Trusted by market leaders in Uzbekistan
Building and deploying secure AI services on our own infrastructure. From intelligent legal assistants to speech analytics systems and LLM-based process automation.
Trusted by market leaders in Uzbekistan
Voice bots for public service call centers. Document OCR at service centers. AI assistants in Uzbek and Russian for tax, interior, and finance ministries.
Answers to questions on Central Bank financial documents and procurement regulations. Speech analytics for bank call centers.
Embed AI capabilities into any application via REST API. One contract, one key — no ML engineering team required.
Instant answers on local legislation, Central Bank financial documents, and procurement regulations in Russian and Uzbek.
Access to various generative models through a single API and one service agreement with automatic fallback to on-prem models.
Audio message transcription, sentiment analysis, and real-time monitoring of sensitive inquiries on social media and email.
Speech synthesis for automating outbound calls and building full-fledged digital contact centers.
| Component | Technology | Purpose |
|---|---|---|
| RAG Technologies | FAISS, Qdrant (vector DBs) | Answer accuracy without fine-tuning models |
| Data Processing | Apache Airflow + connectors (Confluence, files) | Data update pipelines and quality control |
| Censor Service | Built-in filtering and banning | Quick fix for incorrect responses |
| Analytics | Apache SuperSet dashboards | MAU, Retention Rate, inquiry sentiment metrics |
| GPU Resources | Own GPU servers in Uzbekistan | Model inference and training — data never leaves the country |
| Sovereign Storage | Role-based model + data masking | Audit-ready reporting for personal data protection |
We use RAG (Retrieval-Augmented Generation) technology, which allows the model to access an up-to-date external knowledge base (regulatory documents, financial records) in real time. Data updates are handled through automated pipelines built on Apache Airflow.
Yes, the platform architecture supports working with on-premises models (Phase 1) and using sovereign data storage. This eliminates the transfer of sensitive corporate information to external cloud services.
For the PoC phase (AI agent), the minimum requirements are 4 CPU, 16 GB RAM, and 40 GB SSD, plus GPU availability to ensure high-speed response generation.
Yes, text and speech recognition and generation are implemented in both Russian and Uzbek. We pay special attention to translation accuracy and model performance with local specifics.
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