Yedda.ai extracts actionable insights from existing CCTV infrastructure using computer vision and AI. The company runs a lean engineering operation (3 headcount) paired with a disproportionately large product team (35), suggesting a product-driven rather than platform-infrastructure business—likely built on outsourced or partner engineering. Active challenges around production reliability and competitive differentiation indicate scaling pains typical of vision-AI companies moving from proof-of-concept into production at scale across Southeast Asia and Latin America.
Yedda.ai builds AI-amplification software that analyzes CCTV feeds to measure visual actions and operational compliance in real time. The platform targets retail, wholesale, F&B, manufacturing, and automotive operators who need to monitor performance, service levels, and safety protocols across distributed locations. Founded in 2018, the company operates from Singapore and serves clients across Southeast Asia, Latin America, and beyond. The product stack is modern and containerized (Docker, Kubernetes, cloud-first on AWS and GCP), with development velocity currently minimal despite 46 open roles concentrated in product and senior-level positions.
Yedda.ai runs on AWS and GCP with microservices architecture (Docker, Kubernetes). Development includes Go, Python, Node.js, and C#. CI/CD via GitHub Actions, GitLab CI/CD, and Jenkins. Project management on Jira, Asana, and Trello.
The platform integrates with existing CCTV networks to measure real-time visual actions and operational metrics. It helps retail, F&B, manufacturing, and automotive companies track compliance, service levels, and performance without replacing existing camera infrastructure.
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