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AI-Powered Applications

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Our research projects cover areas such as artificial intelligence, data analytics, cybersecurity, and workflow innovations in line with RIS3 2021+ priorities.

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AI-Powered Applications

About the service

We build applications where artificial intelligence is the core — from document search and intelligent assistants to autonomous workflows. We combine NLP, RAG, computer vision, and predictive models with robust product architecture so AI delivers a measurable impact while maintaining security, compliance, and explainability. We ship production-ready solutions: reliable, scalable, and integrated with your systems.

Intelligence in practice

  • AI assistants: Contextual answers, summaries, and next-best actions on top of your data.

  • RAG & search: Relevant results from internal documents with citations and access control.

  • Workflow automation: Task orchestration, data extraction, and intelligent approvals in processes.

From idea to production

We start with a pilot with clear KPIs, then extend the solution with integration interfaces, audit, access management, and telemetry. AI capabilities are encapsulated into services with consistent APIs and strict rate limiting to be safe and predictable in real-world conditions.

Technology & approach

  • NLP & RAG: Embeddings, vector databases (FAISS/pgvector), retrieval, citations, and sources of truth.

  • Models & inference: TensorFlow/PyTorch, ONNX, latency/cost optimization, batching & caching.

  • Data pipelines: ETL/ELT, document pipelines, OCR, extracting structure from PDFs and forms.

  • Security & compliance: RBAC/ABAC, anonymization, encryption, audit, GDPR/NIS2 alignment.

  • Operations: CI/CD, observability, feature flags, canary and rollback policies.

Use cases

  • AI knowledge base: Natural-language questions over internal documents with references.

  • Document processing: Key-field extraction, classification, routing of submissions and contracts.

  • Assisted decisioning: Predictions and recommendations in CRM/ERP, scoring and task prioritization.

  • Voice & chat interfaces: Omnichannel assistants for internal teams and customers.

Client benefits

  • Faster decisions: Relevant insights and recommendations in the context of your data.

  • Less manual work: Automation of document handling and routine tasks.

  • Higher quality: Consistent outputs, auditable results, and traceability.

  • Scalability: Ready for growth in users, data, and functionality.

Our process

We identify the highest-impact use cases and data availability. We set KPIs, risks, security and integration requirements, and plan the pilot and measurement.

We build document channels, metadata extraction, embeddings and vector indices. We enforce access control, versioning, and sources of truth for reliable answers.

We integrate and optimize models (NLP, CV, predictions) for latency, accuracy, and cost. We build stable API layers, caching, hallucination-detection and fallbacks.

We connect AI to your systems (CRM/ERP/DMS) and build interfaces (web, mobile, chat/voice). We implement access policies, audit, and user-success metrics.

We measure accuracy, latency, user satisfaction, and ROI. We enable feedback loops and continuously improve prompts, retrieval, and models for stable performance.

Partnerships & ecosystem

We connect academic know-how with practice. We leverage modern AI libraries, vector databases, and cloud services. We collaborate with internal teams to integrate AI securely into existing processes and tools.

Publications & innovation

Our white-paper topics: RAG architectures in enterprise, answer-quality evaluation, AI service governance, and security patterns for intelligent agents in regulated industries.

FAQ

Frequently asked questions

It depends on the use case. For RAG, a high-quality document corpus is enough; for predictive models, historical data helps. We start with a pilot and validation.

We apply RBAC/ABAC, audit, and encryption. Retrieval respects access rights, and we log all queries and responses for control and traceability.

We minimize them through RAG, citations, confidence filters, and fallbacks. We implement answer-quality evaluation and regular fine-tuning/updates.

A KPI-driven pilot can be delivered in weeks. Production integration, security, and observability typically take a few months depending on scope.

Yes. We deploy both in cloud and on-prem. We handle network policies, secure storage, identities, and regulatory/audit requirements.