Top 10: Hybrid Cloud Solutions
By Maya Derrick
January 28, 2026

Hybrid cloud technology merges the limitless scalability of public clouds with the governance of on-premises infrastructure, establishing a robust foundation for modern IT.

Leading technology firms are revolutionizing enterprise systems, leveraging AI to enhance automation, improve network security, and optimize data management. These hybrid cloud solutions are fostering greater agility and data sovereignty while driving global innovation through interconnected and intelligent ecosystems.

Here are the top hybrid cloud solutions showcasing concrete applications of AI and their benefits:

10. Cisco+ Hybrid Cloud
Cisco’s hybrid portfolio integrates networking and security for comprehensive observability across multi-cloud environments. By enabling AI-centric workloads and automated provisioning through Intersight, Cisco ensures low-latency, secure data communication.

9. HPE GreenLake
Utilizing AI-driven tools for automated security, HPE GreenLake offers a pay-per-use model that drastically reduces costs. Their partnership with Nvidia enhances on-site AI capabilities, protecting critical workloads and optimizing resource use.

8. Dell Apex Hybrid Cloud
Dell APEX delivers cloud-like agility and elastic resource scaling while ensuring reliability and operational simplicity. This adaptability allows businesses to avoid expensive re-platforming while maintaining strong storage and compute solutions.

7. Oracle Cloud Infrastructure
OCI's Cloud@Customer fulfills stringent sovereignty needs while facilitating seamless, multicloud strategies. Such flexibility enables enterprises to harness AI capabilities without latency issues.

6. VMware Cloud Foundation 9.0
VMware provides unified integration of compute, storage, and networking, automating lifecycle operations to achieve private AI capabilities and ensure mission-critical operations.

5. IBM Cloud
An AI-focused design with Red Hat OpenShift allows IBM Cloud to support regulated sectors in modernizing legacy systems and maintaining data security.

4. Google Cloud Platform
With Google Anthos, resource management across diverse environments is simplified. GCP shines in AI analytics and machine learning, empowering businesses to drive data-driven decision-making.

3. Nutanix Cloud Platform
Nutanix streamlines application management across locations, enabling cost-efficient, AI-empowered workload deployment through unified virtualization.

2. AWS
AWS Outposts reduces latency by offering AWS services on-premises, with an extensive array of tools including advanced AI chips.

1. Microsoft Azure
Integrating seamlessly with existing Microsoft services, Azure’s adaptive framework supports AI capabilities across diverse environments, leading the global market in resilient hybrid computing.

Calsoft is leading the charge in integrating generative AI into software development processes, effectively tackling challenges such as tight deadlines, complexity, and quality assurance in traditional SDLC methods. During a March 2025 industry session, key technology leaders explored concrete automation strategies targeting coding, debugging, documentation, and testing workflows.

Generative AI automation significantly enhances development efficiency by allowing teams to shift their focus from monotonous, repetitive tasks toward more complex problem-solving. This transition has led to notable improvements in release cycles, reduced errors, and enhanced code quality, as evidenced by various case studies shared during the session.

The webinar discussed how generative AI tools can alleviate developer burnout, ensuring high code quality while expediting development timelines. Featured speakers included Anshul Bhide from Calsoft, who leveraged expertise from AI developer startup Replit, as well as notable leaders like Amit Gogate, Ryan Villanueva, and Sudarshan Kamath, who contributed insights on AI implementation and innovation.

The session covered vital areas such as effective AI integration within SDLC workflows and quantifying impacts through metrics like error reduction and cycle time. It also addressed challenges of implementation, including training teams and tackling security issues. Additionally, the conversation highlighted the automation of routine tasks and optimization of CI/CD pipelines, improving defect detection via AI-powered testing solutions.

Targeting decision-makers such as CTOs, software engineers, and QA leads, the webinar provided practical frameworks for evaluating generative AI in development workflows. A recording of the session is available via Calsoft's website, offering valuable insights for enterprise software development teams looking to adopt AI technologies.

Calsoft specializes in AI/ML solutions, digital transformation, and enterprise technology implementations, emphasizing engineering excellence across various technology sectors.

Loss prevention has emerged as a significant application of artificial intelligence (AI) in retail, emphasizing its potential at the NRF 2026 retail conference. Central to this is computer vision technology, which analyzes video feeds from surveillance cameras to identify patterns and derive insights crucial for loss prevention.

AiFi CEO João Diogo Falcão noted, “This is an information problem.” Retailers often lack awareness of why products are lost, and thus, harnessing data from cameras—equipped as high-level sensors—becomes essential. By implementing computer vision effectively, retailers can monitor people, products, and store spaces in real time, helping not only to mitigate losses but also to streamline operations.

AI-driven video analytics can monitor entire store environments, sending alerts to staff about potential thefts as they happen. This technology can pinpoint high-risk areas, such as return counters. CDW's Andrew Cadwell highlighted that if a customer exhibits suspicious behavior while returning items, managers can intervene promptly.

Beyond loss prevention, computer vision also yields valuable insights on shopper behavior, allowing retailers to refine product placement and optimize labor scheduling. Falcão pointed out, “How shoppers behave, what they’re looking at, what they’re buying,” can increasingly inform business strategies.

Checkout processes also benefit significantly from computer vision. It enhances efficiency across diverse checkout methods, including self-checkout, a popular means of cost reduction. However, challenges in self-checkout can lead to increased shrinkage. Joshua Mora from RocketBoots emphasized the need to decrease losses without compromising the customer experience by leveraging real-time data to empower associates.

For effective implementation, retailers must ensure robust infrastructure, including high-definition cameras and a reliable network to support data flow. On-site servers can alleviate data challenges and help address privacy concerns.

Ultimately, computer vision not only curtails theft but also facilitates operational improvements and enhances customer service, effectively transforming video analytics into actionable insights for retailers.

IBM has introduced the Enterprise Advantage service, a groundbreaking AI-powered consulting platform designed to empower businesses to scale agentic AI efficiently. Announced on January 19, 2026, this service integrates advanced AI tools and IBM's technical expertise to enable organizations to construct, govern, and operate customized internal AI platforms swiftly.

With IBM Enterprise Advantage, companies can optimize workflows and integrate AI with their existing systems without modifying their cloud infrastructures. This service is compatible with major cloud providers like Amazon Web Services, Google Cloud, and Microsoft Azure, allowing businesses to leverage prior investments seamlessly.

The platform has already demonstrated its effectiveness in real-world applications. For instance, Pearson, a lifelong learning organization, is developing a tailored AI platform that integrates human expertise with AI assistants to enhance everyday decision-making and management tasks. Additionally, a manufacturing firm has successfully launched its generative AI strategy through Enterprise Advantage. This involved identifying valuable use cases, prototype testing, and securing alignment among stakeholders, all within a governed environment.

IBM Consulting's own internal AI delivery platform, IBM Consulting Advantage, has shown to increase consultant productivity by up to 50%, having supported over 150 client projects. This robust track record equips clients with a proven framework to harness the potential of AI effectively.

"Achieving real value from AI at scale poses significant challenges," stated Mohamad Ali, Senior Vice President of IBM Consulting. The Enterprise Advantage service combines human insight with digital AI workers and readily available assets, allowing organizations to adopt AI confidently for meaningful impact. Enterprise Advantage is now available, offering businesses unparalleled support in navigating the complex AI landscape.