Solutions range from entity recognition and sentiment analysis to complex document understanding and conversational AI, always optimized for specific domains.
Classical NLP expertise
LLM applications
CV systems extract actionable insights by combining traditional CV techniques with modern vision-language models. Applications span precise object detection, OCR for document processing, and advanced VLMs that understand visual context in relation to text.
Object detection & semantic segmentation
OCR & document analysis
VLMs
Pioneering research in this underexplored modality has produced new better architectures for stem separation and audio-to-MIDI conversion. Proprietary models for music separation, speech understanding, and audio analysis match or exceed commercial solutions while opening new creative possibilities.
Speech understanding
AI for music
Most business-critical data lives in tables. For research, the most useful data is the one that is well-organized and well-documented. Beyond analysis, we research how sensitive tabular data can be safely shared without re-identification risk.
Classical ML models
Compliance-ready anonymization
Deep learning for tabular data
Privacy-preserving data sharing
Enterprise data is locked behind SQL queries and fragmented across systems. We build natural language interfaces that unify federated sources, use knowledge graphs for semantic understanding, and deploy specialized LLMs that return precise answers, not hallucinations.
NL2SQL
Federated data sources
Ad-hoc reports
Database semantics, joins, query optimization
Graph-based approaches reveal hidden connections that traditional methods miss, enabling AI systems to reason about context, dependencies, and influence patterns.
Knowledge graphs for semantic reasoning
Social and organizational network analysis
Entity resolution and link prediction
ML Engineers
Our ML engineers combine research expertise with production engineering, developing novel architectures, publishing findings, and transforming cutting-edge papers into scalable systems that run on distributed GPU clusters.
AI Inference Engineers
Specializing in both inference optimization research and deployment, our team advances the state-of-the-art in model compression techniques while ensuring production models run efficiently across our GPU infrastructure, edge devices, and cloud platforms.
