Assess
- AI readiness & use case discovery workshops
- Data maturity assessments
- AI governance & responsible AI gap assessments
Design
- Responsible AI frameworks & governance models
- LLM & agent solution design
- AI observability blueprints (bias, drift, explainability)
Build
- AI/LLM integration into enterprise systems
- Agent development (workflow automation, copilots)
- ML model development & fine-tuning
Deploy
- AI deployment pipelines (SageMaker, Vertex AI, Azure ML)
- Conversational AI/LLM deployment into production
- AI workflow integration across enterprise apps
Automate
- AI-driven automation & AIOps
- MLOps pipelines (CI/CD for models, retraining automation)
- AI lifecycle automation (monitoring, retraining, versioning)
Manage
- AI/LLM Ops-as-a-Service (usage monitoring, drift mgmt)
- Model governance & compliance mgmt
- AI platform operations & monitoring
Modernize
- AI modernization (chatbots → enterprise AI ecosystems)
- Model consolidation & optimization (reduce cost/latency)
- Next-gen AI platform adoption (agentic AI, orchestration frameworks)
End-of-Life
- AI/ML model decommissioning & archival
- Data retention and regulatory alignment for AI models