Unravel Data

Data observability platform

Unravel Data logo
101-200 employees
  • B2B
  • Artificial Intelligence
  • Big data
  • SaaS
  • Cloud Computing
Palo Alto, CA

Company mission

To help data teams stop firefighting issues, control costs, and run faster data pipelines.

Top investors

30% employee growth in 12 months

Our take

As businesses continue to grow their data footprint, it's becoming increasingly challenging for them to track, diagnose, and troubleshoot problems in their data operations. Unravel collects performance data from every platform, system, and application - on any cloud - and then uses agentless technologies and machine learning to model a business' data pipelines from end to end.

Unravel serves every member of a data team, across FinOps, DataOps, and Data Apps. Its comprehensive platform delivers AI-driven answers and actionable recommendations; to reduce cloud costs, optimize pipelines, diagnose and tackle errors, and aid cloud migration.

Unravel has an impressive client list that includes a good number of Fortune 100 companies. It has raised a substantial amount of funding, and is focused on bringing new capabilities to its products through a frequent schedule of new releases and updates.

Kirsty headshot

Kirsty

Company Specialist at Welcome to the Jungle

Benefits

  • Flexible Hours - The freedom to work when you work best
  • 401(k) plan and stock options
  • Unlimited PTO - Because people do their best well-rested and unstressed
  • Free Gym - Stay fit, stay healthy and stay happy with free gym Membership
  • Free Snacks and Meals - A fully stocked kitchen and free lunches
  • Platinum Healthcare Plan - For the health and wellness you and your family deserve

Funding (last 2 of 5 rounds)

Sep 2022

$50m

SERIES D

May 2019

$35m

SERIES C

Total funding: $107.2m

This company has top investors

Leadership

MBA from Duke University. Previously Sales Director at eOne Infotech, with experience at Sun Microsystems and Affymetrix.

PhD in Data Platforms from Stanford University. Previously Adjunct Professor Of Computer Science at Duke University.