Convin applies conversation intelligence to automate quality assurance and coaching at contact centers. The stack—Python, Kafka, PostgreSQL, Redis, with ChatGPT, LLAMA, and Falcon for language models—shows a company building ML-heavy analytics on streaming call data. Active projects around speech systems and large-scale model training, paired with pain points in model accuracy and productionization, signal Convin is in active R&D to improve core AI capabilities while scaling beyond its seed-stage foundation.
Convin is a contact center software company that uses conversation intelligence to automate quality assurance, uncover coaching opportunities, and improve agent performance. The platform processes high-volume call data to identify business-driving behaviors and auto-generate personalized coaching. Founded in 2020 by four IIT Delhi alumni, Convin is based in Bengaluru and serves global enterprises across verticals. The company is actively investing in security infrastructure (ISO 27001 implementation, VAPT engagement) and ML infrastructure (speech systems, large-language-model training) to support compliance and product maturity.
Convin runs on AWS, GCP, and Oracle Cloud with PostgreSQL, Redis, and Kafka as core data infrastructure. Python and C++ power the backend, while ChatGPT, LLAMA, and Falcon drive conversation AI. CI/CD is managed with Docker, Kubernetes, Jenkins, and Bitbucket Pipelines.
Active projects include AI-driven conversation analytics, speech and language systems, large-scale language model training, and ISO 27001 compliance implementation. Internal priorities center on improving model accuracy and productionizing ML solutions at scale.
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