Start Your Free Trial

Anvilogic’s 30-day free trial offers you a way to see our AI-powered detection engineering and hunting platform in action.

Frictionless

No need to change processes or existing workflows with your current operations team or deploy agents.

Minimal Effort

Very little time and effort from your team is required to set up the trial. You can choose to use your data or our sandbox data.

Guaranteed Value

Keep any detections developed during the trial. If using your own data, we’ll calculate the cost savings & ROI specific to your environment.

Get Started By Picking Your Data Platform

Pick Your Data Platform

Snowflake

Adopt a SIEM-less architecture over time with a cost-effective data lake while improving your SOC maturity.

Anvilogic for Snowflake

Splunk

Build SPL detections in minutes, automate detection as code, and hunt across Splunk, Snowflake, or Azure.

Anvilogic for Splunk

Azure

Build KQL detections in minutes, automate detection as code, and hunt across Splunk, Snowflake, or Azure.

Anvilogic for Azure

How The Free Trial Works

Step 1

Define Your MITRE ATT&CK Priorities

Quickly customize the MITRE ATT&CK framework to focus on the techniques that matter most to your organization based on the platforms you protect and the threat groups that target your industry. This drives what detections and data feeds you must log to be successful at detecting those attack techniques.

Pick Your Data Platform & Onboard Feeds
Step 2

Pick Your Data Platform, Onboard Feeds & Explore Cost Savings

A key difference in Anvilogic’s platform is that you can “bring your own data lake(s)”. We support Splunk Cloud, Snowflake, and Azure Sentinel/Log Analytics. Pick which platform(s) you want to connect. Based on your MITRE ATT&CK priorities, we will recommend up to 2-3 data feeds to test during the free trial if you choose to use your own data. Then we’ll show you cost saving scenarios if you’d like to move any data feeds to a low-cost security data lake like Snowflake.

Pick Your Data Platform & Onboard Feeds
Step 3

Deploy AI Recommended Detection Use Cases

Once your platform is configured, you can start deploying hundreds of threat hunting and detection queries that align to your MITRE ATT&CK priorities. These detections are deployed as “warning” signals by default and used as baseline activity for AI-generated insights. These warning signals can also be used for hunting and advanced correlation.

Deploy AI Recommended Detection Use Cases
Step 4

Automatically Tune Detections with AI

After a couple of days, our AI-generated insights will automatically begin to tune those deployed detections based on common false positive strings and patterns.

Automatically Tune Detections with AI
Step 5

Escalate High Fidelity Alerts

Once the detections are tuned and reach a low volume threshold we will automatically recommend to escalate these detections to alerts that can be triaged.  In addition, our hunting insights analytics will also analyze each warning signal and escalate any events that are determined to be highly suspicious.

Escalate High Fidelity Alerts
Step 6

Build Your Own Detections & Hunting Queries with an AI Assistant

With Anvilogic, you can also build your own custom threat hunting or correlation rules unique to your environment using a low-code UI builder to escalate any events you feel are most critical to respond to.  Not the best at SPL, KQL, or SQL?  We have a generative AI assistant that turns your natural language questions into search logic.

Build Your Own Detections & Hunting Queries with an AI Assistant
Step 7

Measure Maturity & Improve Over Time

Keep track of all the progress you make in real-time to ensure you are continuously improving based on the detections you have deployed across your prioritized MITRE ATT&CK techniques. Align your security leadership, security engineers, and analysts with a single view of your maturity improvements.

Measure Maturity & Improve Over Time

Adopt a SIEM-less Architecture
At Your Own Pace

Fast-track your security team's ability to deploy and tune detections, hunt more efficiently, and bridge the gap between your traditional SIEM and modern security data lake(s) giving you the option to reduce costs and incrementally migrate over time.