Full-Chain AI Inference Infrastructure Solutions for Enterprises
IFT provides one-stop enterprise AI inference deployment, covering site assessment, solution design, equipment delivery, rack deployment, system integration, and local adaptation. We help customers build scalable, sustainable inference infrastructure faster and at lower cost.
Inference is becoming the main stage.
Industry attention is shifting from “whether models can be trained” to “how inference can be delivered efficiently.” Inference infrastructure is entering the stage of system-level optimization.
From training to inference, procurement logic is shifting toward token delivery efficiency.
As AI applications move from model training to continuous inference, compute demand is no longer measured only by peak performance. Customers increasingly care about cost per token under long-term operation, energy consumption, deployment efficiency, and system stability. More competitive infrastructure solutions need to solve cost, energy efficiency, delivery, and scalability at the same time, so compute can become a sustainable business capability.
Surveyed enterprises consume 1B+ tokens per month
Expect to exceed 10B tokens per month by 2028
Organizations regularly use AI in at least one business function
Projected global data center electricity demand by 2030
Have started limited or scaled AI factory deployments
Expect at-scale AI factory deployment by 2028
Targeted TCO reduction in reference cluster scenarios
Modeled 5-year savings for a 100-server cluster
Solution 01
AI Factory Standardized Compute Factory
Build low-TCO, high-efficiency, and repeatable token production infrastructure for AI inference scenarios.
IFT provides low-TCO AI Factory standardized compute factory solutions for AI inference scenarios. The solution is built around standardized and modular design. It can adapt to IDCs, factory buildings, containerized deployment environments, and other site conditions. It supports rapid deployment of air-cooled, liquid-cooled, and multi-scale compute clusters, helping customers reduce construction complexity and accelerate inference capacity expansion.
Conduct early-stage assessment based on existing factory buildings, power capacity, and site conditions
Use standardized modules to accelerate compute cluster construction and capacity ramp-up
Support multiple types of cluster deployment, including air cooling and liquid cooling
Adapt to data centers, factory buildings, and containerized deployment scenarios
Complete system-level integration around power supply, cooling, and networking
Provide on-site commissioning, troubleshooting, delivery, and acceptance capabilities
Prioritize reuse of existing power and space resources
Reference 5-year integrated TCO optimization
Coordinated design around power density
Support standardized delivery and scalable replication
View Delivery Scope and Applicable Scenarios+
Suitable Customers
Suitable for medium and large customers, industrial parks, cloud service providers, and industrial customers that already have site, power, or old factory building resources and want to quickly build AI inference infrastructure.
Delivery Scope
Delivery includes site condition and business requirement assessment, compute cluster and cabinet solution design, network and storage configuration, power distribution design, cooling solution, system integration, rack deployment, on-site commissioning, troubleshooting, and project acceptance.
Future Expansion
The node scale can continue to expand as business workloads grow. The system can also be continuously optimized around cabinet density, compute output per unit of power, operating energy consumption, and O&M efficiency.
Solution 02
Private Inference Solution for SMBs
A small-scale local inference foundation for AI Agents and enterprise knowledge bases.
For small and medium-sized enterprise customers, IFT provides local inference solutions centered on private deployment, low power consumption, and low TCO. The solution uses locally deployed inference servers and small clusters as the foundation, helping customers run AI Agents, knowledge-base Q&A, internal search, customer service assistance, and other business scenarios inside the enterprise. It also reduces long-term dependence on public cloud APIs and cloud compute calls.
Use 8 or 16 servers as the core configuration for standardized small clusters
Support knowledge-base Q&A, internal search, customer service assistance, and AI Agent applications
Reduce long-term dependence on public cloud APIs and cloud compute calls
Improve data security, deployment autonomy, and cost controllability
Support model deployment, knowledge-base integration, and Agent workflow adaptation
Support single-scenario pilot validation before horizontal expansion
Standard small-cluster starting configuration
Local data loop and privacy control
More controllable long-term usage cost
Native support for localized Agent scenarios
View Delivery Scope and Applicable Scenarios+
Suitable Customers
Suitable for SMB customers that want to deploy AI capabilities inside the enterprise, especially companies that care about data security, permission management, cost control, business autonomy, and localized operation.
