# Nuvia for data warehouse: Sync sales and customer service data from Nuvia to BigQuery, Redshift, and PostgreSQL

> Managed connector to sync Nuvia conversations, contacts, campaigns, and agents into BigQuery, Redshift, and more with Erathos.

Source: https://www.erathos.com/en/blog/nuvia-connector-launch
Em português: https://www.erathos.com/blog/nuvia-connector-launch
Published: 2026-07-29
Category: New Connectors

![Logo Nuvia Api](https://cms-media.erathos.com/h0LhbROC48JghToXOVs8U3Ecs-1.png)

## Sync Nuvia sales and customer support data to BigQuery, Redshift, and PostgreSQL

Nuvia handles sales, customer service, and support using AI agents 24/7. Every handled conversation, qualified lead, triggered campaign, and exchanged message flows through the platform. When this data remains siloed inside, the data team can't join AI agent performance with CRM revenue, track lead progression through the funnel, or measure the actual impact of campaigns on the pipeline.

The Nuvia connector on Erathos solves this: it syncs conversations, contacts, campaigns, messages, agents, inboxes, knowledge bases, and custom tables to your data warehouse in automatic cycles, with incremental sync on endpoints supporting cursor-based replication. No pipeline code to write, maintain, or monitor.

## The problem with custom-built Nuvia pipelines

Building an in-house pipeline for the Nuvia API seems simple on day one. The API uses bearer token authentication, returns JSON, and has predictable endpoints. The trouble starts once the first version hits production.

**Non-uniform pagination across endpoints.** The `conversations` endpoint supports cursor-based pagination based on `createdAt` for incremental syncs. However, `messages` is a child endpoint that depends on `conversationId` and lacks its own cursor. A pipeline that treats all endpoints the same way will duplicate messages or silently miss new records.

**Silent rate limits.** The API can throttle request frequency without throwing an explicit `429` error. The pipeline keeps running, logs a success, but the data lands incomplete. No one notices until a dashboard displays numbers that don't add up.

**Unannounced schema evolution.** Nuvia can add new fields to `conversations`, `contacts`, or `campaigns` at any time. A pipeline doing a `SELECT *` and loading into fixed columns will break silently or, worse, map the wrong field to the wrong column.

**Lack of observability.** There are no structured logs, no execution history, and no reconciliation between what the API returned and what actually landed in the warehouse. When someone asks "why is yesterday's data different from the day before?", no one has an answer.

The most severe consequence isn't a pipeline that breaks with an alert. It's the pipeline that runs successfully, delivers wrong data, and goes unnoticed until a business decision is made based on bad metrics.

## What you can do once Nuvia data lands in your warehouse

### Measure AI agent performance per conversation

With `agents`, `conversations`, and `messages` in your warehouse, you can join which agent handled each conversation, how many messages were exchanged, the time elapsed between the first and last message, and the final conversation status. This allows you to compare agents by resolution rate, average handle time, and message volume, metrics that the Nuvia UI doesn't provide historically.

### Track lead funnel from first touch to conversion

The `contacts` table contains the name, email, phone, and status of each contact. By joining this with `campaign_enrollments`, you can reconstruct the funnel: how many contacts entered each campaign, how many advanced in status, and how many actually converted. When these contacts exist in your CRM (Salesforce, HubSpot, Pipedrive), joining them in the warehouse reveals which Nuvia campaign drove the most actual revenue.

### Audit outbound and inbound campaigns

The `campaigns` endpoint provides the name, type, and status of each campaign. With `campaign_enrollments` in your warehouse, the marketing team can calculate enrollment rates, conversion rates by campaign type, and compare outbound (prospecting) versus inbound (support) performance. This analysis is only feasible when data lives in a queryable table alongside revenue data.

### Analyze knowledge base quality

The `knowledge` table lists the knowledge base items that AI agents use to reply. By joining this with `messages`, you can identify which conversations mentioned or referenced knowledge base topics and measure if the presence of a specific article correlates with higher resolution rates. This helps prioritize which content to create or update.

### Monitor inboxes and support volume by channel

The `inboxes` endpoint provides the name, email, and type of each inbox. With `conversations` filtered by `contactId` and `agentId`, you can measure ticket volume per inbox, identify bottlenecks in specific channels, and plan capacity. Joining this with product data (tickets, feature usage) allows you to correlate support spikes with product releases or incidents.

