# Prometheux

> Prometheux: deterministic agents at scale. Combine your data and everything your organization knows into rules a machine can run and a person can verify, on the stack you already run on.

## What Prometheux does

Prometheux connects to your data where it lives and turns your business logic into rules. Agents answer questions and run workflows by executing those rules, not by guessing, so the same question always returns the same answer and every result traces back to the rows behind it.

- **Data, read in place.** Prometheux reads databases, warehouses, files and APIs where they live and processes them in memory. Nothing is copied or migrated, and data only moves if you want it to.
- **Rules, deterministic.** Your business logic, written once and run across all your sources together. Same question, same answer, every time, with full lineage. Running rules costs no LLM tokens.
- **Context, attached.** The know-how around the rules (documents, notes, a recipe book) attaches to an ontology or a single rule. It guides how rules are written and how agents read the results, but never changes the answer.
- **Agents, on top.** Any model (Claude, GPT, Gemini, open-source) works with Prometheux over MCP, API or CLI. Agents power analytics, integrations back into your apps, and workflows that run deterministically, including ones that monitor themselves.

## Why deterministic agents

LLMs are good at patterns in text, images and audio. They are less good at following rules exactly. Prometheux pairs the two (neurosymbolic AI): models handle language, rules handle logic, so answers are explainable, repeatable and auditable.

## Key use cases

- **Explainable decisions:** credit decisions, risk and compliance with end-to-end lineage
- **Root-cause analysis:** tracing failures across machines, suppliers and processes
- **Digital twins:** end-to-end views of patients, networks or operations at scale
- **Cross-source analytics:** queries spanning hundreds of millions of data points in seconds
- **Graph analytics without a graph database:** multi-hop, recursive and network analysis on existing data

## Where it runs

In your cloud (AWS, Azure, GCP, or natively inside Snowflake and Databricks), on your premises, or fully managed by Prometheux.

## Proven in production

Banca Sella, Dompé, Vodafone, AstraZeneca, a Fortune 100 retailer, a European neo-bank and a US biotech.

## Industries

Finance & Banking, Insurance, Pharma & Life Sciences, Manufacturing, Retail, Telecom.

## Platform

- [Platform](https://www.prometheux.ai/platform): One platform for all your data.
- [Technology](https://www.prometheux.ai/technology): Purpose-built ontology engine.
- [Partners](https://www.prometheux.ai/partners): Databricks, Snowflake, NVIDIA, AWS.

## Solutions

- [Finance & Banking](https://www.prometheux.ai/solution-finance-banking)
- [Insurance](https://www.prometheux.ai/solution-insurance)
- [Pharma & Life Sciences](https://www.prometheux.ai/solution-pharma)
- [Manufacturing](https://www.prometheux.ai/solution-manufacturing)
- [Retail](https://www.prometheux.ai/solution-retail)
- [Telecom](https://www.prometheux.ai/solution-telecom)

## Resources

- [Resource Center](https://www.prometheux.ai/resource-center)
- [Research](https://www.prometheux.ai/research)
- [Book a Demo](https://www.prometheux.ai/book-a-demo)
- [Contact](https://www.prometheux.ai/contact)