Inteleca

08/27/2026

A lot of infrastructure moves through our warehouse.

The hardware needs behind high-performance compute environments can look very different from one deployment to the next.

Different generations. Different architectures. Different use cases.

But one thing they have in common is there continues to be a market for infrastructure well beyond whatever happens to be the newest product announcement.

A few examples of what our clients are using:
✅RTX PRO 6000 GPUs
✅GPU servers
✅MSN3700-VS2F and SN5600 switches

08/25/2026

The GPU gets most of the attention. The rest of the server matters too.

This H100 server required a custom CPU configuration before deployment, so our team handled the processor swap, reassembly, testing, and validation in-house.

Supplying the hardware is only part of the job. The right configuration matters too, and we build systems around how they’ll actually be used.

08/20/2026

56% of the Ai4 attendees we surveyed named moving AI projects into production as one of their biggest priorities.

Getting there is another story.

When we looked at what could limit the next AI project, budget led the overall results. But among the group of respondents involved in infrastructure, the picture changed.

We break down what we learned from 148 attendees across 131 companies in our latest article: https://hubs.la/Q04tJKdS0

08/19/2026

Our team recently managed the decommissioning and remarketing of a large fleet of A100 GPU servers. These systems were removed from production, processed, tested, and ultimately placed back into the market for their next use.

We’ve sold the majority of these servers, with 50 remaining, tested and ready for their next environment.

Projects like this are a good example of what IT asset disposition looks like at scale.

It’s not just about removing equipment. It’s about understanding what still has value, securely processing the hardware and eradicating the data, and finding the right next destination for technology that has years of useful life left.

For specialized infrastructure like GPU servers, remarketing is key to the ITAD process, especially as organizations continue upgrading their data center environments for AI initiatives.

08/11/2026

We’re proud to share that Inteleca has been named to the 2026 Inc. 5000 list of fastest-growing private companies in America for the fourth time.

This recognition reflects 61% revenue growth over 2022-2025, and, more importantly, the work and resilience of our entire team and the trust our customers continue to place in us.

And if you think this year’s growth is impressive, just wait until next year’s numbers come in. We’ve already surpassed our previous annual revenue record as we continue supporting organizations across ITAD, high-performance computing hardware, and modern data center infrastructure.

Thank you to our team, customers, and partners who continue to be part of our growth and journey.

Read the full press release: https://hubs.la/Q04sFx7B0

07/29/2026

The hardware matters. The people behind it matter the most.

It takes a full team effort and plenty of hands-on work to keep everything moving. From our lab technicians to operations to sales and marketing, it has been a busy summer for the Inteleca team.

We connect people and businesses through technology. When hardware is no longer needed in one environment, it can still have plenty of life and value in the next.

But it is the people behind the hardware who use it to innovate, solve problems, and move ideas forward.

The infrastructure provides the foundation. The people are the ones who make the most of IT.

07/16/2026

Is AI just hype, or can it deliver a measurable return on investment?

At Hartsfield-Jackson Atlanta International Airport, CIO Chris Crist says AI is already producing real operational results.

Through its Enhanced Passenger Processing Program, the airport reduced passenger wait times within just 30 days—by 54% for U.S. citizens and 26% for non-U.S. citizens.

For organizations exploring AI, the goal should not be to chase the hype. It should be to identify the right use case and support it with the infrastructure, systems, and strategy needed to deliver a measurable outcome.

Hear more about how technology is shaping operations at the world’s busiest airport in the full episode, available now: https://hubs.ly/Q04pLR-30

07/06/2026

🏈 Our CEO, Paul Hogg, walked into Georgia Tech with a 3.8 GPA, five AP classes already under his belt, and a spot on the football team. He thought he had it all figured out.

📝 Then Differential Equations happened, and reality hit hard.

🐝 The Georgia Tech Alumni Association just featured Paul's "Welcome to Tech" story, the moment that humbled him and ended up shaping how he leads Inteleca today.

⤵️ Give it a read below!

Five Georgia Tech alumni reflect on the pivotal “wake-up call” moments that shaped their paths, revealing how challenge, failure, and opportunity define the Tech experience.

06/25/2026

Before the next batch of NVIDIA H200-powered servers leaves our facility, each system moves through a series of steps to help ensure it's ready for deployment.

🔍 Inspection & Testing
🔧 Custom Configurations
📸 Documentation & Photos
🚚 Shipment Preparation
✅ Ready for Deployment

Every deployment starts with a process.

This is a glimpse of what happens behind the scenes before AI infrastructure reaches its next customer environment.

06/23/2026

💡 NVIDIA isn't the only AI infrastructure conversation happening anymore.

✅ AMD is becoming a compelling option worth considering.

🔧 This Lenovo SR685a V3 was configured with AMD Instinct MI300X GPUs, delivering up to 192GB of HBM3 memory per GPU for demanding AI and HPC workloads.

📈 For organizations working with larger models, memory-intensive inference, or research environments, that additional memory capacity can be an important consideration.

💰 Of course, GPU selection isn't just about memory. Availability, software requirements, ecosystem compatibility, and budget all play a role. But more GPU memory can help reduce the need for model sharing across multiple GPUs.

🌐 The good news is that organizations building out their AI infrastructure today have more options than ever before.