OGAdvisors
AI agents that read email, enrich leads, and keep HubSpot accurate with almost no manual upkeep
The Challenge
Sales and support emails arrived with no clear link to existing deals: reps searched HubSpot manually, logged conversations against the wrong record, or let deals slip because none was ever created. Inbound leads landed unenriched, so qualifying and routing them was manual guesswork.
The Solution
Two production AI systems on HubSpot. First, an event-driven NLP pipeline (n8n, Python, AWS) that reads each inbound email, extracts entities and intent, matches it to the right deal, and creates a new deal automatically when none exists. Second, a multi-agent lead system that enriches every lead with firmographic and funding data from CrunchBase and the web, normalizes and dedupes it, computes a dynamic quality score, assigns the lifecycle stage, and routes each lead to the right pipeline and owner in real time.
An advisory services firm whose sales and support emails arrived with no link to existing deals, and whose inbound leads needed manual research before anyone could act. We built two production AI systems on their HubSpot CRM: an NLP pipeline that reads every inbound email and files it against the right deal (creating one when none exists), and a multi-agent lead enrichment system that scores, classifies, and routes every lead in real time.
"Emails are associated with the correct deal automatically, missing deals are created on the fly, and the sales pipeline reflects reality with far less manual upkeep."
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