Delivery Scope
Delivery includes small inference cluster configuration, local model runtime environment, enterprise knowledge-base integration, AI Agent workflow deployment, permission and data isolation configuration, and go-live tuning support.
Future Expansion
Customers can start with a single business scenario, such as knowledge-base Q&A, internal search, customer service assistance, or workflow automation. Later, they can add more servers, expand model capabilities, and connect more departments and business workflows based on actual results.
Solution 03
Low-Power Desktop Inference Terminal
A terminal product for local validation, deployment testing, local development, and lightweight inference.
Not every AI inference need has to be deployed in the cloud or in a large cluster. For model validation, deployment testing, local development, lightweight inference, and scenario-based AI applications, the key concerns are often not peak compute performance, but local usability, deployment convenience, continuous usage cost, and implementation efficiency. The low-power desktop inference terminal is designed for lighter, more local, and lower-barrier inference needs.
Complete underlying adaptation, full-system optimization, and basic environment preparation in advance
Reduce additional customer investment from selection and assembly to deployment
Keep models, data, and runtime environments on the local side
Use low-power design to support lightweight inference tasks
Help customers complete model validation, deployment testing, and scenario integration faster
Suitable for small-scale pilots, development testing, and edge deployment needs
Lower deployment barrier
Keep data controllable
Reduce long-term cost
Shorten go-live cycle
View Delivery Scope and Applicable Scenarios+
Suitable Customers
Suitable for chip companies, model development teams, AI application teams, laboratories, and professional users that need lightweight local inference capabilities.
Delivery Scope
Delivery includes chip platform adaptation, full-system structural design, thermal and power optimization, preinstalled system environment, and basic inference environment configuration.
Future Expansion
The product can later support batch replication, version upgrades, software adaptation, and specific model optimization based on customer scenarios, enabling a path from validation devices to small-scale deployment.
Solution Matrix
Different customers have very different AI inference needs. IFT divides its solutions into infrastructure-level, small-cluster, terminal-level, and delivery and O&M capabilities, helping customers choose the right deployment path based on their current stage.
| Solution | Target Customers | Core Problem | What IFT Provides | Customer Value |
|---|---|---|---|---|
| Standardized Inference Infrastructure Solution | Medium and large customers, industrial parks, cloud service providers, existing industrial sites | The customer has existing site, power, or old factory building resources, but lacks a low-TCO upgrade path for inference infrastructure. | Provide overall AI Factory solution design and delivery services, covering site planning, compute clusters, cabinets, networking, power distribution, cooling, and hardware delivery services. | Reuse existing resources, lower the construction barrier, improve deployment speed, and strengthen long-term operating economics. |
| SMB Private Inference Solution | Small and medium-sized enterprises, manufacturing companies, service companies, internal knowledge-intensive teams | The customer relies heavily on public cloud APIs, does not want data to flow outside the enterprise, and lacks a local runtime environment for internal AI applications. | 8 / 16-server small clusters, local model environment, knowledge-base integration, and AI Agent workflows. | Keep data local, make long-term token cost more controllable, and bring AI capabilities into real business workflows. |
| Low-Power Desktop Inference Terminal | Chip companies, development teams, model validation teams, edge AI scenarios | Lightweight inference, model validation, and deployment testing do not always need cloud deployment or large cluster construction. | Underlying adaptation, full-system optimization, low-power operation, local closed loop, and ready-to-use deployment. | Lower the deployment barrier and shorten the cycle from validation to scenario integration. |
| Local Delivery and Long-Term O&M | Customers with existing equipment or existing sites but insufficient delivery execution capability | Multi-party coordination cost is high, and rack installation, joint debugging, acceptance, and O&M lack a unified responsible party. | Equipment delivery, system integration, stress testing, O&M support, and later expansion planning. | Bring infrastructure into a truly deployable, acceptable, and operable state. |
Bring AI inference infrastructure from planning to real operation.
Whether you are evaluating a site, designing an inference cluster, or preparing to deploy AI Agents, enterprise knowledge bases, and local model capabilities into business environments, IFT can provide the corresponding system-level solution.
Contact the Solutions Team