Procure Ai builds an AI-native procurement platform using Python, TypeScript, Go, and cloud infrastructure (AWS, Azure, GCP) to automate end-to-end procurement workflows. The tech stack—Kafka, Spark, Airflow, Databricks—reflects heavy investment in data pipelines and real-time processing, suggesting the platform is built around extracting signal from fragmented procurement data sources. Engineering-heavy hiring (6 of 11 active roles) paired with active work on a procurement data graph and serverless ingestion pipelines indicates the company is scaling the data foundation that enables AI agents to operate autonomously.
Procure Ai is a London-based AI technology provider founded in 2020 that automates procurement operations for mid-market and enterprise buyers. The platform combines agentic AI, predictive analytics, and autonomous execution to handle administrative procurement tasks, reduce costs, and surface strategic opportunities. The product is structured around three areas: intelligent data extraction and enrichment, a unified procurement data model, and AI-driven workflow automation. The company operates with 51–200 employees, currently hiring engineers and product roles in Germany and France, with steady velocity.
Python, TypeScript, Go, React, Node.js on AWS, Azure, and GCP. Data layer: PostgreSQL, Kafka, Apache Spark, Airflow, and Databricks. Orchestration via Docker, Kubernetes, Terraform, and CloudFormation.
An intelligent procurement data platform, serverless data ingestion pipelines, a procurement data graph, customer onboarding, and integrations with third-party procurement systems. Addressing data gaps is a core challenge.
Procure Ai'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.