Key features
- Investigate
- Fix
- Prevent
- Optimize
- Understand
Tag @Codewolf in Slack when issues strike. AI agents analyze deployments, correlate logs across services, trace requests, and identify root causes. From alert to diagnosis in minutes.Slack mentions:
- @Codewolf payment API is throwing 500 errors, customers can’t checkout
- @Codewolf investigate this PagerDuty alert - database latency spiking
- @Codewolf trace this request ID through our services
- Alert: High error rate detected in checkout service
- Webhook: Customer support ticket for checkout failures
- Incident channel created: Site down - payment service unreachable
How Codewolf agents work
Codewolf connects to your systems, continuously builds operational context, and deploys specialized AI agents to handle engineering tasks autonomously.Context generation
Agents continuously ingest and update context from your integrations and historical events. Context evolves as your systems change, ensuring decisions are always based on current state.
Triggers and events
Codewolf processes events from multiple sources including Slack mentions, alerts, cron jobs, GitHub events, and webhooks. Triggers are normalized, prioritized, and routed appropriately.
Agent orchestration
A central coordinator dynamically spins up worker agents based on task type and complexity. Specialized agents run in parallel to investigate issues, generate fixes, or perform analysis.
Architecture
Security
Every customer gets their own isolated Private Agent Sandbox with: Isolated infrastructure:- Dedicated agent compute resources per customer
- Isolated agent file storage - your data never touches other customers
- Isolated agent database - complete data separation
- AES-256 encryption in transit and at rest
- SOC 2 Type II certified
- SSO & SAML support
- Role-based access control
Get started
Quickstart
Set up Codewolf in minutes