Your AI team has transformative ideas. Leadership approved the budget. Then reality: preparing data for AI means months of cleaning and formatting. Data scientists become data wranglers. Engineers build pipelines instead of AI features. By the time data is ready, your competitor already shipped.
The problem isn’t the models. It’s how long data prep takes. Your RAG pipeline needs documentation from three systems, each in different formats. Traditional pipelines force sequential work: Spend three months prepping data, then try the AI experiment. Want different features for training? Rebuild everything from scratch. You can’t scale AI on a data platform built for dashboards.
Broadlume, a Cyncly company, went from 6-month data projects to 2-week delivery using Matterbeam. Here’s what changed:
Matterbeam is your data layer built for AI velocity. Stop waiting on data. Every dataset is live, replayable, transformable, and ready to feed any AI experiment or model instantly.
Like Kafka — but for the AI era. Kafka streams raw bytes; Matterbeam understands schema, lineage, and transformations. That means your AI models get structured, traceable data — not just a firehose of unformatted messages. You can replay anything instantly, with no clusters or pipeline rebuilds.
The Replayable Log captures data once in an immutable, org-wide event log that includes unlimited storage. Connect sources, such as Salesforce, MySQL, and Postgres, and data flows immediately with automatic schema detection.
The Unified Stream feeds LLMs, RAG, and analytics simultaneously from one immutable source. Zero duplication or brittle point-to-point jobs. Point-and-click emitters shape data for JSON, Parquet, vectors, or tables. Stream to Pinecone for semantic search, Snowflake for analytics, your ML platform for training. All from the same source.
The Iteration Engine transforms for your specific needs. Change schema or features and replay data with time-travel access. Test small datasets across multiple models, instantly promote the best to production. When your data scientist needs Q3 data with new features, the answer is “replay it in minutes.”
“We literally changed our company strategy based on what we can do with Matterbeam,” says Josh Pendergrass, VP Engineering at Broadlume, a Cyncly company. Before Matterbeam, they accepted that data projects took months or years. Now data is suddenly available everywhere they need it, transformed however they want.
Data scientists access datasets directly instead of filing tickets. Engineering ships AI features instead of maintaining pipeline graveyards. The AI team ships models, not tickets.
We guarantee your AI data readiness. If your AI experiments aren’t running faster in the first 60 days, we refund 100%. Talk to a Matterbeam engineer >
