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Private RAG – Secure integration of generative AI

We deploy private Azure OpenAI instances where your data never leaves your tenant, never trains public models, and is protected by enterprise-grade security.

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The challenge: the risk of "shadow AI"

Employees are already using AI, often pasting sensitive company data into public tools. This creates significant risks and inefficiencies:

Data leakage

When employees paste financial reports or code into public ChatGPT, that data may be used to train the model, potentially exposing trade secrets.

Information silos

Your collective knowledge is buried in thousands of PDFs, SharePoint sites, and emails. Finding the right answer takes hours.

Hallucinations

Public models guess when they don't know the answer. You need an AI that answers based strictly on your facts.

The "blank page" problem

Teams waste time drafting emails or reports from scratch instead of leveraging existing templates and knowledge.

The solution: private retrieval-augmented generation (RAG)

We build a "Corporate Brain"—a secure chat interface that understands your specific business context without exposing data to the outside world.

01

Total data isolation

We use Azure OpenAI Service, which guarantees that your data is not used to train Microsoft's or OpenAI's base models.
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Retrieval-augmented generation (RAG)

02

Instead of relying on the model's pre-trained memory, the AI searches your live documents first, finds the relevant facts, and generates an answer based only on that evidence.
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03

Citations & references

Every answer includes footnotes linking back to the original source document (e.g., "See Page 12 of HR Policy.pdf"), ensuring trust and verifiability.

How it works: building the knowledge engine

We implement a sophisticated pipeline that turns your static documents into an interactive knowledge base.

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01

Data ingestion & chunking

We connect to your data sources (SharePoint, Azure Blob, SQL, Confluence). We break large documents into logical "chunks" so the AI can process specific sections rather than whole books.

02

Vectorization (embeddings)

We convert these text chunks into mathematical vectors using OpenAI embedding models. This allows the system to understand the meaning of a query, not just match keywords.

03

Semantic search & generation

When a user asks a question, the system finds the most relevant vector chunks in milliseconds. It sends these chunks—along with the user's question—to the GPT-4 model securely. The model summarizes the chunks into a coherent answer.

Technology stack: enterprise-grade AI

We utilize the native Azure AI stack to ensure scalability and security.

LLM engine

Azure OpenAI Service (GPT-4o / GPT-3.5-Turbo) for reasoning and generation.

Vector database

Azure AI Search for indexing and retrieving relevant document fragments.

Orchestration

Semantic Kernel or LangChain to manage the logic between the user, the database, and the AI.

Interface

A custom branded web app (React/Python) or integration directly into Microsoft Teams.
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Professnet is officially certified for: ISO 27001

ISO certifications reflect our focus on delivering reliable and secure technology services.
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Tier-1 Partner

Direct collaboration with Microsoft engineers

16 Years

Experience in system design

ISO 27001

Certified information security

< 15 min

Critical incident response time (SLA)

Business value: productivity with privacy

Deploying a private RAG solution transforms how your organization handles knowledge.

  • Zero data leakage: Your intellectual property remains strictly within your Azure subscription boundaries.
  • Instant answers: Reduce the time employees spend searching for information by up to 90%.
  • Onboarding accelerator: New employees can ask the AI "How do I configure the VPN?" or "What is our vacation policy?" without disturbing colleagues.
  • Fact-based accuracy: The AI is instructed to say "I don't know" if the answer isn't in your documents, drastically reducing hallucinations.

Deliverables: your AI ecosystem

We provide a turnkey solution ready for internal deployment.

Deliverable

Technical specifications

Private chat interface

A web-based chat application (like ChatGPT) branded with your logo, supporting file uploads and chat history.

Ingestion pipeline

Automated workflows (Azure Functions) that watch your folders for new files and automatically update the AI's knowledge base.

Infrastructure as code

The entire environment (AI Search, OpenAI, App Service) deployed via Bicep/Terraform for repeatability.

Governance dashboard

Logging and monitoring of all queries (via Azure Monitor) to see what employees are asking and detect usage patterns.

Engagement timeline: from concept to chat

Week 1

Discovery & data prep

We identify the high-value use cases (e.g., "HR Bot" or "Technical Support Helper") and audit the quality of your source documents.

Week 2

Rapid prototyping

We deploy the Azure OpenAI infrastructure and index a sample dataset to demonstrate the "Chat with your Data" capability.

Week 3

Interface & prompt tuning

We refine the "system prompt" to control the AI's personality and strictness. We build the frontend and integrate authentication (Entra ID).

Why partner with us?

