FORGENIX // PRIVATE & ON-PREM AI

AGENTIC AI THAT NEVER LEAVES YOUR NETWORK.

We deploy LLMs and AI agents inside your own infrastructure, integrated with your business systems and knowledge bases. In a private deployment, everything in a request is processed within your perimeter and never sent to a third-party AI service. Hardware and models are selected for your workload — not for a vendor's catalog.

THIS DOMAIN INCLUDES //

ON-PREMISE LLM DEPLOYMENT

ON-PREMISE LLM DEPLOYMENT

WHAT IT IS //

On-premise LLM deployment means running a large language model on servers you own or control, so prompts, documents and generated answers are processed inside your own network and never sent to an external AI provider.

WHAT WE DO //

We size the stack, install and configure the model-serving layer, connect it to your identity system and business tools, and hand your IT team a runbook.

PRIVATE CLOUD AI

PRIVATE CLOUD AI

WHAT IT IS //

Private cloud AI runs your models in a dedicated, isolated environment, in a cloud region you choose or on infrastructure you control, instead of in a shared public AI service.

WHAT WE DO //

We design the environment around your data-residency and isolation requirements, deploy models and agents there, and put access control and logging in front of everything.

AIR-GAPPED AI

AIR-GAPPED AI

WHAT IT IS //

An air-gapped deployment has no connection to the public internet. It is used where data is too sensitive, or regulation too strict, to allow any external traffic.

WHAT WE DO //

We deliver models, tooling and updates through a controlled offline process, and design monitoring and support to work without remote access into your environment.

HARDWARE & MODEL SELECTION

HARDWARE & MODEL SELECTION

WHAT IT IS //

Model and hardware choices drive both quality and cost. The right model size and GPU or CPU capacity depend on the number of users, the languages, the length of the documents and the response time you need.

WHAT WE DO //

We benchmark candidate models on your own data against your workload and response-time targets, then size the hardware to match. We are not tied to a vendor, so the choice follows your requirements.

PRIVATE AGENTS & KNOWLEDGE BASES

PRIVATE AGENTS & KNOWLEDGE BASES

WHAT IT IS //

A private agent or knowledge assistant answers from your own documents and acts in your business systems — all inside the same perimeter as the model.

WHAT WE DO //

We connect the model to your knowledge bases and business systems, enforce each source system's permissions on every answer, and log what was asked and what was returned.

PROBLEM //

  • Sensitive data such as contracts, customer records, source code and strategy can't go to a public AI service, so the AI project stalls.
  • Staff paste company data into public tools anyway, and nobody can show where it went.
  • Regulators, clients or the board require that data stays inside the company or the country.

OUR APPROACH //

We start with the data: what it is, how sensitive it is, where it may live. Then we choose the deployment (on-premise, private cloud or air-gapped) and the model and hardware that fit the workload. Public models stay on the table for tasks where the data allows, but the sensitive core never leaves your perimeter. Around the model sit the same controls as anywhere else: DLP, an AI gateway, least-privilege access for people and agents, and an audit trail.

WHAT WE DO //

DEPLOYMENT
  • Models and agents inside your infrastructure
  • On-premise, private cloud or air-gapped
  • Installed, configured and documented for your IT team
SIZING
  • Workload analysis: users, languages, documents, latency
  • Model benchmarks on your own data
  • Hardware sized to the benchmark results
INTEGRATION
  • Connected to your business systems and knowledge bases
  • Source permissions enforced on every answer
  • SSO and role-based access
CONTROL
  • Requests and answers logged in a store you own
  • No data sent to public AI services
  • One gateway: model allow-list, budgets, usage limits
  • Segmented network, outbound traffic only where allowed

FOUR WAYS TO RUN IT //

ON-PREMISE
  • Your servers, your network
  • Data never leaves your perimeter
  • Best for sensitive data and existing infrastructure
PRIVATE CLOUD
  • Dedicated, isolated environment
  • Region and access under your control
  • Best for scale without owning hardware
AIR-GAPPED
  • No external connectivity
  • Updates moved in through a controlled process
  • Best for the most sensitive environments
PUBLIC LLM — BY TASK
  • Fastest start, pay per use
  • Only for data classified as non-sensitive
  • With masking, DLP and contractual safeguards

TYPICAL PRIVATE WORKLOADS //

MAIL & DOCUMENT ASSISTANT
  • Years of email and documents indexed into a private knowledge base
  • Drafts replies with the context of every earlier exchange with that client
  • Add-in for the mail client your team already uses
SPEECH-TO-TEXT & MEETING NOTES
  • Transcription and summaries on your own servers
  • Commercial secrets never reach a third-party service
  • Tasks and follow-ups extracted automatically
KNOWLEDGE ASSISTANT
  • Answers from your policies, contracts and project history
  • Every answer with a source link
  • Permissions of the source systems enforced
DOCUMENT PROCESSING
  • Contracts, invoices and KYC packs processed in-house
  • Personal and critical data masked before the model
  • Exceptions routed to your team

WHAT YOU GET //

  • LLMs and agents running inside your perimeter
  • Model and hardware choices backed by benchmarks on your own data
  • Business systems and knowledge bases connected, with source permissions enforced
  • Logs and an audit trail you own; private workloads send no data to public AI services
  • Handover documentation and a runbook for your IT team

DATA// In 42% of documented deployments the model itself was fully interchangeable — the platform and process around it were the durable advantage. — Stanford Digital Economy Lab, 2026

PATH// this service applies in the DESIGN and IMPLEMENT phases whenever the audit selects a private deployment — see all services and how it lands on the calendar.

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