For years, executives and data teams have been trapped in the same cycle: asking for a new chart, waiting days (or weeks) for someone to build it, and finally facing static dashboards that show what happened—but not why, or what to do next.
Calliope wants to break that cycle.
Its mission is clear: to change the way organizations understand and use their data.
Instead of offering more dashboards, Calliope is building the analytical brain of the enterprise—a platform that combines a copy-free lakehouse, semantic intelligence, and analytical agents so that data can explain itself, detect anomalies, and recommend actions.
From Dashboards to Dialogue
The new generation of leaders doesn’t want to stare at charts—they want to understand what’s happening. Calliope was created to make that leap: to transform data into an intelligent, contextual, and actionable conversation. While traditional tools are limited to visualization, Calliope interprets.
It understands the relationships between metrics, tables, and business processes, and it can respond in natural language to questions such as:
“Why have sales dropped in the southern region?”
“Which products are driving margin growth in the last quarter?”
It does so through an architectural design very different from any traditional BI platform.
An Architecture Designed for Immediacy
At the heart of Calliope lies a single principle: never move data unnecessarily.
Zero-ETL Extraction:
Calliope’s agents connect to data sources through standard connectors, extracting information without modification and synchronizing it in open formats stored in the cloud.Semantic Lakehouse:
On top of these files, Calliope builds a lakehouse that enables direct analysis—without transformation pipelines or data duplication (Zero-Copy).
This lakehouse adds transactional consistency, governance, and performance over raw data.Parallel and Optimized Execution:
The compute engine runs queries directly on the data, leveraging parallel processing and the ability to scale horizontally when the analysis volume or complexity increases.
This approach preserves the efficiency of a lightweight environment while providing the flexibility to handle large-scale analytical workloads.Semantic RAG:
Calliope maintains a knowledge graph that stores tables, relationships, and client-specific business rules.
This graph serves as the foundation for understanding the meaning of each metric and ensures that every query retrieves information from the correct source.
Orpheus: The Semantic Engine
Above the lakehouse lives Orpheus, the component that gives everything meaning. Orpheus translates natural-language questions into optimized SQL—and, more importantly, it understands the semantic context behind each query.
It knows that “sales” refers to a specific metric, that “region” is a hierarchical dimension, and that “last quarter” has a temporal interpretation within the customer’s business model.
But Orpheus doesn’t stop at query execution:
It generates automatic explanations of dashboards, either as summaries or complementary reports.
It applies knowledge from the RAG and validated examples to ensure accuracy and consistency.
It will soon integrate semantic security validations (RLS) to guarantee that every query respects user permissions from the start.
In other words, Orpheus turns data into understandable knowledge.
Coordinated Analytical Agents
Calliope is not a single model but a system of specialized agents orchestrated by a central coordinator in the analytics layer. Each agent has a specific purpose:
Analyze data.
Create dynamic charts.
Detect insights or anomalies.
Generate executive summaries.
The coordinator decides which agent—and which language model—to use depending on task complexity.
Calliope is LLM-agnostic: it can seamlessly combine models from OpenAI, Anthropic, Gemini, or Groq, always selecting the most efficient and accurate option for each case.
A simple query can be handled by a lightweight model, while a complex analysis or executive explanation can rely on frontier models such as GPT-5 or Claude.
The result: speed, precision, and cost control within a hybrid, multi-model environment.
Semantic Security and Governance
In corporate environments, security cannot be an afterthought—it must be part of the reasoning process itself. Calliope is integrating Row-Level Security (RLS) directly into its architecture. Initially applied at the table level, the goal is to evolve toward semantic security, where Orpheus understands user permissions and automatically adapts both queries and responses.
This will allow, for instance, a regional manager to see only the information for their area even if the query doesn’t specify it, or a financial analyst to access aggregated metrics without exposure to sensitive data.
The Calliope Difference
Calliope doesn’t compete with Power BI or Looker. It competes with the way we think about data analysis itself.
While traditional tools depend on pipelines, transformations, and manual maintenance, Calliope offers:
Zero-ETL, Zero-Copy: data analyzed where it resides.
Semantic Intelligence: data that explains itself.
Specialized Agents: automated analysis, insights, and recommendations.
Integrated Security: context and permissions built into reasoning.
Real Speed: from question to action in seconds.
Calliope doesn’t just display data—it transforms it into living, contextual, and useful intelligence.
Toward the Analytical Brain of Organizations
The future of analytics isn’t about more dashboards. It’s about systems that can reason over data, understand context, and propose actions.
That’s what Calliope is building: a platform where data no longer needs human interpretation, because it explains itself, updates itself, and adapts to the business.
Calliope doesn’t replace anyone.It connects people with the true potential of their data.
It empowers data teams with an intelligent semantic layer,and gives executives the ability to understand and decide without waiting for endless processes.
In short, Calliope turns business knowledge into action.
