How Do We Architect Custom GTM AI Agents?
Every build starts with your actual workflows and data, not a template. We design, integrate, test, and deploy in structured phases with clear handoffs.

GTM Workflow Discovery and Signal Mapping
We audit your current GTM motions, identify where agents can act on real signals, and document the workflow logic before any build begins.

ICP Definition and Data Readiness Audit
We review your ICP criteria, CRM data quality, and enrichment sources to confirm that the data foundation can support accurate agent decisions at scale.

Agent Architecture and LLM Selection
We define the agent topology — single or multi-agent — and select LLMs based on latency, accuracy, and your data residency requirements.

CRM and Stack Integration Setup
We build and test authenticated API connections to your CRM, sequencers, and enrichment tools before any agent begins executing live workflow tasks.

Accuracy and Personalization Testing
Agents run against historical data and live test accounts to validate scoring accuracy, outreach quality, and task completion rates before production access.

Pilot Deployment With Human Oversight
Initial production deployment includes a human-in-the-loop review layer so your team can audit outputs and approve edge cases before full autonomy.

Full Rollout
After pilot sign-off, agents move into full deployment across teams, workflows, and systems, ensuring the solution is operationalized beyond testing and ready for scale.

Continuous Retraining
Agents are regularly retrained using updated ICP criteria, market shifts, and new deal data, keeping performance aligned with evolving GTM priorities and buyer behavior.