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Stand up GPU and HPC environments ready for production AI — enterprise IT services from rentech

AI infrastructure

Stand up GPU and HPC environments ready for production AI

Generic server racks waste budget on AI workloads. We design NVIDIA and AMD stacks for training, inference and edge — then supply, rack, cool, commission and hand off with burn-in complete.

Request AI infra quoteSee the delivery flow
  • NVIDIA and AMD accelerator stacks
  • Design through commissioning
  • Production burn-in and handoff

Request AI infra quote

Share workload type, scale and timeline — we propose GPU/HPC options.

Who AI infrastructure is for

When the workload needs accelerators — not another general-purpose rack.

  • ML / data science teams

    Training and fine-tuning clusters sized to model and dataset reality.

  • Product / platform

    Inference capacity with latency and throughput targets built into the design.

  • Enterprises starting AI pilots

    Right-sized first clusters without overbuying GPUs you will not fill.

  • Edge / latency-critical apps

    Inference closer to users where round-trips to a central DC fail SLAs.

What AI infrastructure includes

Hardware, networking, cooling considerations and commissioning — not boxes only.

  • NVIDIA A100, H200, and L40S GPU configurations
  • AMD Instinct MI300X accelerator stacks
  • HPC cluster design, deployment, and optimization
  • AI inference at the edge for latency-critical workloads
  • End-to-end: hardware + networking + cooling + commissioning

How AI infrastructure projects run

From workload discovery to production handoff.

  1. Discover the workload

    Training vs inference, model size, data locality and growth plans drive the design.

  2. Design the GPU / HPC stack

    We propose NVIDIA or AMD configurations with networking, storage and power/cooling fit.

  3. Supply and rack

    Hardware is procured, delivered and racked to the agreed design.

  4. Commission and burn-in

    Firmware, networking and stability tests prove the cluster before you load production jobs.

  5. Handoff and support

    Documentation, training and optional managed support keep the stack healthy after go-live.

Request AI infra quote

Why rentech for AI infra

Accelerator projects fail on integration — we own the path to production.

Start an AI infra quote
Workload-first design
GPU choice follows training/inference needs — not a one-size SKU.
End-to-end delivery
Supply, rack, network, cool and commission under one plan.
Burn-in before handoff
You inherit a tested cluster, not unopened crates.
Lifecycle partner
Expand, support or retire through the same relationship.

Trusted by Indian businesses

  • Infosys
  • Wipro
  • TCS
  • HCLTech
  • Zoho
  • Razorpay
  • Swiggy
  • Paytm
  • PhonePe
  • Zomato

Customer reviews

Teams building AI capacity work with rentech for design-through-commission delivery — here is their feedback.

  • Infosys

    We rented 40 Dell Latitude laptops for a three-month onboarding batch at our Bangalore campus. Devices arrived pre-imaged with Windows 11 Pro, and the GST invoice made procurement straightforward.

    Ananya R.IT Administrator, Infosys
  • Wipro

    Our design team needed MacBook Pro units for a client sprint in Koramangala. rentech matched M-series configs quickly and handled same-week delivery without delays.

    Rahul M.Design Lead, Wipro
  • TCS

    For a certification programme we needed identical Lenovo ThinkPads across two classrooms in Whitefield. Same specs, single invoice, and pickup at the end of the term — exactly what we needed.

    Priya S.Training Coordinator, TCS
  • HCLTech

    HP EliteBooks for a six-week consulting engagement. When one unit had a keyboard issue, replacement was arranged within a day so our consultant could stay productive.

    Vikram K.Operations Manager, HCLTech
  • Zoho

    We deployed ASUS Zenbook units for a field sales team travelling across Karnataka. Lightweight, reliable, and easy to scale when we added five more reps mid-quarter.

    Deepa N.Sales Director, Zoho
  • Razorpay

    Samsung Galaxy Book Pro rentals for our executive team during an office relocation in Bellandur. Premium displays for board presentations and flexible monthly terms until our permanent fleet arrived.

    Arjun T.Head of Administration, Razorpay
B2BBusiness laptop rentals
GSTCompliant invoicing
FlexibleRental periods
SupportDevice replacement

Planning a GPU or HPC build?

Tell us workload type, target scale and site constraints. We return a design outline and commercial next steps.

Request AI infra quoteWhatsApp Your Requirement

AI Infrastructure FAQs

Do you support both NVIDIA and AMD?

Yes. We design around NVIDIA (including A100, H200, L40S class) and AMD Instinct stacks based on workload, availability and budget.

Can you help if we only need inference at the edge?

Yes. Edge inference designs focus on latency, power and form factor — not only dense training clusters.

Is software stack included?

We commission hardware and networking to a production-ready baseline. Application frameworks and model ops remain yours unless scoped separately.

Can you deploy GPU racks at our data centre?

Yes. Design can hand off to our deployment teams for rack-and-stack, networking, burn-in and production sign-off in India.

Do you rent GPUs or only sell?

Commercial models depend on availability and project length. Share duration and scale — we will recommend purchase, lease or hybrid options where feasible.

How long do projects take?

Timelines depend on GPU allocation and site readiness. Share target dates early so we can sequence procurement and deployment realistically.

AI Infrastructure in Bangalore

Standing up GPU and HPC environments is different from ordering another rack of general-purpose servers. Accelerator workloads need the right GPU configuration, adequate power and cooling, low-latency networking, and stability testing before production jobs go live. Rentech designs, supplies and commissions NVIDIA and AMD-based infrastructure for training, inference and edge AI — with burn-in complete before handoff.

Generic server racks waste budget on AI workloads. The design phase determines whether a cluster will deliver the throughput your models need or sit underutilised because the networking fabric cannot keep up with the GPUs.

GPU and HPC Stack Design

Workload discovery comes first — training versus inference, model size, data locality and expected growth shape the configuration. Rentech then proposes NVIDIA configurations, including A100, H200 and L40S-class accelerators, or AMD Instinct stacks depending on workload fit, availability and budget.

The design also covers networking, storage tiering, and power and cooling constraints at the target site. A cluster that looks right on a spec sheet can fail in production if the row cannot deliver the power budget it needs.

From Supply to Production Handoff

Hardware is procured against the agreed design, delivered to site and racked by deployment engineers. Networking is configured, firmware is updated, and burn-in testing proves stability before the cluster is signed off. Documentation and optional training leave your team ready to operate from day two — not staring at unmarked crates with a shipping manifest.

Beyond Initial Build

AI infrastructure grows. Rentech remains a lifecycle partner for expansion, managed support and eventual asset refresh or retirement. The same partner that designed and commissioned the original cluster can scale it when model sizes increase or inference demand expands to new regions.

Tell rentech your workload type, target scale and site constraints. You will receive a design outline and commercial next steps.

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