Databricks architecture, Lakeflow, Unity Catalog, Databricks SQL, MLflow, Agent Bricks, Lakebase, custom apps, migration, optimization, and production operations.
Databricks delivery systemCORE SPECIALTY
BI+MLLAKEFLOWUNITY CATALOGAGENT BRICKSLAKEBASE
Data IntelligenceAI/BIMLflowApps + Serving
Architecture through operations
One accountable lifecycle for the Databricks Data Intelligence Platform.
Innovative BI designs Databricks account, workspace, catalog, storage, compute, network, identity, and deployment patterns for AWS and Azure. Architecture addresses environment isolation, private connectivity, customer-managed keys where required, workload identities, secrets, serverless and classic compute choices, policy controls, audit logging, disaster recovery, and infrastructure as code.
We carry that foundation into Lakeflow ingestion and orchestration, open Delta and Iceberg data products, Unity Catalog governance, Databricks SQL and AI/BI, MLflow model and agent lifecycles, Agent Bricks, Genie One, AI Search, Unity Gateway, Model Serving, Databricks Apps, Lakebase-backed operational state, CI/CD, OpenTelemetry-aligned observability, performance engineering, FinOps, and sustained platform operations.
Federal and Commercial delivery
Two operating contexts. One deep technical specialty.
Every engagement is shaped around the customer’s security boundary, regulatory obligations, cloud estate, delivery model, data sensitivity, and measurable business or mission outcome.
FED
Federal mission solutions
AWS GovCloud, Azure Government, commercial-cloud, and authorization-boundary architecture as applicable
Identity, least privilege, private networking, encryption, logging, and Zero Trust-aligned patterns
Control mapping, FedRAMP package inheritance inputs, audit evidence, and agency authorization support
Data lineage, stewardship, quality, retention, records, and governed AI and ML workflows
Production readiness, continuity, knowledge transfer, and L1–L3 operational support
COM
Commercial data, AI & ML modernization
Enterprise lakehouse and data-intelligence strategy tied to value and operating metrics
ERP, CRM, SaaS, database, file, event-stream, and partner-data integration
Customer, finance, supply-chain, procurement, sustainability, and operational data products
AI/ML products, RAG applications, decision intelligence, and workflow activation
Platform adoption, cost allocation, performance optimization, reliability, and managed services
Government-cloud services, models, regions, authorization scope, impact levels, and feature maturity are validated for the specific agency environment before architecture commitments are made. A platform authorization does not authorize a customer implementation.
Databricks solution portfolio
Engineering across the complete platform lifecycle.
ARC
Platform architecture & foundation
Account and workspace topology, Unity Catalog metastores, identity federation, private connectivity, customer-managed keys, compute policies, environment isolation, infrastructure as code, compliance configuration, and recovery design.
MIG
Migration & modernization
Dependency discovery, workload rationalization, code conversion, governance migration, reconciliation, parallel run, cutover, and retirement for warehouses, Hadoop, Spark, ETL, BI, and ML estates.
LFW
Lakeflow data engineering
Lakeflow Connect, Jobs, and declarative pipelines; incremental ingestion, CDC, batch and streaming, expectations, materialized views, catalog commits, and event-log observability.
UC
Unity Catalog governance
Catalog design, least privilege, cross-engine ABAC, row filters, column masks, classification, lineage, Delta Sharing, governed functions, auditability, and cross-workspace data, model, service, and AI assets.
AGT
AI, ML & agent engineering
Agent Bricks, Genie One, AI Search, Unity Gateway, MLflow evaluation and OpenTelemetry-format tracing, Models in Unity Catalog, Model Serving, RAG, governed tools, guardrails, drift, and human review.
APP
Apps & operational intelligence
Databricks Apps, including scalable application patterns where supported, and Lakebase-backed Python or Node.js solutions for operational dashboards, governed assistants, review queues, approvals, workflows, and embedded data products.
Application & agent engineering
Turn governed data, AI, and ML into applications people can trust.
Solutions connect Databricks SQL, Unity Catalog-governed data and functions, Model Serving, Lakebase, OAuth, APIs, enterprise systems, and human approval workflows without creating another disconnected data stack.
01
Discover
Define users, decisions, data products, workflow states, security roles, latency, availability, risk, and adoption measures.
02
Engineer
Build Python or Node.js services, responsive interfaces, governed retrieval and tools, durable application state, automated tests, and reusable components.
03
Deploy
Package configuration and dependencies, automate CI/CD with Declarative Automation Bundles, promote across environments, and validate identity and access.
04
Evaluate & operate
Monitor application telemetry, audit events, model and agent quality, traces, latency, cost, incidents, releases, feedback, and service objectives.
Migration factory
Move workloads with traceability, validation, and controlled cutover.
Migration patterns are selected after discovery; tools and sequencing vary by source platform, scale, latency, security, data-retention, and business-continuity requirements.
Execute schema, data, code, pipeline, model, and governance migration with reconciliation, performance baselines, security tests, and business validation.
04
Cut over & stabilize
Coordinate dual run, release readiness, change management, production cutover, hypercare, optimization, knowledge transfer, and legacy retirement.
Databricks support services
Keep the platform reliable, governed, efficient, and ready for change.
Support spans platform administration, DataOps, MLOps/LLMOps, AgentOps, application operations, SRE practices, service management, and continuous improvement.
