Technology Areas
Nine practice areas, from generative AI and retrieval to MLOps and responsible AI.
Model-agnostic and cloud-agnostic by design. The stack follows the problem, not a partnership agreement.
Generative AI
LLMs, RAG, embeddings, fine-tuning, and applications built on them.
AI Agents
Agentic AI, autonomous workflows, and multi-agent systems with guardrails.
Machine Learning
Predictive analytics, classification, and recommendation systems.
NLP
Text analysis, language applications, and conversational AI.
Computer Vision
Image analysis, video analysis, inspection, and visual AI.
AI Automation
Business workflow and process automation, document to decision.
MLOps
Model deployment, monitoring, evaluation, CI/CD, and AI infrastructure.
AI Architecture
Enterprise AI architecture and end-to-end solution design.
Responsible AI
Governance, risk, security, privacy, and systematic evaluation.
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