Case Study
How a Fortune 100 Telecom Automates Data Onboarding with Anvilogic on Snowflake
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A Fortune 100 telecom is building its security data lake on Snowflake. Anvilogic turns the raw feeds landing there into normalized detection sources and runs the team's detections directly on that data.
$1M
In consulting scope cut
82%
Priority attack techniques covered
3× faster
To deploy an emergency detection
“Anvilogic is central to our SOC strategy. As we diversify our data strategy to include data lakes, Anvilogic lets us continue SOC operations while giving analysts the ability to reach across data repos.”
Security Leadership
The Challenge
Every feed had to be parsed and normalized by hand. The company hired nine data engineers, at about $1M a quarter, and still had 100+ feeds with no detection coverage.
The Objective
- Clear the backlog of data feeds
- Automate parsing, normalization, and ETL
- Reduce reliance on hand-built ETL
How They Did It
Anvilogic Onboard
A Blueprint parses and normalizes each raw Snowflake feed, with an analyst approving every step.
Anvilogic Blueprints
The company's teams build their own Blueprints to automate work they did by hand.
Anvilogic Federated Search
Analysts query Snowflake, Splunk, and SentinelOne from one place, without moving the data.
The Results
- $1M in consulting scope cut, re-purposed to higher-value work.
- 82% of priority attack techniques covered, up from 63% in January 2026.
- 3× faster to deploy an emergency detection, 15 minutes, down from 45 to 60.
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