Sunday, July 19

Zimbabwe Government Buys Masks For USD28 Each Company Linked To Mnangagwas Son

Zimbabwe government through its Health Ministry is reportedly buying face masks for USD $28 each from President Mnangagwa’s son linked company called Drax International LLC .
Zimbabwe government through its Health Ministry is reportedly buying face masks for USD $28 each from President Mnangagwa’s son linked company called Drax International LLC. This comes as the Zimbabwean people are struggling to raise USD 50 cents to buy the cheapest face mask available on the market.

In a letter written by the permanent secretary of the Ministry of Finance and Economic Development Golden Guvamatanga to the Ministry of Health and Childcare demanding the release of a consignment of Drax International, the health kits are being charged at very expensive prices to the ministry.
In the letter, Government has purchased 3 740 N95 face masks for USD $28 each, 5 040 Coverall protection Catill type 6b at USD $90 each and 15 000 SARS-Cov-2 Test Kit at USD $34 each totalling USD $987 720.In the local market the N95 face masks cost USD 5.32 each while reusable masks which have become popular cost USD $3 each.

“I write with reference to my letter dated 28 April 2020, advising your Ministry under legal guidance to engage all suppliers for the supply and delivery of medicines and surgical sundries with a view to invoking force majeure provisions, in order to terminate the said contracts o as t mitigate against escalation in the amount of debt to the said suppliers which Treasury is clearly now not going to be able to meet.
“However, Treasury is made to understand that there were times that had already been shipped and currently held at the Robert Mugabe Airport pending clearance. In this regard and given the urgent need for Test Kits, Treasury is hereby exceptionally authorising the release of the consignment to ensure the items availability in the ongoing efforts to fight the COVID-19 pandemic and Treasury will provide funding for the consignment guided by the contract,” Guvamatanga said.

He said Treasury’s position suspending procurement of additional items still stands and the Health Ministry should remain guided by the directive as communicated.

According to local publications Bulawayo24 and Zim Live, Drax International LCC is believed to be registered in Switzerland by Collins Mnangagwa and represented in Zimbabwe by Delish Nguwaya. The company has been supplying drugs to the NatPharm, the government drugs firm, in a separate USD $22.5 million arrangement since September last year. Nguwaya who is well known for a colourful criminal past including multiple arrests for armed robbery, cocaine possession and extortion is a business partner of Collins.

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Best AI Cloud Computing Platforms for Enterprise Businesses

Enterprise AI spending is exploding in 2026.

Companies are no longer experimenting with artificial intelligence. They’re deploying it directly into customer service, cybersecurity, analytics, fraud detection, logistics, healthcare systems, and financial operations.

But there’s a serious problem many executives discover quickly.

AI infrastructure is expensive.

Choosing the wrong cloud platform can lock businesses into years of overspending, performance issues, and security headaches.

That’s why more organizations are searching for the best AI cloud computing platforms for enterprise businesses before making large technology investments.

Why Enterprise AI Requires Specialized Cloud Infrastructure

AI workloads are very different from traditional business applications.

They demand:

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  • Advanced storage systems
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Traditional servers often struggle under these demands.

Cloud providers solve this problem by offering flexible infrastructure that scales as AI usage grows.

What Enterprise Businesses Should Prioritize

A flashy demo means nothing if the platform fails under real business pressure.

Experienced IT leaders focus on several key areas.

Scalability

AI projects usually grow quickly.

A platform that works for one department today may eventually support thousands of users across multiple regions.

Scalability matters heavily.

Security and Compliance

Enterprise AI systems often process sensitive data.

Especially in industries like:

  • Healthcare
  • Banking
  • Insurance
  • Government
  • Legal services

Strong compliance controls are critical.

AI Development Ecosystem

The best AI cloud computing platforms support:

  • Machine learning frameworks
  • AI model training
  • Generative AI systems
  • Data analytics pipelines
  • Automation tools

The broader the ecosystem, the easier future expansion becomes.

Amazon Web Services (AWS)

AWS remains a dominant force in enterprise cloud computing.

Its AI ecosystem is massive.

