AI-native cloud engineering and automation services
Agivant is a 51–200-person AI-first engineering services firm headquartered in Silicon Valley, positioned around cloud transformation, platform engineering, and agentic AI. The tech stack reveals a modern infrastructure-as-code and MLOps foundation (Terraform, Pulumi, Argo CD, Kubernetes, TensorFlow, PyTorch, LangChain) paired with active execution on AI-assisted testing and distributed systems — a hiring mix skewed toward senior engineers and specialized data roles signals a high-complexity, delivery-focused operation rather than a headcount-scaling model.
Notable leadership hires: IT Head
Agivant delivers cloud engineering, digital transformation, and AI automation services to enterprise clients. The firm operates across three core areas: cloud architecture and migration (Kubernetes, multi-cloud infrastructure), MLOps and agentic AI (LangChain, RAG, LlamaIndex), and intelligent testing automation (AI-powered test generation and log analysis). Current project work spans K8s CI/CD optimization, backup/disaster recovery, client IT governance, and distributed data ingestion systems. The company is actively hiring senior engineers and technical leads in India and the United States.
Agivant uses Terraform, Kubernetes, Python, AWS/Azure/GCP, Docker, TensorFlow, PyTorch, LangChain, LlamaIndex, and RAG frameworks. Infrastructure tooling includes Argo CD, Ansible, Vault, Prometheus, and Grafana.
Active projects include agentic AI applications, Kubernetes CI/CD optimization, cloud migration roadmaps, automated testing frameworks, AI-powered test data generation, distributed data ingestion, and IT governance solutions.
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Agivant Technologies'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.