Bud Ecosystem and DataLabs Corporation have formed a strategic partnership to deliver multi-vertical Generative AI agents to enterprises worldwide. The collaboration combines Bud's AI Foundry infrastructure and runtime technology with DataLabs' portfolio of domain-specific AI agents, aiming to overcome key barriers to enterprise AI adoption — integration, scalability, and hardware infrastructure.
Solving the key challenges in enterprise AI adoption
One of the biggest hurdles is hardware. Building new GPU-based infrastructure is prohibitively expensive and slowed by today's global GPU scarcity. Bud Runtime, the universal GenAI inference engine, lets enterprises deploy GenAI on virtually any hardware — GPU, CPU, HPU, NPU, or TPU. Even without a dedicated GPU setup, organizations can run GenAI workloads on existing standard CPUs, legacy systems, and commodity servers while achieving performance comparable to GPU-based systems.
"Enterprises have already made significant investments in their IT infrastructure. With Bud Runtime, DataLabs' agents can operate seamlessly on the hardware companies already own — removing the need for costly, specialized GPU deployments."
Linson Joseph — Chief Strategy Officer, Bud EcosystemAnother barrier is the lack of technical expertise; many initiatives stall at proof-of-concept. Bud AI Foundry provides an opinionated, end-to-end platform that abstracts away technical complexity, so even non-technical executives can deploy and scale GenAI models and agents. The joint solution scales seamlessly across on-premises, cloud, and edge, and Bud Runtime's heterogeneous cluster parallelism distributes workloads across available hardware — reducing infrastructure costs by orders of magnitude and lowering power consumption versus GPU-based alternatives, with support for Intel Xeon and AMD processors.
DataLabs' production-ready agent portfolio
DataLabs offers pre-built, enterprise-tested AI agents that deploy directly on Bud Runtime, spanning multiple industries:
- Financial Services: compliance monitoring, fraud detection, risk assessment, and document processing agents.
- Healthcare: clinical documentation, patient intake automation, and medical coding agents.
- Manufacturing: predictive maintenance, quality control, and inventory optimization agents.
- Customer Experience: support automation, sentiment analysis, and recommendation engines.
- Enterprise Operations: document processing, contract analysis, and knowledge management agents.
Each agent uses a modular architecture for easy customization, is pre-optimized for Bud Runtime, and requires no additional configuration to run on CPU-based infrastructure.
"This collaboration with Bud marks a significant leap in making vertical GenAI agents truly accessible to enterprises of all sizes. By eliminating the need for specialized hardware and enabling out-of-the-box deployment, we're removing the traditional barriers to adoption. Together, we're accelerating how quickly organizations can realize tangible value from AI — across industries and use cases."
Sony Lazarus — Chief Technology Officer, DataLabsUnified infrastructure for scale
Combining DataLabs' domain-specific agents with Bud's AI Foundry and Runtime gives enterprises a scalable, secure, and hardware-flexible solution — what once took months can now be achieved in hours. Key capabilities include:
- Seamless deployment: zero-modification deployment of DataLabs' agents on Bud Runtime via Bud AI Foundry.
- Automated optimization: automatic tuning for available resources.
- Unified management: a single interface to monitor, manage, and scale all deployed agents.
- Heterogeneous cluster parallelism: support for mixed CPU/GPU/NPU environments.
- Enterprise-grade security: built-in controls to protect sensitive data.
- Certified integration: Red Hat OpenShift certification for compatibility with existing enterprise IT.
- Multi-modal AI: text, image, audio, and video processing — even on standard CPU infrastructure.
"This partnership marks a critical step toward industrializing GenAI. By aligning infrastructure and intelligent agents, we're solving the last-mile problem for enterprises that want real impact from AI, not just experimentation."
Linson Joseph — Chief Strategy Officer, Bud EcosystemEarly deployments are already showing measurable results — financial institutions processing millions of daily transactions and healthcare providers running AI-powered documentation agents across multiple facilities, all on existing IT infrastructure.