Sherlocks AI
Debug incidents and reduce downtime with an AI SRE teammate
About Sherlocks AI
Sherlocks AI is an AI SRE that investigates production incidents across your logs, metrics, traces, and infrastructure and reports a root cause analysis in Slack or Microsoft Teams within minutes. When an alert fires, 16+ domain-specialized agents form a hypothesis, query your existing observability stack to validate it, and return the evidence behind each finding with short- and long-term remediations. Its Watson data agent runs inside your own VPC with read-only access.
Pros & Cons
Pros
- Genuinely usable free plan with 30 investigations per month and no credit card
- Investigates autonomously when an alert fires instead of waiting to be prompted
- Shows the command output and log evidence behind each conclusion, so findings can be verified
- Works on top of existing observability tools rather than replacing them
- Read-only, in-VPC data agent and SOC 2 Type 2 certification ease security review
- Setup typically takes under 30 minutes and does not require Kubernetes
Cons
- No self-serve paid tier between the 30-investigation Free plan and custom-priced Enterprise
- Young company founded in 2025, with a small team and limited track record
- Investigations pause on the Free plan once the monthly limit is reached
- Quality of root cause analysis depends on how well your telemetry and integrations are set up
- Performance claims such as 90% MTTR reduction come from the vendor and lack independent verification
Key Features
Alert-triggered investigations
Starts investigating automatically when an alert arrives from your monitoring tools, without anyone prompting it during an on-call page.
16+ specialized AI agents
Domain agents for areas like Kubernetes, databases, cloud, and CI/CD work in parallel to test hypotheses about an incident.
Root cause analysis with evidence
Reports the root cause in two to six minutes along with the command output, log lines, and metrics behind each finding, plus suggested fixes.
Slack and Microsoft Teams native
Investigations are delivered and discussed in chat, and engineers can ask follow-up questions like 'why is my app slow?' directly.
Infrastructure knowledge graph
Builds a map of your services, infrastructure, and dependencies automatically and uses it to scope each investigation.
Institutional memory
Draws on past incidents, runbooks, and Slack conversations so each investigation starts with your team's accumulated context.
Broad integration suite
Reads from Datadog, New Relic, Sentry, Coralogix, Prometheus, Loki, Grafana, Elasticsearch, AWS, GCP, Azure, PostgreSQL, MongoDB, Kafka, GitHub Actions, Jenkins, and more.
In-VPC Watson data agent
A read-only collector deployed via Terraform, Helm, or CloudFormation keeps raw telemetry inside your own cloud account.
Enterprise security options
SOC 2 Type 2 certified, with SSO/SAML, audit logs, RBAC, air-gapped deployment, and an in-VPC LLM option on Enterprise.
Pricing
- 30 investigations per month
- All 16+ AI agents included
- Slack & Microsoft Teams integration
- Connect your existing observability stack
- Self-serve onboarding
- Community support
- No credit card required
- Unlimited investigations
- All 16+ AI agents included
- Full integration suite
- Dedicated Field Engineer for setup
- Dedicated support engineer with SLA
- Custom dashboards and reporting
- SSO / SAML, audit logs, RBAC
- Air-gapped deployment and in-VPC LLM options
- SOC 2 Type 2 security review support
Best For
On-call incident triage
Small DevOps teams get a first-pass root cause in Slack within minutes of a page, cutting time spent digging through dashboards at 3 a.m.
Kubernetes troubleshooting
Diagnose OOMKills, CrashLoopBackOff pods, and resource exhaustion by correlating pod events, logs, and application queries.
Reducing alert noise
Correlated alerts are grouped into a single investigation, helping teams separate real incidents from noise.
Regulated infrastructure
Fintech and other regulated teams run investigations with air-gapped or in-VPC LLM deployments so telemetry never leaves their environment.
Scaling reliability without hiring SREs
Startups add 24/7 investigation coverage as an AI teammate before they can staff a dedicated SRE function.
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