Copilot for Data Teams
An AI "no lock-in" solution, supporting your existing Analytics tooling across all types of datasets. A language and tool agnostic solution to speed up your Data development efforts.
An AI "no lock-in" solution, supporting your existing Analytics tooling across all types of datasets. A language and tool agnostic solution to speed up your Data development efforts.
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 an analytics professional, you know the challenges: complex data models, intricate transformations, and the constant pressure to deliver insights faster. 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 is 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 with modern data stack tools. Describe your data transformation needs in plain language, and we'll generate battle-tested code that follows best practices.
For analytics engineers, this means faster development of modular dbt and Looker models. For analysts, it's the power to build complex transformations without getting lost in implementation details.
We're not replacing the "analytics as code" movement – 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.
Built by data people, for data people.
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.