The Infrastructure for Intelligible AI
Data
Components
AI systems
Connect
Bring in your data from files, databases, or warehouses.
Components
Intelligible automatically extracts structured facts and relationships from your data and institutional knowledge.
AI Reasoning
Use components to ground and improve AI system outputs.
Go from data to
Intelligible works
01
Connect your data.
Use Intelligible Summand's visual interface to easily pull in your data -- no matter if it lives as messy CSVs or XLSX exports, or clean hyperscalar resources.
02
Components generation
Intelligible automatically generates components that make your data interpretable, explainable, and ready for AI. You can now use an AI interface that understands your data.
04
Reason with
your components:
your components:
When you ask a question, the model reasons over components instead of raw data.This gives you: more consistent answers, clearer explanations, reduced token usage. In Summand, you can see this directly through the chat interface.
03
Build structured context:
Behind the scenes, components are translated into natural language statements that preserve their structure.This creates a compact context that can be passed into standard LLM APIs.
05
Reuse across
workflows:
workflows:
Components are persistent and reusable.They can be used across queries, applications, and AI systems. This turns one-time analysis into reusable infrastructure.
Why
This Works
LLMs are good at reasoning over language, but not at parsing raw tables. Components translate structured data into a form that AI models can reason over efficiently, while preserving the underlying data relationships
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