Close is a sales CRM built for speed—combining deal management, VoIP, automation, and reporting in a single platform. The tech stack is modern and API-first (Python, Flask, MongoDB, PostgreSQL, Elasticsearch, React, GraphQL, WebRTC), and active projects reveal a pivot toward AI: call assistants, drafting tools, and autonomous reply systems are all under development. The challenge they're facing—syncing millions of emails and calendar events at scale—suggests their customer base is growing faster than their infrastructure can comfortably handle.
Close is a bootstrapped, profitable CRM platform for small-business sales teams. The product integrates deal tracking, VoIP calling (via Twilio), email automation, sales coaching, and reporting into one interface, with a design philosophy centered on speed and ease of use. Built by a 100+ person, fully remote team across the United States, Close serves inside-sales operations. Recent hiring has accelerated across marketing, engineering, support, and product roles, and current development priorities are weighted heavily toward AI-driven features (call assistants, email drafting, autonomous responses) alongside API performance improvements.
Close uses Python and Flask for backend services, MongoDB and PostgreSQL for data storage, Elasticsearch for search, and React for frontend UI. Infrastructure runs on AWS (EKS, MSK, RDS), with Kubernetes and Terraform for orchestration. Communication layers use Twilio, WebRTC, and WebSockets.
Close is developing AI features including an AI-powered call assistant, AI drafting tools, and autonomous reply systems. Other priorities include improving GraphQL and REST API performance, building new user-facing features, and internal automation improvements.
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Close'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.