Databricks' next-generation operational database turns the lakehouse into a real-time decision intelligence platform. MathCo leverages it to enable Always-On MMM — connecting live data to models, agents, and business decisions at enterprise scale.
Lakebase is Databricks' managed Postgres-compatible operational database, built natively into the lakehouse. MathCo's implementation unlocks three core enterprise capabilities.
The challenge isn't analytics — it's the absence of a persistent, scalable data and decision infrastructure that bridges the lakehouse and live applications.
MMM data, features, and outputs sit fragmented across pipelines. There is no unified, reusable serving layer — every team rebuilds the same plumbing from scratch.
Batch-oriented systems cannot support real-time queries, API-driven consumption, or agent state — locking enterprises out of in-flight decision making entirely.
Without standardized, governed data products, every new use case requires a full re-build — limiting enterprise-wide adoption and blocking meaningful scale.
MathCo implements Databricks' Lakebase as a five-layer platform that enables real-time, agentic, production-grade decision intelligence — deployable across industries and use cases.
Lakebase + Delta + Unity Catalog unify datasets, features, and metadata into a governed, reusable foundation — eliminating fragmented pipelines across domains.
HTAP-enabled Lakebase tables power real-time querying and fast feature access — turning your lakehouse into a live serving layer for models, agents, and APIs.
MLflow-powered lifecycle manages training, validation, versioning, and automated refresh — production-grade ML that stays current without manual intervention.
AgentBricks-powered agents handle scenario planning, optimization, and automated decision workflows — running directly on live Lakebase data with full traceability.
React frontends with FastAPI backends deliver dashboards, simulators, and embedded decision intelligence — making insights accessible to all business users.
Raw → Silver → Gold layers
Low-latency store · Embeddings · Metadata
Train · Validate · Deploy
Simulate · Optimize
Govern · Trace · Secure
QnA · Structured Data
React + FastAPI · Dashboards · Simulators · Co-pilots
MathCo's flagship implementation on Databricks Lakebase — transforming how CPG enterprises measure and optimize marketing ROI continuously, not retrospectively.
Traditional MMM runs quarterly or annually — too slow for today's fragmented media landscape. Databricks Lakebase enables an always-on MMM engine that continuously ingests data, refreshes models, and surfaces actionable insights without manual intervention.
Lakebase provides the persistent context layer that stores features, model outputs, and simulation state — making real-time scenario planning and budget optimization possible directly on live data.
Media spend, sales, promotions, pricing, and external signals unified into analytics-ready Delta tables with frequent refresh cycles.
MLflow automates training, validation, versioning, and model refresh — stable, reproducible models that stay current with market reality.
HTAP-powered what-if simulations evaluate alternative media mix strategies directly on live Lakebase data in real time.
Auto-generated narratives and recommendations translate complex model outputs into plain-language guidance for business users.
Workspace, Unity Catalog, Git integration, automated code quality
EDA, algorithm selection, model build via Databricks Notebooks
MLflow optimization, data validation, business UAT via dashboards
QA to production, Delta Tables, activation via SQL/APIs
Continuous monitoring, alerts, drift detection, recalibration
A fully integrated stack spanning data ingestion, ML model lifecycle, agentic intelligence, and business-facing applications — all governed by Unity Catalog and served through Lakebase.
Watch a full demo of MathCo's Always-On MMM solution built on Databricks Lakebase — real-time scenario simulation, GenAI-assisted insights, and the Lakebase-powered data layer.
Watch Demo Video →