PyDough

Built for a few era of business intelligence

PyDough lets anyone ask questions in natural language and get structured, accurate answers. But unlike typical text-to-SQL tools, PyDough goes further: It's purpose-built to give users the power to understand their data, verify every step, and trust every result.

A formal but friendly DSL purpose-built for LLMs

PyDough introduces a Python-native Domain-Specific Language (DSL) designed to bridge the gap between natural language and executable logic.

Designed for LLMs: Bounded syntax reduces ambiguity, hallucination, and token bloat.

Readable for people: Clean, logical code that anyone can inspect and test.

Safe by default: All logic ties back to known semantics and rules.

Grounded execution: All logic ties back to known semantics and rules.

An LLM that understands your question and explains its answer

LLM interprets your question and generates PyDough code that’s easy to verify.

Every prompt, plan, and path is exposed and inspectable

Plans are translated into PyDough, not raw SQL, for easy verifiability by anyone

Enables human-in-the-loop verification before anything runs

A Knowledge Graph that grounds every response

All logic is grounded in a graph of business semantics.

Defines entities, relationships, metrics, and join rules

Resolves ambiguous terms with domain-specific context

Prevents overcounts and invalid joins using explicit data-aware structure

Gives both LLMs and humans a shared map of meaning.

An AI Ensemble that challenges itself

PyDough uses multiple LLMs in parallel to boost reliability

Models generate, review, and challenge each other’s logic

Conflicting interpretations are surfaced, explained, and ranked

Enables redundancy and self-correction — leading to higher fidelity answers

What makes PyDough different

Simple syntax with built-in guardrails

PyDough is clean, compact, and LLM-friendly—reducing token usage and complexity in query generation. It auto-enforces joins and relationships using metadata — blocking unsafe, slow, or invalid queries before they run.

Built for LLMs

PyDough’s custom interpreter gives agents smart, structured error messages — not just “syntax error.” Extendable plugins make debugging and self-correction seamless.

Write once, run anywhere

One language, every warehouse. PyDough compiles to Snowflake, Postgres, SQLite, and more — so you can train LLMs once without worrying about SQL dialect chaos.

Resistant to data leakage

Because PyDough is new, LLMs haven’t memorized it. That means you get cleaner evals, safer prompts, and no noisy interference from pre-trained SQL behaviors.