Unravel offers an AI‑driven data observability platform that continuously monitors performance, cost, and data quality across major cloud data warehouses and processing engines. The system automatically generates and applies optimization actions, delivering real‑time insights and FinOps analytics through a dashboard and API to help data engineering teams meet SLA targets and reduce cloud spend.
Funding
$50M 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.
4OTPFounders
Product
Problem
Data engineering teams spend a large portion of their time manually tuning pipelines and troubleshooting performance issues, leading to missed service-level agreements, escalating cloud costs, and reduced productivity.
Solution
Unravel provides an AI‑driven data observability platform that automatically analyzes workloads on major data platforms such as Databricks, Snowflake, BigQuery, Amazon EMR, and Cloudera. The system continuously monitors performance, cost, and data quality metrics, then applies autonomous optimization recommendations to accelerate pipelines and lower resource consumption. By surfacing actionable insights and executing fixes without human intervention, Unravel reduces the need for manual tuning and endless support tickets. The platform integrates with existing CI/CD pipelines and offers a self‑service health‑check tour, enabling data teams to meet SLA targets and achieve measurable FinOps savings. Results are delivered through a web dashboard and API endpoints that support further automation and reporting.
Target Audience
Primary customers are data engineering and platform operations teams at enterprises that run large‑scale analytics workloads on cloud data platforms, as well as data platform owners responsible for cost and performance governance.
Features
- Real‑time observability across multiple cloud data platforms (Databricks, Snowflake, BigQuery, EMR, Cloudera)
- Agentic AI that automatically generates and applies performance and cost optimization actions
- End‑to‑end monitoring of pipeline latency, resource utilization, and data quality anomalies
- Integrated FinOps analytics that quantify cost savings and track budget compliance
- API and CI/CD integrations for seamless incorporation into existing data engineering workflows
- Self‑guided health‑check tours and free assessments to demonstrate impact before deployment