IBM announced self-hosted deployment for IBM Bob, allowing organizations to bring AI software development to on-premises, private-cloud, sovereign-cloud, and air-gapped environments where they have control. Bob is IBM's agentic software development platform that helps teams move beyond code generation to apply AI to the work of software delivery and modernization.
IBM Bob’s self-hosted deployment option brings AI to customer-managed infrastructure and is specifically designed for organizations that require greater control over data residency, security policies, AI governance, and software development workflows, according to the company.
Unlike many AI coding and software development tools that require organizations to move data to external services, the self-hosted version of IBM Bob allows enterprises to deploy AI software development and modernization capabilities in environments where their code, application context, and data already reside.
"The future of enterprise AI will depend on security, governance and sovereignty,” said Neel Sundaresan, GM of AI and automation, IBM. “Organizations need AI that operates inside environments they have control over, especially when working with sensitive code and regulated data. Bob’s self-hosted deployment provides a way for enterprises to bring agentic AI directly to those environments so they can benefit from the technology while maintaining security, compliance, and operational control.”
Most enterprises operate software environments that contain sensitive data such as intellectual property, proprietary source code, and regulated customer information.
Now, IBM Bob’s deployment flexibility can help enterprises address those requirements by allowing them to bring AI to the data instead of moving their data for the AI. Enterprises can run supported models on premises, including in air-gapped environments, using supported models they’ve licensed or connect Bob to supported external model services through hybrid configurations.
IBM Bob’s deployment flexibility allows organizations to use AI for software development and modernization across infrastructure environments and models, helping them achieve true AI adoption.
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