Lev accelerates AI-powered pipelines with Matia for commercial real estate OS platform

Info

Location: New York, New York
Industry: Commercial Real Estate Tech
‍Products: Matia ETL, Matia Reverse ETL, Matia Observability‍
‍Use Cases: AI Pipelines, Data Ingestion/ETL, Data Activation

The data stack

ETL: Matia
Reverse ETL: Matia
Observability: Matia
Warehouse: Databricks
Transformation, dbt,
‍Connectors Used: PostgreSQL, MongoDB, HubSpot, Posthog, Sendgrid

Overview

Lev is building the operating system for commercial real estate financing. The platform connects brokers, borrowers, and lenders in a centralized, intelligent environment that acts as a commercial real estate operation system. At the heart of this experience is real-time data powering AI-driven recommendations.

To make their AI models actionable, Lev needed a pipeline infrastructure that could move data from Databricks to operational systems with speed, precision and confidence.

Challenge

Lev's platform depends on accurate borrower and deal data flowing continuously into Databricks, where machine learning models rank the best-fit lenders for each commercial real estate deal. As the business scaled, their data infrastructure started to show strain.

• Costs at their legacy ETL platform were unpredictable and growing exponentially
• Syncs from Databricks to external tools were too slow to support AI-powered product delivery
• Reverse ETL workflows were manually managed
• Engineering time was tied up debugging pipelines instead of optimizing models

On top of that, Lev was leveraging Serverless Databricks as part of their architecture, which, while efficient for scaling compute, added complexity to managing reliable, always-on data pipelines.

“Matia didn’t just help us move data; it made our AI workflows operational. We can now get model outputs from Databricks into our platform fast enough to make a difference for our customers.” - Alberto Sheinfeld, CTO, Lev

Solution

Lev adopted Matia to build and orchestrate the AI pipelines that power their platform from ingestion to observability, activation. Matia introduced Lev to dbt to be able to expedite model deployment. Together with Databricks and dbt, the team now has a modern data stack designed for agility and scale.

With Matia, the team consolidated their fragmented pipeline infrastructure and made reverse ETL seamless. Insights from Databricks and dbt models could now be synced to customer-facing tools in near real time.

• Sub 5-minute response times: Lev got white glove treatment from Matia. In the instances where there was development work needed or questions, the Matia team responded within 5 minutes and usually resolved any issues in less than 48 hours
• Reverse ETL with reliability: Instead of maintaining scripts to push data into back to PostgreSQL, Matia’s platform automated it all
• 5x faster syncs: By optimizing how data moved from Databricks and through dbt, Lev ensured brokers could act on AI insights without lag, seeing a 80% decrease in sync times
• Unified observability: Matia gave the team full visibility across pipeline stages, helping them scale without the usual complexity
  

Results

• 5x faster syncs from Databricks to operational systems
• Lower infrastructure costs on Databricks
• AI predictions deployed in real time to customer workflows
• Improved pipeline reliability across ingestion, transformation with dbt, and reverse ETL
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“The support from Matia has been incredible. We give feedback and see changes almost immediately. It feels like we’re co-building with their team.” - Alberto Sheinfeld, CTO, Lev

Looking Ahead

As Lev grows its footprint across commercial real estate, the need for trustworthy, scalable AI pipelines only increases. With Databricks, dbt, and Matia, their team has the tools to move fast, reduce maintenance, and let data drive every financing conversation.

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