Autolake provides a fully managed, autonomous data lake platform that automatically ingests, curates, and governs enterprise data in the customer’s cloud.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises often struggle with fragmented data sources, manual pipeline development, and ongoing maintenance of data lakes, leading to costly delays, governance risks, and underutilized analytics potential.
Solution
Autolake delivers a fully managed, autonomous data lake platform that automatically ingests, curates, and governs enterprise data within the customer’s cloud environment. The service provides built‑in transformation, masking, and slowly changing dimension support, while automatically handling schema evolution and self‑healing pipelines. Curated datasets are exposed instantly through REST APIs, BI tools, and AI/ML platforms, and users can query the lake with natural‑language prompts for immediate insights. Continuous monitoring of data usage, compliance, and performance ensures reliable operation without manual intervention.
Target Audience
Primary customers are mid‑size to large enterprises that need a production‑ready data lake without building and maintaining custom pipelines, including data engineering teams, analytics departments, and AI/ML practitioners.
Features
- Automated data ingestion with incremental, snapshot, and full‑load modes, plus AI‑powered ingestion optimization
- Built‑in data curation tools for transformation, masking, data profiling, and SCD handling
- Smart schema evolution that detects compatible changes and pauses on breaking changes for review
- Self‑healing pipelines and autonomous lifecycle management, including automated scaling, healing, and optimization
- Instant data distribution via REST APIs, BI integrations, and AI/ML platform connectors
- Natural‑language query interface that returns answers directly from curated data
- Fine‑grained access control, unified catalog integration, and data encryption/compression for governance and security