Popular AWS AI services include:

  • SageMaker
  • Bedrock
  • Rekognition
  • Comprehend
  • Lex
  • AI-powered analytics tools

Large enterprises often choose AWS because of its flexibility and global infrastructure.

Strengths of AWS

  • Extremely scalable infrastructure
  • Massive service ecosystem
  • Strong developer community
  • Advanced AI model deployment tools
  • Global data center presence

Potential Drawbacks

AWS pricing can become complicated.

Poor optimization often leads to surprisingly high cloud bills.

Microsoft Azure

Azure has become incredibly strong in enterprise AI.

Especially for organizations already using Microsoft products.

Azure integrates naturally with:

  • Microsoft 365
  • Active Directory
  • Power BI
  • Dynamics 365
  • GitHub

That integration creates operational advantages for many enterprises.

Azure OpenAI Services

Microsoft’s partnership with OpenAI changed the enterprise AI market significantly.

Businesses can integrate:

  • AI copilots
  • Large language models
  • Automation workflows
  • Generative AI applications

Directly into enterprise systems.

Azure Strengths

  • Excellent hybrid cloud capabilities
  • Strong enterprise integrations
  • Growing AI ecosystem
  • Robust compliance features

Azure has become especially popular in highly regulated industries.

Google Cloud Platform (GCP)

Google Cloud is highly respected for AI and data analytics.

Google’s strengths come largely from its deep experience with:

  • Machine learning
  • Search infrastructure
  • Big data processing
  • AI research

Many AI-focused startups prefer Google Cloud because of its advanced analytics capabilities.

Google Cloud Strengths

  • Powerful AI research tools
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  • Advanced Kubernetes support
  • Strong TensorFlow integration

Challenges for Enterprises

Some enterprises still view Google Cloud as less mature in traditional enterprise support compared to AWS and Azure.

Oracle Cloud Infrastructure (OCI)

Oracle has aggressively expanded into enterprise cloud computing.

OCI appeals heavily to organizations already running Oracle databases and enterprise systems.

The company focuses strongly on:

  • High-performance computing
  • Database optimization
  • Enterprise security
  • AI infrastructure scaling

Hybrid and Multi-Cloud Strategies

Many enterprises no longer rely on a single cloud provider.

Instead, they use:

  • Multi-cloud environments
  • Hybrid infrastructure
  • Distributed AI workloads

This approach reduces vendor lock-in and improves resilience.

However, complexity increases significantly.

Managing multiple cloud platforms requires advanced expertise.

Hidden Costs Businesses Often Ignore

Cloud AI costs extend far beyond monthly subscriptions.

Companies frequently underestimate:

  • GPU expenses
  • Data transfer fees
  • AI model training costs
  • Security management
  • Compliance audits
  • Staff training

Without careful planning, AI cloud spending can escalate quickly.

Why Enterprise AI Keywords Have High CPC

Enterprise AI contracts generate enormous long-term revenue.

Cloud providers, cybersecurity companies, consultants, and SaaS vendors aggressively compete for decision-makers searching these terms.

That’s why enterprise AI cloud computing keywords often command extremely high advertising rates.

Final Takeaway

The best AI cloud computing platform for enterprise businesses depends heavily on operational goals, existing infrastructure, compliance requirements, and long-term scalability plans.

AWS dominates in infrastructure scale. Azure excels in enterprise integration. Google Cloud shines in analytics and AI research.

The smartest organizations evaluate:

  • Security requirements
  • AI workload demands
  • Budget flexibility
  • Vendor ecosystem support
  • Long-term growth plans

Before making large AI infrastructure investments.

A rushed cloud decision can become a very expensive mistake later.

FAQ

Which cloud platform is best for enterprise AI?

The best platform depends on workload requirements, compliance needs, and existing business systems.

Is AWS better than Azure for AI?

AWS offers enormous scalability while Azure provides strong Microsoft integration and OpenAI capabilities.

Why is AI cloud infrastructure expensive?

AI workloads require powerful GPUs, advanced storage systems, and large-scale computing resources.

What industries use enterprise AI cloud platforms most?

Healthcare, finance, cybersecurity, manufacturing, and enterprise SaaS companies are major users.

What is multi-cloud infrastructure?

Multi-cloud environments use multiple cloud providers instead of relying on a single platform.