For years, executives and data teams have been trapped in the same cycle: asking for a new chart, waiting days (or weeks) for someone to build it, and finally facing static dashboards that show what happened—but not why, or what to do next.
Calliope wants to break that cycle.
Its mission is clear: to change the way organizations understand and use their data.
Instead of offering more dashboards, Calliope is building the analytical brain of the enterprise—a platform that combines a copy-free lakehouse, semantic intelligence, and analytical agents so that data can explain itself, detect anomalies, and recommend actions.
From Dashboards to Dialogue
The new generation of leaders doesn’t want to stare at charts—they want to understand what’s happening. Calliope was created to make that leap: to transform data into an intelligent, contextual, and actionable conversation. While traditional tools are limited to visualization, Calliope interprets.
It understands the relationships between metrics, tables, and business processes, and it can respond in natural language to questions such as:
“Why have sales dropped in the southern region?”
“Which products are driving margin growth in the last quarter?”
It does so through an architectural design very different from any traditional BI platform.
An Architecture Designed for Immediacy
At the heart of Calliope lies a single principle: never move data unnecessarily.
Zero-ETL Extraction:
Calliope’s agents connect to data sources through standard connectors, extracting information without modification and synchronizing it in open formats stored in the cloud.Semantic Lakehouse:
On top of these files, Calliope builds a lakehouse that enables direct analysis—without transformation pipelines or data duplication (Zero-Copy).
This lakehouse adds transactional consistency, governance, and performance over raw data.Parallel and Optimized Execution:
The compute engine runs queries directly on the data, leveraging parallel processing and the ability to scale horizontally when the analysis volume or complexity increases.
This approach preserves the efficiency of a lightweight environment while providing the flexibility to handle large-scale analytical workloads.Semantic RAG:
Calliope maintains a knowledge graph that stores tables, relationships, and client-specific business rules.
This graph serves as the foundation for understanding the meaning of each metric and ensures that every query retrieves information from the correct source.
Orpheus: The Semantic Engine
Above the lakehouse lives Orpheus, the component that gives everything meaning. Orpheus translates natural-language questions into optimized SQL—and, more importantly, it understands the semantic context behind each query.
It knows that “sales” refers to a specific metric, that “region” is a hierarchical dimension, and that “last quarter” has a temporal interpretation within the customer’s business model.
But Orpheus doesn’t stop at query execution:
It generates automatic explanations of dashboards, either as summaries or complementary reports.
It applies knowledge from the RAG and validated examples to ensure accuracy and consistency.
It will soon integrate semantic security validations (RLS) to guarantee that every query respects user permissions from the start.
In other words, Orpheus turns data into understandable knowledge.
Coordinated Analytical Agents
Calliope is not a single model but a system of specialized agents orchestrated by a central coordinator in the analytics layer. Each agent has a specific purpose:
Analyze data.
Create dynamic charts.
Detect insights or anomalies.
Generate executive summaries.
The coordinator decides which agent—and which language model—to use depending on task complexity.
Calliope is LLM-agnostic: it can seamlessly combine models from OpenAI, Anthropic, Gemini, or Groq, always selecting the most efficient and accurate option for each case.
A simple query can be handled by a lightweight model, while a complex analysis or executive explanation can rely on frontier models such as GPT-5 or Claude.
The result: speed, precision, and cost control within a hybrid, multi-model environment.
Semantic Security and Governance
In corporate environments, security cannot be an afterthought—it must be part of the reasoning process itself. Calliope is integrating Row-Level Security (RLS) directly into its architecture. Initially applied at the table level, the goal is to evolve toward semantic security, where Orpheus understands user permissions and automatically adapts both queries and responses.
This will allow, for instance, a regional manager to see only the information for their area even if the query doesn’t specify it, or a financial analyst to access aggregated metrics without exposure to sensitive data.
The Calliope Difference
Calliope doesn’t compete with Power BI or Looker. It competes with the way we think about data analysis itself.
While traditional tools depend on pipelines, transformations, and manual maintenance, Calliope offers:
Zero-ETL, Zero-Copy: data analyzed where it resides.
Semantic Intelligence: data that explains itself.
Specialized Agents: automated analysis, insights, and recommendations.
Integrated Security: context and permissions built into reasoning.
Real Speed: from question to action in seconds.
Calliope doesn’t just display data—it transforms it into living, contextual, and useful intelligence.
Toward the Analytical Brain of Organizations
The future of analytics isn’t about more dashboards. It’s about systems that can reason over data, understand context, and propose actions.
That’s what Calliope is building: a platform where data no longer needs human interpretation, because it explains itself, updates itself, and adapts to the business.
Calliope doesn’t replace anyone.It connects people with the true potential of their data.
It empowers data teams with an intelligent semantic layer,and gives executives the ability to understand and decide without waiting for endless processes.
In short, Calliope turns business knowledge into action.
