AI-Native Operations Platform for Security, DevOps, and IT

COMPANY OVERVIEW

Kindo is an AI-native operations hub designed to unify and automate technical operations across security, DevOps, and IT. Acting as a central orchestration layer, Kindo consolidates processes that previously relied on fragmented tools, enabling organizations to coordinate end-to-end workflows from a single terminal. The platform integrates directly into existing infrastructure — Kubernetes clusters, cloud APIs, CI/CD pipelines, ITSM systems, SIEM tools, and job schedulers — creating a shared environment where security engineers and DevOps teams can execute complex multi-step workflows without switching between disconnected systems. Kindo includes a proprietary offensive security AI model called Deep Hat, purpose-built for DevSecOps use cases.

CORE FOCUS

Security and DevOps teams operate across an increasing number of specialized tools, creating context-switching overhead that slows response and fragments institutional knowledge. Kindo solves this by providing a single AI-driven terminal that connects to every system in the stack, enabling engineers to run investigations, build automated agents, execute remediation workflows, and manage infrastructure from one unified interface. The platform's agent builder enables both manual and automated workflows — triggered or scheduled — that can span multiple tools and require human input at defined steps. Administrative controls enforce DLP policies, audit all activity, and scope access by user group, giving security leaders governance over how AI automation is used across the organization.

PRODUCTS & TOOLS

Chat Interface — Conversational AI terminal for executing read and write actions across all connected tools.

• Familiar chat UI with file attachment, summarization, and secure tool authentication
• Toggle tools per conversation and execute both read and write actions from one interface
• AI clarifies ambiguous requests to prevent unintended automated actions

Agent Builder & Automation — No-code workflow engine for building multi-step agents that run on triggers or schedules.

• Build manual or fully automated agents with triggered or scheduled execution
• Multi-step workflows with model switching per step and human input support
• Shareable runbooks enable team-wide reuse of proven automation patterns

Deep Hat Security Model — Purpose-built AI model trained on DevSecOps data for offensive and defensive security operations.

• Trained specifically on DevSecOps data with strong benchmark performance
• Supports penetration test script generation and sandbox execution
• Tool-calling capability enables direct execution of security operations tasks

Administrative Controls — Enterprise governance layer for managing AI usage, access, and compliance across the organization.

• Model enablement controls, org-wide DLP policies, and custom regex filters
• Integration access control with fine-grained audit logs for every automated action
• User group policy scoping ensures appropriate access by role and team