The PROCERTUS architecture: people and AI agents ask questions through one intelligent layer — a business glossary, a context graph and a query trace — which reaches enterprise data from seven kinds of sources and orchestrates frontier models, returning every answer with its trace.

Product

One layer between your questions and your data.

The architecture in one picture: people and AI agents on one side, everything you have on the other, and the ProCertus layer in between.

PeopleAsk in natural languageAsk in natural language

AI agents

Intelligence layerThe intelligent layer

Frontier modelsClaudeGPTGeminiOtherClaude · GPT · Gemini

Enterprise dataStructured + UnstructuredStructured + Unstructured

DatabasesWarehouses + operational DBs

Cloud appsSaaS your teams live in

ERP / CRMSystems of record

File sharesDocuments + spreadsheets

EmailContext no table holds

IoT devicesDevice + sensor streams

Web / logsHigh-volume signals

Your data

All your enterprise data, where it lives

Databases, cloud apps, ERP and CRM, file shares, email, connected devices, web and logs. All your sources — connected where it already lives.

The intelligence layer

One layer that understands it all

Between the questions and the data sits the PROCERTUS intelligence layer. Accuracy, scale, governance, and lowest TCO all rolled up into one

Frontier models

Models behind the layer, never at your data

Claude, GPT, Gemini, Others. We use frontier models where they excel, always through the layer.

The full loop

Ask it something

A question travels from a person or an agent, through the layer, across your sources, back through a model and returns with its answer. Fire one below and watch the round trip.

PROCERTUS · simulatorsample data

Which accounts are most likely to churn next quarter?What does revenue look like if pipeline conversion holds?Where will we stock out first?

pick a question to run the loop — sample data only