ON-PREMISE AI
Local LLMs for every company and research institution.
Run generative AI on your own infrastructure, without depending on external APIs. GRIDTECH, LLC builds and operates AI environments that keep your data in-house, and supports the development work that follows.
WHY ON-PREMISE
Why choose a local LLM
Electricity has always reached homes and businesses from a power plant. Today, most generative AI depends entirely on an external "power plant" — a cloud API. GridTech offers the option of placing AI inside your own environment, the way you might install your own generator on your own site.
What matters is not replacing every LLM with a local one. It's having the option to run an LLM inside a boundary your organization controls, so AI can be applied even to data you cannot send to an external service and work you cannot make dependent on an external provider.
An organization's real value lies in the data it cannot send outside. A local LLM is the strategic foundation for turning that data into intelligence while keeping it under the organization's own control — independent of any external service's terms.
Data sovereignty and confidentiality
The information you feed into an AI system is itself an asset of your company or institution. Sending it to an external API means handing that information outside your organization. In healthcare, research, government, and manufacturing, some information cannot be sent outside at all. With a local LLM, information never leaves your own environment — one of the most reliable forms of information control available.
Dependency risk
External APIs carry risks you cannot control: pricing changes, service discontinuation, changes to terms of use, model deprecation, network failures. Building part of your operations on an external API means placing part of your business process on someone else’s roadmap. AI running on your own infrastructure is independent of these external factors.
Cost structure
Usage-based APIs cost more the more you use them. For steady, ongoing use, an upfront investment in equipment can end up being more cost-effective. That said, on-premise is not always cheaper. It requires upfront hardware investment, electricity, and operational effort, so for low-frequency or short-term use an external API is often still the more reasonable choice. GridTech proposes whichever fits based on your actual usage pattern.
Control
You are free to choose and swap models, and to fine-tune them on your own data. Without a network call to an external service, latency stays stable. Audit logs can be captured entirely within your own environment.
Five strategic values a local LLM provides
| Strategic value | What the organization gains |
|---|---|
| Data sovereignty | Decide where inputs, search targets, generated output, and logs are processed and stored |
| Operational sovereignty | Manage model updates, shutdowns, evaluation, access rights, and usage limits yourself |
| Continuity | Limit the impact of network outages, API downtime, pricing changes, and service discontinuation |
| Reproducibility | Fix the model, weights, and inference conditions so results can be re-verified |
| Organizational fit | Optimize for your terminology, internal rules, research field, or manufacturing process |
"Local" does not mean "safe"
Running locally does not automatically guarantee safety. A misconfigured permission can leak information to another internal department, and data can leak from RAG, logs, or caches. Wrong: local means safe. Right: local means the organization can design, verify, and control safety itself. Read more →
GridTech does not reject the cloud. We support choosing cloud or on-premise based on the use case — a local LLM is one option among others, offered where it is needed.
Read the full article (including references and decision criteria) →
AI DEVELOPMENT
AI Development Support
Core businessWe support running generative AI on your own infrastructure instead of relying on external APIs, from planning through construction and operation.
What we provide
- Construction and operation support for in-house local LLMs
- AI agent development
- AI development support in on-premise environments
Who this is for
- Organizations that want to use generative AI but cannot send their information outside
- Organizations already using external APIs for AI who want to prepare for the risks of that dependency
- Organizations that want to embed AI into concrete tasks such as searching and summarizing internal documents
How we work
- 01
Requirements
We confirm the nature of the data involved, the performance required, and the budget.
- 02
Construction
We select an LLM and hardware configuration suited to the use case and build the environment.
- 03
Operation
We continue to support operation, model updates, and further development after construction.
IT SUPPORT
IT Support
Before AI development became our core business, GridTech carried out contract development including disaster-prevention systems. We handle system development end to end, from requirements definition through design, implementation, and operation.
- Contract development including disaster-prevention systems
- System construction
- System operation
EVENT SUPPORT
Event Support
We support online event streaming, from arranging and setting up equipment through running the stream on the day. We also support the operation of small-format events such as wine tastings.
- Live streaming support for events
- Operational support for events such as wine tastings
COMPANY
Company
| Name | GRIDTECH, LLC |
|---|---|
| Representative | Makoto Watanabe |
| Location | Chiyoda-ku, Tokyo, Japan |
CONTACT
Contact
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