Cloud-native master data management platform built for enterprise AI agents
Reltio sells a cloud-native master data management platform that unifies and enriches enterprise data in real time for applications and AI agents. Its stack spans AWS, Azure and GCP alongside agent frameworks like LangGraph, Crew AI and AutoGen, matching active work on agentic workflows. Hiring is accelerating and senior-heavy, with engineering, sales and security leading, while job posts flag multi-tenant scaling and global data protection as pressure points.
Reltio, founded in 2011 and headquartered in Redwood Shores, CA, builds a SaaS data platform centered on master data management. The product consolidates and enriches data and metadata from many sources, including unstructured formats, to create unified views of core business entities. It targets large enterprises in life sciences, financial services, healthcare and technology. The privately held company has 201–500 employees and hires across the United States, Canada, the United Kingdom, Portugal and India.
Reltio runs on AWS, Azure and GCP with Kubernetes, Terraform, Helm and Jenkins, builds in Java, Python and React, and uses Kafka, Snowflake, Databricks and BigQuery plus OpenAI, Mistral, Llama and LangGraph.
Job posts point to MDM platform feature development, agentic workflows on Reltio's agent flow platform, infrastructure modernization, AI-powered self-service, and automation for scalability and cost optimization.
Reltio hires in the United States, Canada, the United Kingdom, Portugal and India, with engineering, sales, support, ops and security the most active areas and an accelerating hiring pace.
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Reltio'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.