Kindo triples enterprise adoption & unveils Deep Hat AI model

Kindo.ai has reported significant growth in enterprise adoption and introduced new product capabilities for its AI-native automation platform.

The company confirmed a threefold increase in active enterprise deployments during the second quarter, citing rapid expansion among AI-native security teams and organisations in quant finance, healthcare, and cloud infrastructure. Monthly volumes are said to now reach millions of policy-backed, secure agent actions running across customer environments.

Customer momentum

Kindo's platform is structured around automating processes for security operations (SecOps), development operations (DevOps), and IT operations (ITOps), focusing on reducing the number of tools teams require to maintain their systems. According to company benchmarks, some customers have reduced their legacy toolsets by as much as 80%, consolidating their workflows onto a unified system capable of GPU-scale performance and providing full-stack observability.

The company noted it has seen zero customer churn over the past year and reported a 400% year-over-year increase in Committed Annual Recurring Revenue (CARR). Net Revenue Retention (NRR) was cited at 300%, signalling that existing clients are both expanding their platform usage and remaining engaged over time.

Product advances

Alongside its financial results, Kindo has launched several upgrades to its platform. This includes the introduction of new chat interfaces and AI-managed tool calling, enabling real-time, natural language collaboration with AI for critical security and DevOps workflows.

The system now supports native and automatic AI-generated integrations, designed to automate and keep up-to-date with continuous integration/continuous deployment (CI/CD) suites as well as standard security and incident response tools. Its agents now offer dynamic parameter support, executing actions across complex systems through simple, no-code interfaces.

The company also introduced Deep Hat V3, a 32-billion-parameter open-source model that enhances penetration testing, security operations, DevOps, and troubleshooting. Customers can deploy Deep Hat privately on their own infrastructure, keeping sensitive security and operational data under their direct control.

Peter Clay, CISO, Aireon, said: "Kindo's agentic AI helped us detect advanced threats, accelerate analyst training, and automate where traditional tools fell short. We're seeing a $47 return for every $1 spent. It's a rare combination of speed, precision and measurable impact."

Kindo's open-source AI model, formerly known as WhiteRabbitNeo, has been renamed Deep Hat. This rebrand is intended to reflect the model's community-driven nature and its role in adversarial AI, red teaming exercises, and infrastructure automation. The company plans to demonstrate Deep Hat at industry gatherings in August.

Leadership and platform positioning

Kindo also recently expanded its leadership team. Mathew Varghese has joined as Chief Revenue Officer to support further commercial growth following the recent financial and operational momentum.

The company's approach integrates a proprietary large language model (LLM) and automation tools, aimed at allowing technical teams to offload repetitive tasks, automate complex workflows, and enforce organisational policies rapidly and securely.

Ron Williams, CEO and Founder, Kindo.ai, said: "If your AI automation depends on a third-party API, it's not yours. Kindo and Deep Hat change that. Only Kindo delivers fully self-managed AI automation with a complete toolchain and Deep Hat, our DevSecOps-specific LLM, that runs securely on premises."

Kindo reports its technology wires together code repositories, log streams, and cloud APIs into a unified command-line interface, which the company states forms an autonomous control loop capable of diagnosing and remediating issues directly.

Bryan Vann, CTO and Co-Founder, Kindo.ai, said: "By wiring every repo, log stream and cloud API into a single command‐line conversation, we've built an autonomous control loop that diagnoses issues, decides on fixes and deploys them in real time. It's the first AI agent engineered expressly for DevOps and SecOps that turns one prompt into full‐stack action."

Kindo operates within the broader context of AI-driven automation in technical operations, as organisations increase their focus on operational efficiency, security assurance, and infrastructure scalability in cloud-based and hybrid environments.