AI is only as accurate as its data

Before an AI analyst is connected, the data has to be linked, validated and accessible by the rules. That is what we do.

01Builder

Sketch your data architecture

Pick sources and goals — the diagram appears on the right straight away: sources, pipeline, warehouse, BI and outputs.

01 · Sources
02 · Goals
Preliminary architectureNodes: 8
Preliminary data architecture for the selected sources and goals
  1. CRM → ETL · ELT
  2. ERP · 1C → ETL · ELT
  3. External API → ETL · ELT
  4. ETL · ELT → Data quality checks
  5. Data quality checks → Data Warehouse
  6. Data Warehouse → AI analyst, Alerts
  7. AI analyst
  8. Alerts
SOURCES
CRM · ERP · 1C · External API

PIPELINE
3 connectors · Scheduled / incremental loads · Deduplication · validation · reference data

STORAGE
Data Warehouse (PostgreSQL or ClickHouse by volume)

OUTPUTS
AI analyst · Alerts

This is a preliminary outline. The architecture may change once we look at your sources.

02Data for AI

What AI needs from data

Clear field names and descriptions, freshness, row-level access rights and a log of what data the agent has seen.

Data is ready — need the AI agent itself?

AI agentsAgentZone
03Contact

Let’s look at your data

Five questions and you get a preliminary data architecture and a first step. Or just write to us.

Preliminary data architecture

Step 1 of 6
Where does your data live?Choose several if needed

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