Technology that creates real value

Applications built on large language models — grounded in your data, evaluated against your tasks, and designed with guardrails.

• Retrieval-augmented generation (RAG) and semantic search
• Agentic workflows with tool use and human oversight
• Fine-tuning and prompt optimization where it adds value
• Evaluation harnesses, tracing, and guardrails
• Commercial and open-weight model deployment

Cloud-native infrastructure that is reproducible, observable, and cost-aware — so teams can ship frequently and safely.

• AWS and Microsoft Azure architectures
• Docker, Kubernetes, and serverless platforms
• Infrastructure as code with Terraform
• CI/CD pipelines and automated testing
• Monitoring, logging, and cost management

Data foundations that analytics and AI can trust — with quality checks, lineage, and governance built in.

• Batch and streaming data pipelines
• Warehouse and lakehouse platforms
• Machine learning model development and deployment
• Business intelligence and semantic layers
• Vector databases and embedding pipelines

Security and responsible-AI practices applied throughout design and delivery, aligned with the requirements your organization must meet.

• Secure-by-design architecture and threat modeling
• Identity, access control, and secrets management
• Data privacy, minimization, and retention controls
• AI governance, transparency, and human oversight
• Audit logging and documentation support