AI and data
Practical AI. Reliable data. Systems built for production.
From LLM-powered search and document intelligence to predictive models and analytics, the focus is on making AI useful beyond the demo. That means pairing the model layer with dependable data pipelines, well-structured datasets, and infrastructure that holds up under real workloads.
Capabilities
- LLM integrations and AI apps
- Semantic search and RAG
- Machine learning and prediction
- Data pipelines and orchestration
- Analytics and business intelligence
Technology stack
- Python
- OpenAI
- Anthropic Claude
- PyTorch
- dbt
- Snowflake
