What is Nexa?
Nexa is a data and AI platform from DataReadyAI. You point it at your source systems, and it ingests raw data, models it through governed Raw → Curated → Consumption layers, generates the pipelines that move data between them, and lets you build AI agents and agentic automations on top of the result. This page explains what Nexa does, the layer model it is built around, and where to go next.
What Nexa does
Section titled “What Nexa does”Nexa covers the path from a source connection to a working analytics-and-AI product without you hand-writing the ingestion, modeling, and pipeline code:
- Ingest — Connect to databases, message queues, and file storage, and pull tables and files into the platform.
- Model — Map source fields into curated business entities and then into consumption-ready shapes, with AI-assisted field mapping and tagging.
- Generate pipelines — Turn those mappings into runnable jobs and pipelines that keep each layer up to date.
- Build on top — Create AI agents and multi-step agentic automations that use the modeled data, and expose them as apps.
- Govern — Track business terms, PII (personally identifiable information) tags, changes, and cost across everything above.
The Raw → Curated → Consumption model
Section titled “The Raw → Curated → Consumption model”Nexa organizes data into three layers, the widely used medallion pattern. Each layer has a distinct job, and Nexa generates the pipelines that move data from one to the next.
| Layer | Also called | What lives here | Purpose |
|---|---|---|---|
| Raw | Bronze | Source data landed as-is | Faithful, auditable copy of what the source sent |
| Curated | Silver | Cleaned, conformed business entities | Deduplicated, typed, mapped records you can trust |
| Consumption | Gold | Wide, joined, analysis-ready entities | 360-degree views, metrics, and shapes for BI, apps, and agents |
You work with these layers in the UI under Data Flow (Raw and Curated) and Canvas (Consumption). The mapping you define at each boundary — which source field becomes which curated attribute, which curated entities combine into a consumption entity — is what Nexa compiles into pipeline code.
Agents, automations, and apps
Section titled “Agents, automations, and apps”Once data is modeled, Nexa lets you build AI on top of it:
- Agents — Conversational or task-focused AI that answers questions and acts against your governed data. See Agents overview.
- Agentic automations — Multi-step workflows with triggers and actions that run a plan against your data and systems. See Automations overview.
- Apps — Deployed front ends (for example Streamlit or Slack) that surface an agent to end users. You start, stop, and open them from the Apps screen.
Governance built in
Section titled “Governance built in”Governance is not a separate product bolted on; it spans every layer:
- Business glossary — A catalog of business terms and entities, so field names mean the same thing everywhere. See Business glossary.
- PII tagging — Sensitive fields are identified and tagged as data is mapped.
- Change review — Structural changes flow through an approval step before they take effect. See Review changes.
- Cost tracking — Usage and spend are surfaced on the Usage & Costs screen.
Who uses Nexa
Section titled “Who uses Nexa”| Role | What they do in Nexa |
|---|---|
| Data engineers | Set up connections and connectors, review generated pipelines, manage jobs |
| Data / analytics teams | Map curated and consumption entities, define business glossary terms |
| AI builders | Create agents and automations, deploy them as apps |
| Platform / operations teams | Install, configure, and operate Nexa in the customer cloud |
How Nexa fits your stack
Section titled “How Nexa fits your stack”Nexa runs against your existing cloud and data platform rather than replacing them. The web UI (nexa-web) talks to backend services that drive your data platform directly, so the tables, pipelines, and compute Nexa creates live in your Snowflake or Databricks account under your governance.