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Security architects

We aren't just AI developers; we are cloud security experts. We ensure the solution is protected by Private Endpoints and VNETs.

Prompt engineering skills

We know how to talk to the model to prevent "jailbreaks" and ensure it adheres to corporate tone.

Microsoft partners

We have early access to the latest Azure AI features and best practices.

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What our customers say about us

Their professionalism, reliability, and commitment to each project ensure that every collaboration runs smoothly and efficiently. I wholeheartedly recommend Professnet as a solid and competent business partner.

Mariusz Duczek

Managing Director @ SCHURTER

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Thanks to their skills in system integration and technological consulting, we have significantly improved our operational processes. Projects are executed not only on time but with the utmost care.

Jarosław Sojewski

Managing Director @ FOMAR Friction

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The professionalism of the team, their quick response to our needs, and in-depth analysis have enabled us to optimize our cloud environment and enhance its security. We confidently recommend Professnet as a solid technology partner.

Maciej Kromkowski

Board Member @ Power21

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Case studies

From Local Server Room to Global Cloud

How abcgo.pl Reduced Costs by 40% and Secured Client Financial Data.

ERP System:

enova365

Technologies:

Microsoft Azure, Azure Virtual Desktop (AVD), SQL Database

Key Achievement:

40% OPEX Reduction
Read more
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hero-m365
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Building a resilient security architecture

How KZBS secured the ecosystem of 500+ cooperative banks against modern threats.

Sector:

Banking / Public Trust

Scale:

500+ Associated Banks

Key Compliance:

NIS2, DORA, GDPR, ISO 27001
Read more

FAQ

No. When using Azure OpenAI Service (Enterprise), Microsoft contractually guarantees that your data is not used to train their foundation models. Your data remains yours.

We can implement "Document Level Security." If a user asks a question about a document they don't have permission to view in SharePoint, the AI will not see that document and will not answer based on it.

The system can ingest PDF, Word (DOCX), Excel, PowerPoint, Text, HTML, and Markdown. We can also connect to external wikis like Confluence or Notion.

Costs are consumption-based. You pay for the Azure resources (AI Search + OpenAI tokens). For a mid-sized internal tool, monthly run costs are often surprisingly low compared to buying per-seat licenses for public SaaS tools.

Technology Partners

cisco
citrix
dell
eset
fortinet
fujitsu
hpe
huawei
jabra
lenovo
manage-engine
microsoft
oracle
palo-alto
redhat
symantec
trend-micro
vmware
xerox
cisco
citrix
dell
eset
fortinet
fujitsu
hpe
huawei
jabra
lenovo
manage-engine
microsoft
oracle
palo-alto
redhat
symantec
trend-micro
vmware
xerox
cisco
citrix
dell
eset
fortinet
fujitsu
hpe
huawei
jabra
lenovo
manage-engine
microsoft
oracle
palo-alto
redhat
symantec
trend-micro
vmware
xerox
cisco
citrix
dell
eset
fortinet
fujitsu
hpe
huawei
jabra
lenovo
manage-engine
microsoft
oracle
palo-alto
redhat
symantec
trend-micro
vmware
xerox
cisco
citrix
dell
eset
fortinet
fujitsu
hpe
huawei
jabra
lenovo
manage-engine
microsoft
oracle
palo-alto
redhat
symantec
trend-micro
vmware
xerox
cisco
citrix
dell
eset
fortinet
fujitsu
hpe
huawei
jabra
lenovo
manage-engine
microsoft
oracle
palo-alto
redhat
symantec
trend-micro
vmware
xerox

We are always happy to talk

Reach out to us about a project, consultation, or to explore other collaboration opportunities.

portrait Lukasz Tabaczek

Lukasz Tabaczek

CEO
professnet@professnet.pl
+48 516 524 227
Schedule a meeting
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03-219 Warsaw
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VAT ID: PL 5242 793 610

Cloud & Infrastructure:

Migration & Repatriation Azure Landing Zone Secure Connectivity Intune & Device Management

Apps, Data & AI:

App Modernization Factory Serverless & Event-Driven Azure DevOps & IaC Private RAG (GenAI)

Security & Compliance:

Managed SOC Identity & Entra ID DevSecOps (SSDLC) Security Consulting

Managed Services:

Managed Infra (24/7) Co-Managed Azure Managed Compute (VMs) Data Lifecycle & Archive

Assessments:

Azure 3D Assessment NIS2 & DORA Audit AI Readiness Check App Mod. Assessment AKS Health Check

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