Databricks + Caelus: Lakehouse to Production AI
Unified value framing, feature engineering, governed MLOps and GenAI orchestration accelerating time‑to‑impact on Databricks.
Architecture & Execution Pillars
Composable pillars drive predictable delivery and compounding platform leverage.
Lakehouse Foundations
Delta architecture, medallion modeling & governance controls.
Feature & Vector Stores
Reusable feature pipelines, embedding generation & catalog integration.
GenAI & LLM Ops
RAG patterns, evaluation harness, deployment orchestration & monitoring.
Governed MLOps
CI/CD pipelines, model registry promotion, bias & drift checks.
Cost & Performance
Cluster right‑sizing, photon acceleration & workload governance dashboards.
Adoption & Enablement
Playbooks, workshops & co‑delivery capability uplift.
Databricks Lakehouse & GenAI Blueprint
Blueprint aligning ingestion, feature / vector management, ML/LLM lifecycle and observability with governance & cost telemetry.
- Delta ingestion & medallion zone data quality contracts
- Feature & embedding pipelines with registry reuse
- RAG orchestration & evaluation harness
- Model CI/CD pipelines & governance checks
- Observability: lineage, performance & cost analytics
Reusable Assets & Tooling
Shrink lead time from ideation to production while embedding governance.
Value Sprint Playbook
2–4 week framing: value model, architecture slice, KPI baseline.
GenAI RAG Starter
Ingestion, embeddings, retrieval adapters & evaluation harness.
MLOps Pipeline Templates
CI/CD + quality gates, bias checks, drift detection & promotion workflows.
Impact Benchmarks
Representative improvements from lakehouse modernization programs.
3
Faster Use Case Throughput
44
Governance Maturity Lift
26
Run-Rate Cost Reduction
500
Enterprise Clients
Launch a Databricks Value Sprint
Baseline maturity, prioritize use cases & design a sequenced 90‑day roadmap.