Get Started

State-of-the-art AI on your proprietary data — at a fraction of the compute cost.

Transfer Hub

Manages fine-tuning workflows for large pre-trained models (LLMs, vision transformers, time-series foundation models) on proprietary enterprise data with parameter-efficient tuning methods. Enables traditional industries to leverage state-of-the-art models without the prohibitive cost of training from scratch.

Why It Matters

TransferHub puts state-of-the-art AI within reach of enterprises that could never justify training foundation models from scratch.
Parameter-efficient fine-tuning adapts LLMs, vision transformers, and time-series foundation models to proprietary data — capturing frontier-model capability at a fraction of the compute cost.
1.png

Frontier AI without frontier budgets

Fine-tuning a pre-trained model costs a tiny fraction of training from scratch — traditional enterprises get state-of-the-art performance on their own data without hyperscaler-scale spending.

2.png

4–8x lower GPU memory with LoRA/QLoRA

Parameter-efficient methods make fine-tuning feasible on accessible hardware — models that would demand massive A100 clusters run on modest instances.

3.png

Proprietary data stays proprietary

Fine-tuning happens on the enterprise's own infrastructure with their own data — competitive advantage gets built in, not shipped out to a third-party API.

The Cloudly Advantage

TransferHub is Cloudly’s answer to the question every client boardroom is asking: “what’s our LLM strategy?” It rides the strongest demand wave in enterprise IT while anchoring that demand to our GPU infrastructure, cluster, and MLOps services — turning GenAI hype into concrete, winnable engagements.
1.png

Rides the GenAI budget wave

LLM initiatives have board-level urgency and dedicated budgets — TransferHub gives BD a credible entry into conversations every competitor wants.

2.png

Premium GPU infrastructure services

P4d/G5 and A100 provisioning, tuning, and operations are high-value Cluster Services engagements — with ComputeOrchestrator cutting the spot-instance cost alongside.

3.png

Data-sovereignty differentiator

On-infrastructure fine-tuning beats API-based AI for banks and healthcare firms barred from sending data to external model providers — a deal-winner in our core verticals.

4.png

Full platform pull-through

Fine-tuning jobs need TrainForge scheduling, HyperTune optimization, ExperimentHub tracking, and SyntheticGen data — TransferHub deals naturally expand into platform contracts.

5.png

HuggingFace stack consultancy

PEFT and Axolotl expertise positions Cloudly as a hands-on GenAI implementation partner, not just an infrastructure vendor — commanding premium consulting rates.

The Final Takeaway

Repeat revenue by design — Every new use case, model generation, or data refresh triggers another fine-tuning cycle — engagements recur naturally as the client's AI ambitions grow.

Powered By

HuggingFace PEFT

Core to the TransferHub technology stack.

LoRA/QLoRA

Core to the TransferHub technology stack.

Axolotl

Core to the TransferHub technology stack.

AWS P4d/G5 instances

Core to the TransferHub technology stack.

Let's start a quick, free consultation

Get Started