Sherlocks.ai - AI-Powered SRE Incident Management
Sherlocks.ai helps SRE and DevOps teams manage incident response by automating parts of the investigation process. It is designed for teams looking to reduce MTTR and maintain institutional knowledge.
At a glance
- Category
- Operations
- Best for
- SRE teams, DevOps engineers, Engineering leadership
- Pricing
- A free start option is available. Pricing was not clearly available from the provided evidence. Buyers should confirm current pricing on the vendor website.
- Key use cases
- Incident Response, Dev and DevOps Alignment, Async and Follow-the-Sun Support, Daily Reliability Reviews, Onboarding and Knowledge Retention
- Integrations
- AWS, GCP, Azure, Kubernetes, Datadog
- Official website
- www.sherlocks.ai/
Sherlocks.ai is an AI-driven platform designed to act as an autonomous reliability teammate. It integrates with observability and cloud stacks to monitor infrastructure and services, detect issues, and perform automated root cause analysis (RCA).
The tool is built for SRE teams, DevOps engineers, and engineering leadership. It helps by correlating signals from logs, metrics, and code changes to identify potential causes of failure. Interaction occurs primarily within Slack, where teams can trigger investigations using natural language commands.
Buyers should confirm their specific security and compliance needs, as the platform offers several deployment models, including SaaS, Hybrid, and self-hosted In-VPC options to manage how telemetry data is handled. It is designed to support human SREs by handling repetitive diagnostic tasks.
Key Features
Correlates infrastructure signals with code changes and deployments to help identify the primary cause of an incident.
Analyzes alerts to help reduce noise and surface actionable causes.
Supports investigation triggers and analysis delivery via @sherlocks commands directly in Slack channels.
Maps system dependencies, communication patterns, and historical incident data to provide context.
Offers SaaS, Hybrid, and self-hosted (In-VPC) options for different security and data residency requirements.
Monitors systems to help identify potential issues and patterns before they escalate.
Use Cases
Correlating infrastructure signals with recent code changes to help identify root causes.
Providing shared visibility into infrastructure and software context to help reduce friction between developers and operations teams.
Supporting handoffs between global teams by providing AI-generated investigation context.
Using automated RCAs as input for daily standups to help prioritize technical debt.
Building an institutional memory of past incidents to help new engineers understand the system.
Best For
Integrations
Pricing
A free start option is available. Pricing was not clearly available from the provided evidence. Buyers should confirm current pricing on the vendor website.
FAQ
It connects via read-only APIs to cloud providers (AWS, GCP, Azure), observability tools like Datadog and Prometheus, and CI/CD pipelines such as GitHub and Jenkins.
The platform is designed with read-only permissions and offers an In-VPC deployment model to keep telemetry data within the customer's environment.
No, it is designed to handle repetitive investigation and diagnostic tasks so engineers can focus on architecture and resilience.
The platform is Slack-native, allowing users to trigger investigations and receive analysis summaries through Slack commands.
Source category: Operations
Source subcategory: Workflow Automation
