Anvilogic vs. Vega
Automate your SOC without rebuilding your stack
Vega brings federated analytics and detection across distributed security data. Anvilogic goes further, automating work across data onboarding, search, detection, and investigation while your data stays in the systems you already use.
Get a demoGo beyond detection and investigation
Security operations don't start with an alert. Teams have to onboard and understand new data, search across environments, identify coverage gaps, build and tune detections, investigate what fires, and carry decisions through to resolution.
Anvilogic connects that work across four core areas of security operations:
Make new security data usable faster.
Profile and map new feeds, understand their schemas, and identify coverage opportunities without requiring the data to move first.
Search across the data you already have.
Ask questions across SIEMs, data lakes, cloud storage, and security platforms without centralizing everything into another repository.
Turn gaps into coverage.
Identify coverage gaps, build and tune detections, and deploy them into the systems where your data already lives.
Move from alert to decided case.
Triage and investigate alerts with the context needed to understand what happened, make a decision, and carry the case forward.
At a glance
Anvilogic and Vega both work across security data that lives in multiple systems. The difference is how they operate across that environment.
| Vega | Anvilogic | |
|---|---|---|
| Detection execution | Runs through Vega's distributed analytics layer | Runs natively in Splunk, Sentinel, Snowflake, Databricks, and more |
| Query language | Vega KQL | SPL, KQL, SQL, and each platform's native syntax |
| Search | Federated across connected sources | Federated across Splunk, Sentinel, Elastic, CrowdStrike LogScale, Snowflake, Databricks, Azure, S3, and more |
| What you stand up first | Connectors into Vega, plus Vega's index | Access to the repositories you already run |
| Detection content | Detection Skills attached to detections, open spec | Thousands of MITRE-mapped detections maintained by a dedicated threat research team, plus detection-as-code and a Dev Kit |
| Automation model | Skills attach reasoning to detections | Blueprints orchestrate workflows across Onboard, Search, Detect, and Investigate |
| Case workflow | Triage to verdict | Triage, investigation, case management, and disposition |
| Response handoff | BlinkOps | Tines, Torq, ServiceNow, Jira, and more |
Why the difference matters
Automate more of the work around the alert
An alert is only one point in the SOC workflow. Anvilogic automation can start before an alert exists, with onboarding new data, searching across environments, identifying coverage gaps, and building and tuning detections. When an alert fires, that work continues through triage, investigation, case management, and disposition. Blueprints orchestrate those workflows across agents, tools, and human approval points, so automation isn't limited to a single detection or task.
Keep the security investments you've already made
Adopting AI shouldn't require another data migration or a new system of record. Anvilogic operates across the SIEMs, data lakes, cloud storage, and security platforms your team already uses. Detections deploy into the systems holding the data in the languages your engineers already know, while federated search lets teams investigate across connected environments. Your existing infrastructure stays in place while AI works across it.
Give AI the context of your SOC
Your analysts don't make decisions based on an alert alone. They know your data, your detections, the changes your team has made, and how similar situations have been handled before. The Anvilogic Enterprise Security Graph connects feeds, schemas, detections, alerts, tuning decisions, and investigation outcomes so agents understand what things mean in your environment and carry that context across the work.
Anvilogic is proven in complex, enterprise environments
"We were early adopters of the unified workflow Anvilogic and Databricks provide and have been able to bring detection engineering outcomes to business enablers recognized at the board level."
Zendesk brings a new data feed online in about seven minutes, roughly ten times faster than its previous process, without committing the team to a single underlying repository.
"Anvilogic is the perfect solution because it doesn't depend on any specific underlying data lake or SIEM. It isolates and abstracts the layer of data storage down to the schema."
Bring us a real test
Bring us a source you haven't onboarded yet. We'll make it detection-ready, deploy a detection against it, and take the first alert it produces through to a decided case, on the platforms you already run.
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