Agentic AI provides an AI‑driven Site Reliability Engineering platform that automates incident investigation, root‑cause analysis, and remediation to cut mean time to resolution by up to 91%. Its pre‑built and custom AI agents integrate with existing monitoring stacks, offering predictive insights, blast‑radius visualizations, and automated post‑incident reporting for SRE and DevOps teams. Customers such as Google, VMware, and Bose use the system to reduce incident frequency and operational costs.
Funding
Funding not disclosed
Founders
Product
Problem
Site reliability teams spend extensive manual effort investigating incidents, diagnosing root causes, and executing remediation, leading to long mean time to resolution (MTTR) and increased operational risk. Traditional monitoring tools provide alerts but lack automated analysis and coordinated response, causing delays and higher incident frequency.
Solution
Agentic AI’s HealR platform delivers an autonomous SRE assistant that continuously monitors metrics, logs, and traces, then initiates AI‑driven investigations as soon as an anomaly is detected. A multi‑agent workflow performs root‑cause analysis, visualizes blast‑radius impact, and generates evidence‑backed remediation recommendations. Safe auto‑remediation actions are executed with optional human‑in‑the‑loop approval and automatic rollback if needed. Predictive intelligence forecasts potential failures, allowing teams to address issues before they surface. All insights are presented through natural‑language dashboards and conversational Agent Chat, enabling engineers to query data without writing queries. The platform integrates with existing monitoring stacks and CI/CD pipelines, turning reactive alerts into proactive, self‑healing operations.
Target Audience
Primary customers are SRE and DevOps teams in mid‑size to large enterprises that require continuous reliability and rapid incident resolution. The platform also serves platform engineering groups seeking to embed AI‑driven automation into their monitoring and CI/CD workflows.
Features
- Autonomous incident investigation using AI agents that correlate metrics, logs, and traces without human intervention
- Blast‑radius visualization that maps cascading impact across the entire infrastructure in real time
- Safe auto‑remediation with rollback and configurable human‑in‑the‑loop approval gates
- Predictive intelligence module that forecasts anomalies and suggests preventive actions
- Conversational Agent Chat for natural‑language querying of logs, metrics, and dashboards
- Topology GPT for AI‑generated service dependency maps and impact analysis
- Integrated runbook automation that generates, updates, and executes playbooks based on live incidents