Anvilogic

Anvilogic's core argument is architectural rather than feature-based, and it is worth understanding before you evaluate anything else. Most security platforms ask you to move your data into them. Anvilogic instead sits on top of storage you already own — Amazon S3, Azure Blob Storage, Google Cloud Storage — and the SIEMs and data lakes you already run, like Splunk, Microsoft Sentinel, CrowdStrike NG-SIEM, Elastic, Snowflake, Databricks, Azure Data Explorer, Azure Log Analytics, Microsoft Fabric, and Amazon Security Lake. Search Agents issue one query across Splunk, Snowflake, Sentinel, and S3 without moving the data. That is the single most useful thing the product does for a mid-to-large SOC, because it means you can start shifting security analytics to a cheaper data lake incrementally without a wholesale migration. The second strength is detection engineering depth, which is not a side feature here. The Custom Detection Builder, the Threat Detection Library of curated MITRE-mapped rules and scenarios, Detection Coverage Maturity tracking for MITRE coverage and feed quality, and Automated Detection Tuning with ML recommendations together cover the full lifecycle of writing, deploying, tuning, and proving a detection. Correlated Threat Scenarios and Threat Prioritization extend that into multi-stage attack correlation. For a detection engineer who currently maintains parallel rule sets in Splunk and Sentinel, this is the workflow that justifies the purchase. The 8.0 release, generally available as of the vendor's August 2026 announcement, adds two things that used to be missing. Case management now carries an alert from triage through to resolved without switching tools mid-investigation, and the SafeBreach integration uses breach and attack simulation to confirm that deployed detections actually fire and cover the tactics you claim. Blueprints reached general availability in the same release, tying Onboard, Search, Detect, and Investigate agents into repeatable step-by-step workflows. Federated search was rebuilt on Anvilogic Compute. The Anvilogic MCP layer connects to OpenAI and Anthropic AI systems plus third-party MCP connectors, which matters if your team already has an AI stack it wants to route SOC workflows through. Where it does not fit: this is not a SIEM. It presumes an existing security data environment and a detection engineering function that will act on tuning recommendations and coverage gaps. A small team with one simple SIEM and little custom detection work will pay for capability it never exercises. The platform also assumes someone owns detection quality — the ML tuning recommendations and coverage scoring are only useful if a human closes the loop. On commercial terms: there is a genuine $0/mo Features tier with Detection Armory, Detection Lifecycle Management, Threat Research & Intel, Tasks & Workspace, Workflow Automation, Maturity Scoring, Feed Quality Analysis, and Detection Coverage Improvement Recommendations,