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Anvilogic and Databricks turn the lakehouse into a full security data platform.
Agentic SecOps on top of infinitely scalable storage, at a fraction of traditional SIEM cost.
Customers have re-platformed their highest-volume security data from legacy SIEMs to Databricks in a matter of days at a fraction of the cost.
Anvilogic translates your existing detections, onboards your feeds, and keeps coverage continuous through the entire move. No data engineering required, no detection gaps, no re-training the team.
There's no rip and replace. Keep your SIEM running today, route new high-volume feeds to Databricks, and run Agentic SecOps across both.
Anvilogic detects, triages, and hunts across your SIEM and your lakehouse as one — so every step of the move is on your schedule, and every step cuts cost.
Existing detections and workflows stay put. Anvilogic connects to Splunk or Sentinel as-is — day one, nothing moves.
Route voluminous feeds like EDR, cloud, network to storage instead of expanding your SIEM license. Onboarding agents land them in minutes.
Detection, triage, and hunting agents operate across SIEM and lakehouse as one — at a fraction of the cost of doing it all in the SIEM.
“The impacts that AI makes across the detection lifecycle, from tuning, to reducing false positives in alert monitoring, to leveraging a cost-effective lakehouse, fundamentally transform the detection engineering process.”
“We were early adopters of the unified workflow Anvilogic and Databricks provide and have been able to transform detection engineering outcomes into business enablers recognized at the board level.”
SIEM pricing charges you for every TB you ingest and every day you keep it. The Lakehouse charges you for data you compute.
Directional, based on customer re-platforming projects at 365 days of retention. Your actual numbers come from a POV.
Data lands in your own object storage at cloud rates. You are never billed per GB indexed.
Spark clusters spin up for a detection job and spin down. Idle capacity costs nothing.
Keep a full year hot in Delta instead of rolling to cold archive after 90 days.
Anvilogic writes and deploys the DLT pipelines, so you do not staff a platform team to do it.
Drop logs into S3, Azure Blob, or Google Cloud Storage. Databricks works directly on the data where it sits, and Anvilogic deploys the Python notebooks that carry it through bronze, silver, and gold as Delta Live Tables, then runs PySpark detections on the gold layer.
Point any feed at cheap object storage. That's your whole job.
Anvilogic deploys the Python notebooks that run as Delta Live Tables inside your workspace — no data engineering required.
Detections run as scheduled PySpark jobs against the gold layer, deployed and tuned by Anvilogic.
Data onboarding agents bring new data feeds into Databricks automatically. You can create your own workflow that samples the raw data feed, maps every field to your schema of choice, and deploy production ETL pipelines. Put a human review step where required and let the agents do the rest.
See a live migration plan for your environment: what moves first, what stays, and what it saves.
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