Kubiya.ai, introduces the first AI-assistant for engineering platforms and knowledge management, offering a ChatGPT-like experience for users. The solution simplifies access to DevOps functions and answers questions from knowledge systems such as Notion, Confluence, and technical documentation. Users can interact using everyday language, turning complex tasks into easy conversations. The AI-powered editor helps DevOps and platform engineers create and manage automations, workflows, and knowledge assets quickly and cost effectively compared to traditional tools.
Kubiya is an AI tool designed to make DevOps professionals’ lives 10 times easier, and draws many parallels to Github Co-Pilot and the productivity boost it unlocked for millions of developers. Kubiya does this for DevOps by understanding users’ specific needs and providing personalized, secure and efficient recommendations. The tool focuses on improving operations while keeping things safe and well-organized.
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While traditional engineering solutions typically require a great effort to fully integrate into organizational processes, Kubiya existing customers have enjoyed a near immediate impact, with thousands of pre-built use-cases that can be actioned through natural language and time-to-value reduced to minutes.
Kubiya’s self-learning ability, coined behavioral AI, adapts to new scenarios based on user-specific data and feedback. As a headless internal developer platform (IDP) that lives within Slack, Teams, and CLI, users can provision resources, trigger CI/CD Jobs, Kubernetes deployments, cloud cost usage reports, Git, Jira, Terraform and other DevOps functions without leaving the comfort of their favorite chat apps or mobile device.
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“For businesses looking to keep a technology edge in today’s fast-paced environment there is no easy ‘off-ramp’ other than to continually invest in additional headcount. Kubiya offers a ‘cheat-code’ to operational efficiency, where we don’t just teach one person in the organization how to ‘fish’, we give the entire ‘village’ a fishing net,” says Amit Eyal Govrin, CEO of Kubiya.ai.
DevZero CEO Debosmit Ray provides his perspective, “Permissions and running various DevOps workflows consumed a lot of our engineering cycles, even more so for our VP of Engineering. Implementing Kubiya reduced this time significantly, and cut it down by half. Giving each team member the autonomy to run their workflows helped reduce impact from context-switching across the various teams. I love how subtly generative AI capabilities have been incorporated into Kubiya – it’s like interacting with an AI DevOps engineer.”
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