Deal management and investment operating platform for real estate investors
Dealpath builds software that runs the real estate investment lifecycle, from deal sourcing through portfolio management, on a Ruby, Python, Go and TypeScript stack hosted on AWS EKS and RDS. New adoption of GCP, Vertex AI, LangSmith and DeepEval points to an LLM build-out with formal evaluation tooling, while engineering-led hiring sits alongside a heavy post-sale focus on implementation, renewals and upsell.
Notable leadership hires: Strategic Account Director
Dealpath, founded in 2014 and headquartered in San Francisco, CA, provides an AI-enabled platform for commercial real estate investment firms. The product spans deal sourcing, pipeline tracking, market intelligence, investment data, execution workflows, reporting and portfolio tracking. Customers range from large institutional investors to mid-market and regional firms. The company is privately held, employs 51–200 people, and hires in the United States across engineering, operations, sales, product, support and marketing.
Dealpath uses Ruby, Python, Go, TypeScript, React, Node.js and Flask on AWS (EKS, RDS) with PostgreSQL, OpenSearch, Datadog, Sentry, Looker and Mixpanel, plus Salesforce and Outreach for sales.
Yes. Dealpath is adopting GCP, Vertex AI, LangSmith and DeepEval, and job posts reference AI-driven prototypes for enterprise clients and AI-assisted development workflows.
Dealpath is headquartered in San Francisco, CA, has 51–200 employees, and currently hires in the United States.
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Dealpath's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.