Enterprise AI implementation firm building agentic and LLM-based solutions
Cognida builds and deploys AI solutions for enterprises, pairing consulting with engineering on a multi-cloud stack spanning AWS, GCP and Azure, with Databricks, MLflow and both OpenAI and Anthropic models. Pain points cluster around production AI economics (model drift, latency cliffs, token cost control), signaling a shift from prototypes to cost-metered, production-grade agentic systems. Senior-heavy hiring in the US and India points to delivery capacity, not junior scale-up.
Notable leadership hires: Head of IT
Cognida is a privately held enterprise AI solutions provider founded in 2022 and headquartered in Sunnyvale, California. It offers an agentic accelerator platform called Zunō alongside implementation services covering machine learning, generative AI, data engineering and analytics. The company serves North American enterprises in manufacturing, retail, financial services, healthcare and life sciences, logistics and technology. It employs 201–500 people, with teams across North America and India.
Cognida works with Python, Java, Node.js, Spring Boot, React and Angular, runs on AWS, GCP and Azure, and uses Databricks, Apache Spark, Delta Lake, MLflow, Kafka, PostgreSQL and MongoDB, plus OpenAI and Anthropic models.
Job posts point to scalable AI architecture, moving models from proof of concept to production, multi-agent workflows, LLM-based structured extraction from unstructured data, and per-operation cost metering for AI workloads.
Cognida is hiring in the United States and India, with hiring accelerating and focused on senior engineering roles, plus data, operations and a Head of IT position.
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Cognida'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.