Scowtt uses Python + PyTorch + TensorFlow on GCP and AWS to build AI agents that predict purchase intent and automate lead engagement. The tech stack (ML frameworks + serverless + Salesforce/HubSpot integrations) reflects a product that sits between CRM and ad platforms, routing real-time signals back to Google and Meta bidders. Active hiring spans engineering, data, and support across junior-to-staff levels, with onboarding velocity and churn reduction dominating the project roadmap—a sign they're moving from early wins to product-market fit scaled.
Scowtt is a sales and marketing AI platform founded in 2024 that targets mid-market and enterprise companies seeking to improve lead conversion and ROAS. The product has two core components: a marketing AI layer that scores leads and feeds purchase-intent signals to ad platforms, and an AI sales agent that engages leads 24/7 and routes high-confidence prospects to human reps. The platform integrates with Salesforce, HubSpot, Google Ads, and Meta, pulling CRM and site analytics data to inform real-time bidding and outreach. The company is US-based with 11–50 employees.
Python, PyTorch, TensorFlow, GCP, AWS, BigQuery, Node.js, Next.js, TypeScript, Salesforce, HubSpot, Twilio, AWS Lambda, DynamoDB, and PostgreSQL.
Active projects include marketing AI, AI sales agents, conversion and value prediction models, LLM fine-tuning for agents, continuous training systems, and customer onboarding automation.
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