Mindlyft
Custom GTM systems built in your stack, approved by you
Mindlyft is GTM engineering on subscription for B2B tech companies. We call it service as a software: we build the custom systems your team needs, tailored to how your business works, and run them inside the stack you already pay for. Every promise from a customer call becomes the CRM update, the ticket and the recap. Powered by A.S.T.R.A., an approval and audit layer: every agent action is human-approved, reversible and logged, and nothing customer-facing goes out without your yes.
Features
Call outcomes turned into CRM updates, tickets and recaps
Handoffs posted, renewal risk flagged, required fields enforced, duplicates merged
Runs inside Salesforce, HubSpot, Jira, Slack and Gmail
Approval on every customer-facing step; every action logged and reversible
We build and run it first, then your team takes over
Use Cases
Acquire: B2B teams with a working sales motion and more pipeline work than people
Expand: teams whose handoffs, onboarding and renewals leak revenue
Keeping the CRM current after every customer call without manual updates
Adding approval and audit over AI agents already touching your go-to-market
Comments
Hey Fazier, I'm Harshit. I spent 6+ years at Adobe, New Relic and Freshworks working with 1,000+ customer accounts, and the same thing kept breaking: what a customer was promised on a call rarely made it into the CRM, the ticket queue or the follow-up. Mindlyft builds that follow-through inside the stack you already use, and nothing customer-facing goes out without your yes. Happy to answer anything about how it works, or what we got wrong along the way.
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Comments
Hey Fazier, I'm Harshit. I spent 6+ years at Adobe, New Relic and Freshworks working with 1,000+ customer accounts, and the same thing kept breaking: what a customer was promised on a call rarely made it into the CRM, the ticket queue or the follow-up. Mindlyft builds that follow-through inside the stack you already use, and nothing customer-facing goes out without your yes. Happy to answer anything about how it works, or what we got wrong along the way.
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