CRM is one silo. Your call recordings are another. Slack is another. Email is another. Calendar is another. An AI model that can only see one of those at a time is operating with partial information - which is why its output feels generic.

The MCP stack changes that. Wire HubSpot, Slack, Gong, and Google Calendar together through Model Context Protocol, and suddenly your AI has the same full picture that your best rep has - except it has it for every deal, every contact, every conversation, all the time.

What does the connected MCP stack look like?

Four MCPs form the core of a B2B sales stack:

HubSpot MCP is the foundation - the source of truth for deals, contacts, companies, and pipeline. Claude reads deal stages, property values, activity timelines, and association maps. It writes back updated fields, created tasks, and logged activities. Every agent in the stack reads from and writes to HubSpot.

Slack MCP is the delivery layer. Every alert, digest, brief, and recommendation gets delivered as a Slack message - in the channel or DM where it’s relevant. Reps don’t check a new tool. They check Slack, which they’re already checking 50 times a day.

Gong MCP (or Fathom, or any transcription tool) is the intelligence layer. Call transcripts are the richest data source in your entire stack - what prospects actually said, what objections they raised, what competitors they mentioned, what timeline they committed to. Without transcript access, AI agents are working from CRM fields that are three layers abstracted from reality.

Google Calendar MCP is the trigger layer. Upcoming meetings with external contacts trigger pre-call brief agents. Meeting completions trigger post-call processing. Calendar data tells the system when to act and who’s involved.

How does data flow between these systems?

Here’s what happens when a rep has a call with a prospect at 2pm:

Before the call (triggered by Calendar MCP): 30 minutes prior, the pre-call brief agent fires. It reads the deal record from HubSpot - stage, value, days in stage, open tasks. It pulls the last call transcript from Gong and summarizes what was discussed. It checks activity timeline for recent emails. It profiles the attendees. It delivers a brief to the rep via Slack. The rep walks in prepared.

After the call (triggered by Gong MCP): The transcript becomes available. The MEDDIC extraction agent reads it and populates qualification fields in HubSpot - Metrics, Economic Buyer, Decision Criteria, whatever was mentioned. The competitive intelligence agent checks for competitor mentions and logs them. The action item agent extracts follow-up commitments and creates HubSpot tasks. All of this happens automatically. The rep reviews and moves on.

Continuously (triggered on schedule): The deal risk agent scans every open deal in HubSpot hourly. It checks last activity date, stage velocity, contact engagement patterns, and close date history. When a deal crosses a risk threshold, it sends a Slack alert to the AE with context and a suggested next step.

Weekly (triggered on schedule): The forecast digest agent compiles every deal that changed stage, every new deal, every slipped close date, and every deal that closed. It formats a summary and delivers it to the sales manager and CRO via Slack on Monday morning.

No human initiated any of this. The MCPs provide the connections. The agents provide the logic. The system runs.

Why does connecting everything change the quality of AI output?

An AI that only sees your CRM knows deal stages and field values - the structured data your reps entered (or didn’t).

An AI that also sees call transcripts knows what the prospect actually said. It knows the objections that were raised. It knows the timeline the prospect committed to. It knows whether the rep followed up on what they promised.

An AI that also sees email threads knows what happened between calls. It knows which contacts are responsive and which have gone dark. It knows when a prospect forwarded the proposal internally.

An AI that sees all of this simultaneously can make judgments that no single-source AI can. It can tell you that a deal looks healthy in HubSpot (right stage, recent activity) but the last call transcript revealed the champion is concerned about budget approval - a risk that won’t show up in CRM fields for weeks.

That’s the difference between AI that works from metadata and AI that works from reality.

What if you’re starting from a disconnected stack today?

Most teams are. HubSpot has the deals. Gong has the transcripts. Slack has the conversations. Nothing talks to anything else except through manual copy-paste by reps who don’t have time.

The good news: the MCP stack is additive, not all-or-nothing. Start with HubSpot + Slack. That gives you deal alerts, pipeline digests, and basic automation delivery. Add Gong next - that unlocks transcript-based agents (MEDDIC extraction, competitive intel, call summaries). Add Calendar last for trigger-based agents like pre-call briefs.

Each connection multiplies the value of every other connection. Two MCPs are more than twice as useful as one, because the agents can cross-reference data sources and produce insights that neither source could generate alone.

The full stack - HubSpot + Slack + Gong + Calendar - takes 3-5 days to wire together. Not months. Not a platform migration. Just connections between tools you already own.

Your sales stack already has the data to run an intelligent pipeline. The MCPs are just the wiring that lets AI finally see it all at once.