The founder is still the routing layer
Important account context lives in the founder's head. Reps need help deciding who to contact, what matters, and when to hold back.
GTM engineering partner
GTM engineering for AI workflows that know how your company sells.
Cheetah is a GTM engineering and AI implementation partner for founder-led and complex B2B teams. We connect the tools you already use, map the context behind good decisions, and deploy workflows your team can trust and maintain.
Direct answer
What is a GTM engineering partner?
A GTM engineering partner designs and implements the data, automation, and AI workflows behind a revenue team. The work sits between RevOps, data engineering, and day-to-day sales execution.
A good partner does more than connect software. They capture your ICP rules, account history, buying signals, suppression logic, messaging guidance, and approval decisions. Then they make that context available to every workflow that needs it.
Cheetah uses a Context Graph as that shared layer. Your CRM, enrichment, conversation data, and operating rules stop living in separate automations. Agents can check what happened before, why a decision was made, and what should happen next.
When to hire
Bring in a partner when the stack works, but the system does not.
Point tools keep multiplying
Clay, HubSpot, Gong, sequencers, and intent sources all work, but each workflow rebuilds identity, rules, and history from scratch.
AI output is hard to trust
Agents produce plausible messages or scores without checking prior outreach, deal stages, exclusions, or the team's real playbook.
You need a system before another hire
A full-time GTM engineer makes sense when the roadmap is stable and there is enough ongoing work. A partner is useful when you first need to find the right architecture, ship it, and prove the operating model.
Partner or in-house?
Choose based on the work, not the job title.
| Situation | Hire in-house | Use a GTM engineering partner |
|---|---|---|
| Roadmap | Stable backlog with a clear owner | Architecture and priorities still need to be worked out |
| Skills needed | One role can cover most of the work | The build crosses RevOps, data, AI, integrations, and enablement |
| Speed | You can support recruiting and ramp time | You need a working first workflow before committing to headcount |
| Ownership | The team already knows what to own | You want the system, documentation, and operating rhythm transferred to your team |
How Cheetah works
Aggregate. Resolve. Execute.
Bring the signal together
Connect CRM records, email, Gong, Slack, enrichment, intent data, and campaign history. We start with the sources needed for one high-value workflow.
Build identity and decision context
Match people, accounts, interactions, and rules into canonical records. The graph keeps the evidence behind scores, routing, and agent decisions.
Deploy with checks in the loop
Agents query the graph before they act. They can qualify, draft, route, or hold an account based on the same context your best operator would check.
Operate and improve
Implementation is not the end of the engagement. We review decision traces, update rules, fix weak data paths, and add workflows only when the first one is stable. Your team keeps the logic, documentation, and history.
Proof in the product
What Cheetah already knows how to do
These are implementation examples shown in Cheetah today, not projected customer results.
Enterprise ABM qualification
An agent checks account history and past outreach, enriches current company data through Clay, reviews funding, hiring, and tech changes, then applies a timing threshold before routing the account.
Signal-based outbound
Series C funding, a sales hiring post, and a new office can become structured signals. The workflow uses those signals with account history to choose a sequence and draft relevant outreach.
Shared context across agents
Sales, marketing, and customer workflows can query the same Context Graph instead of building separate memory inside each automation.
Works with the stack you already have
HubSpotSalesforceClayApolloOutreachGongSmartleadLemlistInstantlyZoomInfoSlackEmail
Common questions
Before you hire a GTM engineering partner
Do you replace our CRM or sales tools?
No. Cheetah connects the tools already in your stack and adds a shared context layer. We only recommend replacing a tool when it blocks the workflow or creates avoidable data risk.
What should the first workflow be?
Start where a repeated revenue decision depends on data from several places. Account qualification, signal-based outbound, lead routing, re-engagement, and enterprise ABM are common candidates.
How is this different from a generic automation agency?
The work begins with decision context, not a list of tool connections. We model the identity, history, rules, and evidence an operator needs before we automate the action.
Can our team maintain what you build?
That is the goal. The engagement includes the workflow logic, decision traces, and operating documentation so your team can inspect and change the system.
Start with one workflow worth fixing.
Tell us where context breaks today. We will map the stack, the decisions, and the smallest useful implementation.
Talk through the first workflow