Cross-tool knowledge graph
DrDroid connects to cloud, code, CI/CD, and observability tools using OAuth and builds a stack-wide knowledge graph from the connected systems.
DrDroid is an AI SRE agent that connects to cloud, code, and telemetry sources to build a stack-wide knowledge graph for incident investigation and remediation support. It is aimed at teams that want faster root-cause analysis, shared investigations, and an enterprise path for self-hosted deployments.
DrDroid is an AI SRE agent for incident investigation and operational reliability. It connects to cloud, code, and telemetry sources, then scans the stack to build a knowledge graph that links services, dashboards, pods, repositories, configs, and supporting documentation.
The product is designed to help teams respond faster to alerts, find root causes with less manual tab-hopping, and apply runbooks or remediation steps with more context. Source pages also describe a self-learning model that reuses prior investigation patterns and improves as alerts, deploys, incidents, and conversations are added to the graph.
DrDroid connects to cloud, code, CI/CD, and observability tools using OAuth and builds a stack-wide knowledge graph from the connected systems.
When an alert or incident appears, the graph helps trace related services, dashboards, pods, repos, and cloud resources to narrow down blast radius and likely causes.
The product continuously ingests telemetry, runbooks, docs, issues, deploys, and conversations so the graph stays current as the system changes.
DrDroid uses remembered patterns from prior investigations to avoid repeating failed steps and to surface responses that worked before.
The platform can suggest next steps, support root-cause diagnosis, and trigger guarded automated runbooks with full context from the graph.
The pricing page says Teams includes shared investigations, audit trail, unlimited integrations, and smart model switching, while Enterprise adds self-hosting, BYO LLM, and identity/security controls.
Use DrDroid when an alert fires and the team needs to connect the symptom to services, repositories, dashboards, pods, and cloud resources without manually jumping between tools.
Use it to shorten root-cause analysis by tracing related deploys, config changes, incidents, and telemetry in one graph-backed context rather than starting from a blank slate.
Use the self-learning memory to capture recurring incident patterns so the next similar alert can skip known dead ends and reuse the steps that worked before.
Use the product to centralize runbooks, wikis, ADRs, READMEs, and on-call docs alongside live signals so responders can work from documented process plus current telemetry.
Use the enterprise plan when procurement or security requirements call for VPC isolation, SSO/SCIM, audit logs, IP allowlisting, custom residency, or a Bring Your Own LLM setup.
DrDroid connects to cloud platforms, code repositories, and telemetry sources, then builds a knowledge graph from the connected stack. The product says it can use that graph to support faster incident response, quicker root-cause analysis, and automated remediation.
The pricing page says the Teams plan includes unlimited users and shared investigations, so it is designed for team use rather than seat-based licensing. Enterprise adds controls such as self-hosting in a VPC, SSO/SCIM, IP allowlisting, and custom data residency.
The pricing page says the Teams plan starts at $99 per month and includes 99 investigation credits, with top-ups at $1 per credit. Enterprise uses custom volume credit pricing and license-based fees.
The home page and pricing page both point to a setup centered on connecting existing tools and telemetry rather than installing agents. The home page says OAuth into cloud, code, CI/CD, and observability, with no agents and no code changes, and the pricing page says the product is available through the Teams plan and Enterprise.
Source pages show DrDroid working across alert investigation, diagnosis, and runbook-driven response. The product can also ingest runbooks, wikis, ADRs, READMEs, and on-call docs, but the source material does not define every output format in detail.
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