Pricing

Tailored Strategy. Predictable Investments.

GammaFlow builds custom GTM AI agent deployments around your workflows, systems, governance needs, and revenue objectives. Pricing is scoped after we understand the automation opportunity.

Custom-scoped engagements are priced after diagnostic alignment.

Because we build custom teams around your specific objectives, final pricing is determined collaboratively after our initial diagnostic alignment.

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What drives scope

Pricing is tied to workflow complexity, systems, and deployment depth.

The goal of the pricing page is not to hide the ball. It is to make sure the conversation starts at the right level: enterprise GTM teams, real workflows, system integrations, and measurable operating outcomes.

  • Number of workflows being scoped, built, tested, and monitored.
  • Depth of CRM, marketing automation, sales engagement, analytics, and data integrations.
  • Governance requirements, approval paths, auditability, and security review.
  • Amount of custom prompt, data, routing, reporting, and workflow orchestration required.
  • Level of enablement needed for marketing, sales, RevOps, and technical stakeholders.

Minimum engagement framework

Built for teams that want a partner, not a template.

01

Diagnostic alignment

We identify the first workflow, required systems, stakeholder map, risk points, and success metrics.

02

Alpha deployment

We build the first practical agent workflow around your real data, tools, approval paths, and constraints.

03

Scale plan

We document what worked, where to expand, and how to roll the playbook across additional revenue workflows.

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If the floor makes sense and you have a workflow worth automating, the next step is a working session. We will identify the first GTM AI agent deployment and the likely scope.

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Common fit signals

When pricing usually makes sense.

  • Your GTM team is already spending meaningful time on repeatable manual workflow coordination.
  • You have Salesforce, HubSpot, sales engagement, enrichment, analytics, or internal data systems in place.
  • The workflow has a clear owner, business impact, and enough examples to test against.
  • You need a governed deployment path rather than disconnected AI experiments.