Kindo provides an AI-native control plane for technical operations, allowing Security, Dev, and IT engineers to centrally manage and deploy automation agents. It connects directly into existing infrastructure and tools to execute complex workflows, turning engineering intent into automated outcomes. This platform streamlines processes like SOC execution, incident response, and vulnerability management, reducing manual overhead and accelerating resolution times.
Funding
$27.6M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
DevSecOps teams often struggle with manual, repetitive tasks in incident response and vulnerability management, leading to inefficiencies and potential security gaps. Writing configurations and managing workflows across various systems of record consumes valuable time and resources.
Solution
Kindo offers a no-code platform that leverages AI agents to automate DevSecOps workflows and runbooks, streamlining incident response and vulnerability assessments. By integrating with existing systems like ServiceNow, GitHub, and Jira, Kindo enables teams to automate tasks typically performed by DevOps and SecOps analysts. The platform uses SIEM data, sensor logs, and infrastructure as code (IaC) to orchestrate infrastructure responses to events and planned projects. Kindo's AI Agents are accessible via an OpenAI compliant API and within Dev Copilots, allowing users to build and deploy automation on their terms.
Target Audience
Kindo primarily targets DevSecOps and SecOps teams looking to automate manual tasks, improve incident response, and enhance vulnerability management.
Features
- No-code AI Agents that automate DevSecOps tasks using natural language.
- Integration with existing systems of record, including ServiceNow, GitHub, and Jira.
- Ability to leverage SIEM data, sensor logs, and infrastructure as code (IaC) for automation.
- OpenAI compliant API for accessing and integrating AI Agents.
- Data Loss Prevention (DLP) filters for Agent model data.
- Access Control Lists (ACL) for model access.
- Single Sign-On (SSO) and logging capabilities for agents.