The live context layer for agents and apps

Transform siloed data into up-to-the-second context, just using SQL

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Trusted by engineering leaders

Real-world context engineering

Why is it so hard to keep up with demands for fresh context?

OLTP Databases

Siloed and can't handle data-intensive queries.
Data Lakehouse

Lacks the freshness and cost-efficiency required for online services.
Do-it-yourself

Complex to operate, often requiring specialized talent.

The missing element in your AI architecture

Introducing Materialize

Operate confidently with live context.

Backed by the best to bring a breakthrough in incremental computation to the enterprise.

Integrate data from any source

Continually and incrementally ingest data from your databases, ERPs, CRMs, and other systems, unify it, and clean it for downstream consumption. Materialize grows more powerful as you connect more sources. Use our secure and scalable SaaS or keep everything air gapped on prem. Materialize separates storage from compute, scaling beyond local memory giving you economical processing for your most demanding operational workloads.

Use SQL to create real-time data products

Transform raw updates into live, canonical business objects that can be queried directly or pushed to downstream systems in real-time. Use Materialize to build a trustworthy, up-to-the-second digital twin of your business that streamlines agent and microservice development. Our groundbreaking incremental computation engine performs the minimal work to keep things up to date as updates happen, without destabilizing your operational databases. Any engineer who knows SQL can now launch a new data product or contextual building block for AI in minutes.

Rapidly deploy use cases from a live context graph

Link your real-time data products into a continuously updated context graph that agents and services can query directly. Offload complex queries from your MCP endpoints and APIs onto incrementally computed data products with single-digit millisecond latency. Keep vector embeddings fresh as source data changes, enabling RAG that's so fresh it's interactive. Every application and agent stays grounded in a trustworthy, up-to-the-second view of your business.

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Trusted by engineering and data teams

80%

reduction in costs for online feature store

54x

increase in loan eligibility checks

50ms

Feature lookups across 3 data sources for ML scoring

80%

reduction in costs for online feature store

54x

increase in loan eligibility checks

50ms

Feature lookups across 3 data sources for ML scoring

80%

reduction in costs for online feature store

54x

increase in loan eligibility checks

50ms

Feature lookups across 3 data sources for ML scoring

80%

reduction in costs for online feature store

54x

increase in loan eligibility checks

50ms

Feature lookups across 3 data sources for ML scoring

Support your most demanding AI initiatives with your existing team

Give agents real-time, contextual building blocks so they can discover and react to the data they need at scale. Link context with knowledge graphs so they know where to go next. Agent capabilities grow exponentially as new data products are added. Serve directly from Materialize or keep embeddings and search attributes up to date at a fraction of the cost.

Simplify vector search pipelines

Evolving your architecture

Integrate Materialize into your existing stack

Lambda Architecture

Get a quick win by adding Materialize as a speed layer alongside your batch-based systems. This avoids the costly transformations required to keep up with live data and lets you see the impact of actions that would otherwise be too complex to calculate reactively.

Kappa Architecture

Over time, use Materialize to create the authoritative representation of your business in the moment. Query Materialize directly while sending events downstream to power core processes or enable historical analysis.