Cake for Analytics with GenAI
Supercharge dashboards, reports, and data exploration with generative AI. Use LLMs to summarize, interpret, and explain data—all on top of your existing analytics stack, deployed through Cake’s open-source infrastructure.







Deliver faster insights with LLM-powered analytics and natural language interfaces
Data teams are buried in dashboards, but most business users still struggle to get answers. Generative AI changes that by letting users ask questions in plain language, receive natural-language summaries, and surface insights without needing to touch SQL or read through dozens of charts.
Cake provides a modular stack to bring GenAI into your analytics workflows. You can ingest and preprocess data with DBT or AirByte, orchestrate pipelines with Kubeflow, and layer in LLMs using LangChain or Pipecat to interpret or generate explanations. Whether you’re building chat interfaces on top of a warehouse or injecting AI summaries into reports, Cake makes it secure, scalable, and fast to deploy.
And because it’s open-source and cloud agnostic, you can plug GenAI into your existing tools without rebuilding your stack, while reducing costs and staying in control of sensitive business data.
Key benefits
- Accelerate time to insight: Let users ask questions and explore data without writing queries.
- Integrate with existing analytics tools: Enhance dashboards, reports, and notebooks without starting over.
- Cut costs and complexity: Replace third-party AI add-ons with open-source, composable infrastructure.
- Deploy anywhere: Run on top of your current stack—in your cloud, behind your firewall, or at the edge.
- Ensure trust and compliance: Control data access, audit responses, and log AI-generated outputs.
Common use cases
Teams use Cake’s GenAI analytics capabilities to simplify data exploration and reporting:
AI-powered dashboards
Embed LLMs that explain charts, flag anomalies, or answer follow-up questions directly in existing dashboards.
Chat with your data
Create secure interfaces that let internal teams query Snowflake, BigQuery, or S3 data via natural language.
Automated reporting
Generate weekly updates, summaries, or narrative insights automatically from data pipelines or notebooks.
Components
- LLM orchestration: LangChain, Pipecat
- Models: Open-source LLMs (e.g., Llama 3, Mixtral), Hugging Face
- Data integration: AirByte, DBT
- Storage & warehouse: Snowflake, AWS S3, Delta Lake
- Monitoring & observability: Prometheus, Grafana
- Workflow orchestration: Kubeflow Pipelines
- Frontend frameworks: Superset, Jupyter, Streamlit
"Our partnership with Cake has been a clear strategic choice – we're achieving the impact of two to three technical hires with the equivalent investment of half an FTE."

Scott Stafford
Chief Enterprise Architect at Ping
"With Cake we are conservatively saving at least half a million dollars purely on headcount."
CEO
InsureTech Company