Adapt connects carrier portals so insurance agencies can retrieve documents, standardize naming, and route notifications automatically.
When Karim Yahia joined as Adapt’s founding GTM engineer, the stack was conventional but disconnected: HubSpot as the CRM, Apollo as the primary enrichment source, and ZoomInfo seats that were rarely used because they sat outside the team’s day-to-day workflow. There was no data warehouse and almost no built enrichment workflow.
Adapt sells to independent P&C insurance agencies. Account records were sparse and inconsistent, so reps filled gaps by cross-checking vendors, using the CRM directly, or patching issues with their own AI tools. There was no account prioritization or scoring, and very little top-of-funnel signal reached the team.
Individual workarounds had accumulated across personal automations and native workflow builders. They were useful to the person who built them, but difficult for the rest of the team to discover, safely change, or reuse. A coding agent could not see them either.
The result was not another dashboard. It was a durable way to find, decide, and act on GTM signals.
Adapt started with TAM enrichment, using a waterfall across providers so one vendor’s gaps do not become blank CRM fields. That work exposed duplicate account fields, duplicate data, and inconsistent CRM modelling that had been hidden in daily operations. Deepline became the layer its coding agents use instead of writing directly to HubSpot and running into rate limits.
The team combines de-anonymized website visitors, LinkedIn page visitors, and semantic and keyword searches across social platforms. Because Adapt’s ICP is so narrow, a relevant site visitor has unusually high signal. Each signal filters by ICP, enriches the contact, and pulls existing HubSpot context before it reaches a shared Slack channel.
The hard part was surfacing a fragmented set of existing rep-built processes and migrating them without breaking downstream dependencies. The result is a central library of Deepline Plays that the whole team can see, review, and improve.
Build a complete account foundation first, so segmentation, targeting, and later persona enrichment have dependable inputs.
Package ICP filtering, enrichment, and CRM context into repeatable Plays instead of rebuilding the same one-off script.
Bring scattered rep workflows into one visible system gradually, preserving what depends on them while replacing the patchwork.
“GTM engineering is largely a CRUD problem. GTM, outside of the human connection, can be expressed as code — and then it becomes so much easier for a coding agent to understand your GTM.”
Karim Yahia
Founding GTM Engineer, Adapt
Nearly every GTM workflow at Adapt now runs as a Deepline Play, with the relevant customer data in one shared database rather than spread across tools and personal automations. Routine fixes typically take 10–15 minutes, and the team now sends roughly 20–30 signal alerts a day. Those alerts feed a meaningful share of newly created opportunities.