Your data layer built for AI velocity.
Stop waiting on data. With Matterbeam, every dataset is live, replayable, transformable, and ready to feed any AI experiment or model instantly.
Like Kafka – but for the AI era
AI needs more than a message bus. Kafka streams raw bytes; Matterbeam understands schema, lineage, and transformations. You can replay anything instantly, with no clusters or pipeline rebuilds.
How Matterbeam Goes Beyond Kafka
The Replayable Log
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The Unified Stream
The Iteration Engine
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The Matterbeam Difference
Kafka moves messages. Matterbeam makes data AI-ready — live, historical, shaped, and replayable, without pipelines or clusters.
These teams accelerated their AI roadmap with Matterbeam
Don’t just take our word for it.
"We literally changed our company strategy based on what we can do with Matterbeam."
Before Matterbeam, Cyncly accepted that data projects took months or years. Then they saw data suddenly available everywhere they needed it, transformed however they wanted. Now they ask "can we use Matterbeam for this?" before every new project.
"Matterbeam isn't just about moving data—it's about transforming how we think about workflows."
Promoboxx will ship AI experiments weekly, not quarterly. They'll spend their time building intelligence instead of pipelines.
"Matterbeam made complex data integration simple."
The platform provided a robust, central data foundation that reduces development overhead, enables agile changes, and improves developer throughput by removing system complexities.
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Connect any source to any AI destination
If it holds data, Matterbeam can connect, shape, and emit it anywhere.
Amazon Redshift
Google Analytics
HubSpot
Kafka
MySQL
Pinecone
Salesforce
Shopify
Our AI Data Prep Guarantee
If your AI experiments aren’t running faster in the first 60 days, we refund 100%.
Data migrations, now with an Undo button
Traditional migrations drag on because you cannot test without disrupting production. With Matterbeam, try, retry, and perfect each step before cutover. All from the same interface you use for AI workloads.
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Keep legacy and target in sync while you test. Diff results, fix issues, and switch when ready.
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Cut over by dataset or workload. Verify parity before switching consumers. Roll back instantly if needed.
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Replay from any point in history. Recover from errors, audit every record, and inspect transforms.
Collectors pull from any system. Emitters shape JSON, Parquet, vectors, or tables for any target.
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Frequently Asked Questions
How is Matterbeam different from traditional data pipelines?
Traditional pipelines are brittle, one-directional, and purpose-built. If you need data for a new report, AI model, or dashboard, you’re starting from scratch. Each pipeline is a separate engineering project.
Matterbeam flips this. Your data flows into immutable datasets once. From there, you can:
- Add new transforms or emitters without touching the source
- Replay historical data through new logic
- Time travel to any point in your data history
- Spin up new use cases in minutes, not months
Can Matterbeam help with our AI initiatives?
Absolutely. This is where we shine.
Most AI projects fail because teams can’t access the data they need when they need it. Getting historical data cleaned and prepared takes months. By the time data is ready, the project timeline is blown.
With Matterbeam:
- Data scientists access datasets directly
- Time travel gives instant historical data for training
- Transforms let them experiment with features fast
- No waiting for data engineering sprints
One customer went from 6-month data projects to 2-week delivery using Matterbeam. The AI team ships models, not tickets.
What pain points and use cases does Matterbeam solve for?
AI/ML projects blocked by data access: Give data scientists instant access to clean historical data. Time travel to create training sets in hours instead of months. 95% of AI projects fail on data infrastructure, not models.
Data migrations and integrations: Collect from old and new systems into unified datasets. Replay historical data as you migrate. No temporary pipelines to throw away later.
Engineering backlogs measured in quarters: Every use case needs a new pipeline, so simple requests take months. Matterbeam collects once, use anywhere. Deliver in days.
Customer 360 views: Combine Salesforce, Stripe, support tickets, and product usage. Updates stream in real-time as data changes across systems.
Real-time analytics without infrastructure burden: Stream from production databases to warehouses without impacting performance. Keep dashboards fresh without batch delays or brittle pipelines.
Do I need to replace my existing data tools to use Matterbeam?
No, you don't need to replace anything. Matterbeam works alongside everything you have today – your data warehouse, BI tools, databases, and existing pipeline tools like Fivetran, Hevo, or Airbyte.
But once teams experience replay and transformation capabilities (replay historical data, transform on the fly, test without breaking production), they naturally phase out their point-to-point tools. These are capabilities traditional tools simply can't match.
Plus, Matterbeam is cheaper. Instead of paying for three Salesforce connectors to send data to three destinations, you pay for one collector and spin up unlimited emitters. No triple billing. Teams typically save 50-70% while gaining capabilities they never had before.
Start with Matterbeam alongside your current stack. Let the replay functionality and cost savings speak for themselves.
How can you make an AI Data Prep Guarantee?
Matterbeam’s streaming log makes every dataset replayable. That means you can change schemas, transformations, or logic and instantly rerun your data flows — no fragile pipelines, no rework. It’s how we turn what used to be weeks of prep into a few days of iteration, giving teams measurable results almost immediately.
Is there a free trial?
Contact us to discuss your needs. We work with design partners on custom arrangements that let you prove value before committing.