7AI is tailored to your environment, workflow, and needs for security that works like you do: fast, adaptive, and focused on outcomes that matter.
Highlighted examples of how 7AI agents are delivering security outcomes today. To learn more about the breadth of 7AI use cases, get a demo.
7AI agents are able to ingest, parse, analyze, and understand whether threat intelligence data is relevant to your environment.
Triggered by alerts from EDR solutions, 7AI agents enrich data, perform investigations, form conclusions, and output results to other systems.
By integrating with cloud security solutions, 7AI agents understand cloud security alerts and perform end-to-end investigations at AI speed.
Alerts from identity solutions spawn AI agents to run agentic investigations with full enterprise context, offloading non-human work.
The 7AI Agentic Security Platform consists of AI agents that perform specific security tasks. Agents are experts at their task, able to understand context, and are bound by architecture to eliminate hallucinations.
7AI agents each have a specific scope, and are able to make decisions, adapt, and improve.
Agents are experts in the specific tasks they are given to perform.
7AI agents have access to tools to analyze, conclude, and complete their mission.
At 7AI, we’re building the future of agentic security—one customer outcome at a time. The agents listed below are a representative sample of what’s actively deployed in production environments today. Each agent is purpose-built to autonomously resolve specific classes of alerts or tasks, from endpoint threats to identity hygiene. But this is just the beginning. We continuously develop and expand our library of agents, connectors, and workflows in close collaboration with our customers. If you don’t see a specific use case here, chances are we’re already working on it—or can build it with you.
Explore our list of current and planned 7AI agents. Contact your 7AI success team or email product@sevenai.com if you don’t see an agent you need.
Surfaces AWS account-level activity anomalies by profiling user and service actions against baseline behaviors.
Assesses configuration and access logs of AWS Elastic Load Balancers to detect misrouting, DDoS patterns, or privilege misuse.
Aggregates configuration and metadata from AWS resources to assess security posture and ownership.
Surfaces recent activity in Azure environments, identifying anomalous actions across users, service principals, and roles.
Fetches and compiles data from multiple systems in response to investigative prompts, enabling deeper context generation.
Tracks activity within S3 buckets to detect unusual access, modifications, or bulk downloads.
Enriches AWS S3 bucket info with metadata including permissions, access logs, and exposure risk for security review.
Performs semantic analysis on email body and subject for phishing indicators, urgency cues, or social engineering.
Evaluates email content against DLP policies to detect potential exfiltration or inappropriate data handling.
Analyzes patterns of email recipients to detect potential misuse of distribution groups or anomalous communication.
Examines sender metadata and authentication to detect spoofing, typosquatting, or domain abuse.
Fetches the full raw email from the mail server for analysis of headers, links, attachments, and content.
Surfaces past alerts on a device and relates them to current activity to detect escalating risk.
Provides contextual data on a device including OS, owner, last activity, and vulnerability exposure.
Resolves multiple device identifiers to a canonical entity to ensure accurate correlation across alert sources.
Investigates the device’s recent activity, active processes, and connections to determine compromise likelihood.
Performs static and dynamic analysis of files, looking for known signatures, behaviors, and propagation patterns.
Traces the origin and modification path of a file across systems to determine source, spread, and potential data exfiltration.
Automates quarantine or deletion of files confirmed to be malicious, using native EDR and endpoint controls.
Determines if files are malicious, suspicious, benign, or unknown.
Correlates IP addresses with known devices, sessions, and user activity to track movement and exposure.
Inspects and interprets command-line arguments used during process execution to identify known attack patterns or scripting misuse.
Analyzes process behavior, ancestry, and execution context to detect suspicious or unauthorized activity on endpoints.
Interrogates Windows registry changes associated with alerts to detect persistence mechanisms or configuration tampering.
Retrieves and analyzes lineage data from SentinelOne to reconstruct the origin and propagation path of detected threats.
Queries recent activity within Splunk Mission Control to identify prior related incidents or alert patterns for context.
Compiles a timeline of events and entities associated with an alert, connecting dots across systems to produce a coherent incident narrative.
Expands and inspects URLs associated with alerts, checking for phishing indicators, downloads, redirects, and reputation.
Inspects login behavior across endpoints and identity providers to identify brute force attempts or session hijacks.
Fetches data from Okta about user identity, group memberships, device associations, and MFA status.
Identifies accounts that granted elevated privileges and assesses whether the action aligns with normal administrative behavior.
Monitors behavior of service and administrative accounts for unusual access patterns or risky command execution.
Analyzes user activity trails to identify deviations from typical behavior and detect signs of credential misuse or insider threats.
Surfaces past alerts tied to the same user and correlates with the current incident to detect patterns of compromise.
Investigates a user's behavioral fingerprint to highlight anomalies in login, device usage, and data access patterns.
Enriches user entities with organizational role, authentication context, and recent access behavior for deeper investigation.
Provides a consolidated identity view of a user across identity providers and activity sources to support correlation.
Compiles login events for a user across systems to flag geographic anomalies, impossible travel, or access outside work hours.
Pulls contextual data from Windows environments about a given user, including group memberships and recent sessions.
Calculates network and geographic proximity between IP addresses to evaluate possible lateral movement or coordinated attacker behavior.
Investigates and enriches domain-related observables, identifying reputation, WHOIS data, hosting details, and relationships to known threat infrastructure.
Performs enrichment and threat assessment for external IPs, correlating with threat intel feeds and identifying risky infrastructure.
Correlates internal IPs with associated assets and users, tracking movement across the environment for threat triage and attribution.
Aggregates geolocation, ASN, blacklist, and threat intel data for any observed IP address to aid in contextual alert triage.
Evaluates network traffic metadata to uncover anomalies in volume, direction, and communication patterns tied to alerts.
The 7AI Agentic Security Platform connects to IT and Security tools, enabling agents to enrich, investigate, and form conclusions. The following is a highlighted list of API-based connectors available today.
Find out how 7AI can transform your security operations with swarming AI agents.