One Data offers a software platform that centralizes data ingestion, validation, and governance for enterprise AI workloads, creating a single source of truth through a unified catalog, automated quality checks, and policy‑driven access controls. The platform provides scalable pipelines, real‑time lineage tracking, and native connectors to AI/ML frameworks, enabling data scientists and engineers to retrieve clean, trusted datasets without manual preprocessing.
Funding
$34.9M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
1OFounders
Product
Problem
Enterprises building AI applications often struggle with fragmented, low‑quality data sources and lack a unified platform to ensure data trustworthiness, governance, and seamless integration into machine‑learning pipelines.
Solution
One Data provides a software platform that centralizes data ingestion, validation, and governance for enterprise AI workloads. The platform creates a single source of truth by cataloguing data assets, applying automated quality checks, and enforcing access policies. Integrated pipelines transform and enrich data, delivering clean, trusted datasets directly to downstream models. Real‑time monitoring and audit trails give organizations visibility into data lineage and compliance, reducing the risk of biased or erroneous AI outcomes. By exposing standardized APIs and connectors, One Data enables data scientists and engineers to retrieve ready‑to‑use data without manual preprocessing.
Target Audience
Primary customers are large enterprises and AI teams that need reliable, governed data for building and deploying machine‑learning models, including data engineers, data scientists, and compliance officers.
Features
- Unified data catalog with metadata management and searchable asset registry
- Automated data quality profiling, anomaly detection, and cleansing workflows
- Policy‑driven access control and compliance auditing for regulated data
- Scalable ingestion pipelines supporting batch and streaming sources
- Native connectors to popular AI/ML frameworks and cloud data warehouses
- Real‑time lineage tracking and versioning of datasets for reproducibility