Ripik.AI builds computer vision agents for steel, cement, and chemicals manufacturing—automating visual inspection and process monitoring 24/7. The tech stack (PyTorch, TensorFlow, OpenCV, TensorRT, ONNX) is purpose-built for production ML inference, while active projects focus on scaling these pipelines across multiple production sites and deploying hardware-accelerated anomaly detection. Pain points around real-time performance and infrastructure reliability signal an engineering org focused on moving from proof-of-concept deployments into high-volume, multi-site rollouts.
Tech Stack 32 technologies
Core StackJava Python React MySQL PostgreSQL MongoDB AWS SAP Oracle Redux JavaScript Figma PyTorch TensorFlow Docker SQL HBase GCP Azure Tally Zoho Excel Chart.js D3.js Recharts REST API Adobe XD OpenCV TensorRT ONNX+2 more
What Ripik.AI Is Building
◆Challenges
- Reducing downtime
- Real-time performance optimization
- Compliance with gst and tax regulations
- Audit query resolution
- Working capital management
- Strong governance practices
- Timely legal compliance
- Automation of decision making on the factory floor
- Anomaly detection in manufacturing
- Ensuring scalability and reliability of infrastructure
▲Active Projects
- Product replication across business sites
- Manufacturing ai platform scaling
- New product feature development
- Vision ai solutions for anomaly detection in cement and steel manufacturing
- Scalable ml pipelines for production environments
- Installation and commissioning of ai hardware
- Integration of ai tools for real-time monitoring
- End-to-end ai pipelines for computer vision
- Scaling ai products across production lines
- Deploying ml pipelines into production
Hiring Activity
Steady15 roles · 6 in 30d
Department
Seniority
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