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AI audit
We identify use cases with measurable impact and assess data, risks, workload and infrastructure readiness.
Private AI infrastructure
Private AI that works
inside your infrastructure.
We design, deploy and adapt AI systems on company-owned resources — from audits and hardware selection to production and model evolution.
PRIVATE AI CORE ONLINE
INTAI CORE
01Models
02Data
03Systems
04Control
Data stays insideFull controlIndependent of external APIsIntegrated with your stack
01 / NEWS & ANALYSISPractical AI
Practical AI
without noise or hype
In-depth articles about private models, RAG, AI agents, security and implementation economics.
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All news and analysis 02 / FULL LIFECYCLEFrom an idea to a
From an idea to a
working system
One engineering partner is responsible for the integrity of the solution: business impact, models, infrastructure, security and integrations.
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Private AI
We design an on-premise AI environment and select models, servers and software for real production scenarios.
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RAG systems
We build enterprise document search with sources, access controls and measurable answer quality.
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AI agents
We automate connected actions across enterprise systems with limited permissions and human control.
03 / TECHNOLOGY
We build AI around the business, not the other way round
We select components without locking the company into one vendor. The architecture stays portable, observable and understandable to your team.
04Business interfacesCopilot · Search · Automation
03AI orchestrationAgents · RAG · Guardrails · Eval
02Models and dataOpen-weight LLM · VLM · Embeddings
01Your infrastructureGPU · Storage · Network · IAM
04 / WHY ON-PREMISEPrivate AI means
Private AI means
control without compromise
Technology independence becomes a practical advantage: lower risk, faster processes and transparent economics.
Data stays inside
Documents, prompts, embeddings and logs never have to leave your infrastructure. You define the perimeter, retention rules and access levels.
Control over the model
Model versions, system prompts, knowledge bases and fine-tuning are fixed and reproducible, without unexpected provider-side behavior changes.
Predictable economics
No per-token billing or exposure to foreign-currency pricing. At stable utilisation, hardware becomes a manageable infrastructure asset.
Low latency
Models run close to the data and enterprise systems, accelerating conversations, batch jobs and real-time workflows.
Works without external access
Private and isolated environments continue operating during provider outages, restricted internet access or service availability changes.
Deep integration
AI connects to ERP, CRM, document systems, storage and internal APIs with role-based access, audit trails and business context.
Designed for compliance
The architecture accounts for data localisation, access separation, logging and internal security policies from the beginning.
Your intellectual core
Domain datasets, adapters, evaluations and accumulated expertise remain company assets instead of becoming part of an external platform.
05 / PROCESS
We start with the outcome
We do not sell AI for its own sake. We first define the business metric and quality criteria, then choose the technology.
- 01
Discovery
Interviews, process map and data assessment
- 02
Prototype
Quality validation on representative examples
- 03
Architecture
Security, infrastructure and TCO
- 04
Implementation
Integration and acceptance testing
- 05
Evolution
Monitoring, evaluation and improvement
Enterprise search
Answers grounded in internal documents, with sources and access controls.
RAGAI assistants
Assistants for sales, support, legal, analytics and engineering teams.
AGENTSDocument processing
Classification, extraction, review and routing without external cloud services.
VLMIntelligent automation
Connected actions across enterprise systems under human control.
WORKFLOW07 / START A PROJECTLet's discuss the task,
Let's discuss the task,
data and perimeter
Describe the process you want to strengthen with AI. In the first meeting we will review the use case, constraints and a realistic path to a prototype.
request@int-ai.ru ↗