DML helps companies create data-driven applications by simplifying complex data infrastructure tasks. Our AI-powered platform speeds up development, letting your team focus on building rather than troubleshooting.
DML emerged from the innovative minds behind Looker (acquired by Google).
We're revolutionizing how data professionals interact with LLMs by providing a specialized middleware
that understands the nuances of data work.
As product builders, we always had the challenge for building reliable data consumer applications: complex data models,
intricate transformations, vendor lock-in, errors from manually written data pipelines. While general AI solutions promise to help,
they often fall short when dealing with real-world data complexities – we've proven this through extensive benchmarking (check out our Benchmark App).
Our platform was built specifically for data work, using context-aware code generation that understands:
Instead of generating isolated snippets, DML creates complete, production-ready codebases that integrate seamlessly into either the rest of the existing data stack,
OR as part of the new AI app (specificially, with a custom RAG or fine-tuned Model).
Focus on describing your data transformation needs in plain language, and we'll generate battle-tested code that follows best practices.
For engineers, this means faster development of modular data models. For product managers, it's the power to build complex data-rich apps without getting lost in implementation details.
We're not replacing "anyone's ability to code" – we're amplifying it. By making code generation intelligent and context-aware, we're enabling data teams to focus on strategy while delivering results 10x faster.
During the last decade as an industry we've pushed companies to adopt "Data Driven Cultures" by giving everyone access to Analytics tools. This, however, rarely worked well in practice. Not everyone is suited to work with Data - to make inferences and logical conclusions. We understand this and want to focus on people who are actually good with Data: people with analytical, technical, and science backgrounds.
Traditionally a Data Role is viewed as a profession of lone geniuses. We believe that whether you are a genius or not is irrelevant to how much all of us can benefit from collaborating on projects together. Open source communities are a prime example of this.