The future of data isn't another dashboard — it's an intelligent, conversational interface powered by a robust semantic layer. We provide Data-Modeling-as-a-Service to help businesses bypass the traditional BI backlog and connect Large Language Models directly to a governed, single source of truth.
Book a MeetingToo much time and energy has been spent on governing data within Business Intelligence tools. This creates a bottleneck where access to data is locked behind long BI development cycles.
Getting a new dimensional breakdown requires a drawn-out process of back-and-forth ticketing with data analysts. Your team waits days or weeks for answers that should take seconds.
When your data modeling and metric definitions live entirely inside a BI tool, your LLMs can't natively access them. Your AI investment is disconnected from your business logic.
Stakeholders rarely need a complex dashboard — they just need the answer to a business question. Traditional BI forces every question through the same rigid visualization layer.
Instead of modeling data inside the BI layer, we move your business logic upstream into a universal Semantic Layer. By decoupling metrics from dashboards, we create a structured, well-governed environment where LLMs can safely and accurately query your data warehouse.
We leverage industry-leading tools like dbt and CredibleData to define your metrics as code — creating a single, machine-readable source of truth. The result: your AI gives the right answer, every time, using your organizational definitions.
Empower non-technical stakeholders to ask complex data questions in natural language — getting instant, accurate answers without writing SQL or waiting on an analyst.
Eliminate the endless feedback loop of dashboard design. Deliver flexible dimensional breakdowns instantly through conversational queries.
Stop worrying about LLM hallucinations. By routing AI through a semantic layer, the model only queries pre-approved, well-governed metrics.
Put the contents of your data warehouse directly into the hands of decision-makers. Break down silos, remove technical barriers, and dramatically increase data utilization across the enterprise.
We evaluate your current data warehouse architecture and identify a high-value domain to serve as the pilot. Together we define the core metrics, dimensions, and business logic required.
We build a robust semantic layer using dbt or CredibleData — defining your metrics as code in a single, governed source of truth.
We connect the semantic layer to an LLM interface. Instead of writing complex SQL against raw tables, the model uses the semantic layer's API to pull governed metrics instantly.
We rigorously test the conversational output for accuracy and usability with your stakeholders. Once validated, we iterate to bring in more data domains and scale your AI capabilities.
Stop solving data problems with more dashboards. Give stakeholders the power to converse directly with a governed, accurate, and scalable data model.
Book a Meeting