Analitica builds enterprise AI that turns internal documents, live data and domain knowledge into reliable decision support for employees, operators and management — designed for secure deployment, flexible integration with existing IT/OT environments, and practical use in regulated, data-sensitive and technically demanding organizations.
Public AI systems are powerful, but business use often requires current information, traceable answers, domain-specific understanding, and strong control over sensitive data. Analitica’s AI solutions address these requirements by combining retrieval, semantic analysis, explainable outputs, and secure integration with your existing systems and knowledge sources.
Each solution works on its own and as part of a whole. They share one secure retrieval core, so a document indexed once can power search, monitoring, voice interaction, and the shopfloor.
Flexible deployment options, including on-premise installation.
References, auditability and role-based access control.
With document systems, databases, file shares and workflows.
Built for the specifics of local languages, including complex morphology.
Secure AI-powered knowledge retrieval and generation over your information sources.
Analitica.AI.RAG is a retrieval-augmented generation solution for secure, efficient search across business documentation and other internal knowledge sources. It combines a hybrid search engine, domain-aware AI and enterprise security controls so users can quickly access relevant information without exposing internal knowledge outside the organization.
It's designed for organizations that need reliable answers grounded only in approved data sources. Instead of generating from general model knowledge, the system retrieves relevant content from configured repositories and produces contextual answers with direct references to the original documents and exact content locations.
Traditional and semantic search combined for accurate retrieval across large collections — tuned to the specifics of local languages, including synonyms, lemmatization and the complex morphology of highly inflected languages such as Slovenian.
Recognizes legally structured components — articles, sections and headings — and keeps them whole, so answers and summaries carry precise references.
Generates enriched natural-language answers only from retrieved source content, preventing hallucinations and improving reliability.
Every answer can include a link to the source document and the precise referenced section, making outputs easy to verify.
Integrates with Active Directory or Microsoft Entra, so users only receive information they're allowed to access in the source system.
SharePoint, file shares and email archives; formats from DOCX, PDF, TXT, PPTX and HTML to engineering formats such as DWG, DXF and STEP — indexed and updated automatically.
Configure multiple agents, each dedicated to a specific department or task.
Reads the structure of technical drawings — title block, bill of materials, item positions and references to standards — and 3D model data such as assembly structure, components, materials and revisions, so answers stay tied to the valid revision.
Keeps the link between text and its charts, tables and figures — captions, legends and citations included — so answers can draw on findings presented in tables and charts, not only running text.
Intelligent monitoring of regulatory, market and domain-relevant information.
Analitica.AI.Monitor is an AI-based solution for automated scanning, analysis and alerting across selected information sources. It helps organizations monitor regulatory updates, market developments, compliance-relevant publications and other external signals, then routes only relevant changes to the right stakeholders.
Instead of burdening teams with irrelevant notifications, it continuously watches configured sources, detects new publications or changes, analyzes their meaning, and distributes concise alerts with summaries, relevance scores and source references — turning monitoring from a manual burden into a structured, auditable capability.
Continuous monitoring of regulatory databases, government portals, industry publications, corporate websites, news sources and other configured channels.
Identifies new items and compares versions to detect meaningful updates — legislative changes, revised guidelines, market opportunities and competitor signals.
Natural-language processing evaluates the real importance and implications of each change, reducing alert fatigue and improving focus.
Routes relevant updates to stakeholders via email, dashboards, task-management integrations or APIs — with AI-generated summaries and impact assessments.
Maintains traceability for source scans, relevance analysis, generated alerts and the actions taken afterward.
Portable deployment across on-premise, hybrid and cloud, with scalable resourcing and integration into existing IT systems.
Two-way speech interface and conversational agent for call centers and user support.
Analitica.AI.Vox is a two-way speech interface and conversational agent built to automate the work of agents in call centers and user-support departments. It converses with the caller in natural language and composes answers from your knowledge base — for example Analitica.AI.RAG — and from real-time data in your backend systems.
It takes over repetitive calls end to end — answering frequent questions, providing balance and status information, guiding users through procedures — and hands anything beyond its scope to a human agent together with a conversation summary and the caller's verified identity. A narrower set of the same speech interface serves hands-free work in industrial environments.
Natural two-way conversation in local languages, with Slovenian and further languages supported.
Connects to Analitica.AI.RAG for grounded answers from internal documents, policies, manuals and other curated knowledge.
Retrieves real-time information from client systems through APIs, business applications, CRM/ERP platforms or custom services.
Separates inquiries that need no authentication from those that do. For personal or financial data it verifies identity through your existing systems, then releases only what that caller is entitled to.
Not a general-purpose chatbot: you define the tone, the actions it may perform, the actions that are explicitly prohibited, and when it escalates to a human operator.
Integrates with existing call-center and telephony systems, plus web portals, service desks, kiosks and business applications — with every conversation logged for quality control and audit.
Every solution ships as containers, so it runs the same on your hardware or in the cloud — and adapts to your security policy, not the other way around.
full isolation
The entire system, including the generative model, runs on your own infrastructure — completely isolated from the outside world.
balanced
The generative step can use an external API while your data stays managed locally — ideal for non-sensitive content such as public laws and directives.
fully managed
All infrastructure is deployed in the cloud for the fastest start and elastic scaling, with the same containerized core.
Your sources
docs, SharePoint, OT/IT
Hybrid search
vector + relational
AI generation
grounded &
Cited output
RAG, Monitor, Vox
Custom projects since 2001
These four products grew out of custom machine-learning work we have been delivering since 2001 — as an interdisciplinary team of researchers and software engineers, across manufacturing, insurance, telecommunications, electricity distribution, retail and environmental monitoring.
Our strongest ground is where AI meets signal processing and spectral analytics — the data that never fits neatly into rows and columns.
See the work at Analitica Labs
Vibration, sound & voicesignal & spectral analysis
Image, video & HSIcomputer vision, hyperspectral
3D models, GIS & CADgeometry & spatial data
Natural languageNLP & document understanding
IoT sensor datatime series & telemetry from the field
Insurance
Manufacturing
Telecommunications
Utilities, retail & hospitality
Environment
Electricity distribution
Case · Manufacturing · 3D CAD
In designer glass production, the preform geometry that yields a given bottle has traditionally been a matter of expert judgment and trial runs. We trained a machine-learning model that derives the 3D preform model directly from the 3D model of the finished product, as specified by the customer.
Want to see more?
We'll prepare a demonstration on your chosen sources and systems — so you can judge it on your reality, not ours. Get a direct view of the capabilities, an assessment of result quality and confirmation it meets your security policy.