### Query custom Nuvia tables

Nuvia allows you to create custom tables (`tables` and `table_rows`) with structured JSON data. In the warehouse, this data can be flattened into analytical columns, enabling direct SQL queries on information that Nuvia stores semi-structured. This unlocks ad hoc analysis that the platform's UI doesn't support.

## What's available in the connector

Endpoint

What it contains

agents

AI agents configured in Nuvia (name, model, description, status)

campaigns

Outbound and inbound campaigns (name, type, status)

campaign\_enrollments

Contact enrollments in campaigns, mapping campaigns and contacts

contacts

Contacts database with name, email, phone, and status

conversations

Conversations between contacts and agents, with an incremental cursor on createdAt

inboxes

Configured inboxes (name, email, type)

knowledge

Knowledge base articles used by AI agents (title, type, status)

messages

Individual messages within conversations (content, type, sender)

tables

Custom tables created in Nuvia (name, description), with an incremental cursor on updatedAt

table\_rows

Data rows of custom tables, stored in JSON

The `conversations` and `tables` endpoints support incremental sync (full and incremental refresh) using cursors on `createdAt` and `updatedAt` respectively. All other endpoints run as full refresh.

## How to authenticate

Authentication for the Nuvia connector requires a single field:

- **Token**: Nuvia API bearer token, used for all requests

**Where to find it:**

1. Log in to your Nuvia account at [app.nuvia.ai](https://app.nuvia.ai/)
2. Navigate to **Settings > Integrations > API Keys**
3. If an API key doesn't exist, create a new one by clicking the appropriate button
4. Copy the generated value
5. Paste the token into the **Token** field in the Erathos connection form
6. Click **Save and close**

See the full documentation at [docs.erathos.com/connectors/apis/nuvia-api](https://docs.erathos.com/connectors/apis/nuvia-api).

## Why outsource ingestion to Erathos

### End-to-end visibility of every run

Every sync runs with structured logs: how many records the endpoint returned, how many were inserted, how many were updated, and how long each step took. There is an execution timeline that allows you to audit any given day and answer "why is yesterday's data different" without needing to reproduce the pipeline locally.

### Out-of-the-box alerting

The connector comes pre-configured with alerts for execution failures, abnormal drops in record volume, and credential expiration. No configuration needed: if the Nuvia token expires or a sync fails three times in a row, your team is notified automatically. The issue is caught before anyone notices missing data on the dashboard.

### Native backfills and reprocessing

If a run fails or you need to reload data for a specific period, reprocessing is a native operation. No editing code, manually shifting cursors, or writing ad hoc scripts. A single click reruns the sync for the selected timeframe, featuring the exact same logs and observability as a standard run.

## Available pipelines

- Nuvia to BigQuery: [https://www.erathos.com/pipelines/nuvia-api-bigquery](https://www.erathos.com/pipelines/nuvia-api-bigquery)
- Nuvia to Redshift: [https://www.erathos.com/pipelines/nuvia-api-red-shift](https://www.erathos.com/pipelines/nuvia-api-red-shift)
- Nuvia to PostgreSQL: [https://www.erathos.com/pipelines/nuvia-api-postgresql](https://www.erathos.com/pipelines/nuvia-api-postgresql)
- Nuvia to Databricks: [https://www.erathos.com/pipelines/nuvia-api-databricks](https://www.erathos.com/pipelines/nuvia-api-databricks)
- Nuvia to Supabase: [https://www.erathos.com/pipelines/nuvia-api-supabase](https://www.erathos.com/pipelines/nuvia-api-supabase)
- Nuvia to Amazon S3: [https://www.erathos.com/pipelines/nuvia-api-amazon-s3](https://www.erathos.com/pipelines/nuvia-api-amazon-s3)
- Nuvia to Azure SQL Server: [https://www.erathos.com/pipelines/nuvia-api-azure-sql-server](https://www.erathos.com/pipelines/nuvia-api-azure-sql-server)
- Nuvia to Azure Synapse: [https://www.erathos.com/pipelines/nuvia-api-azure-synapse](https://www.erathos.com/pipelines/nuvia-api-azure-synapse)
- Nuvia to ClickHouse: [https://www.erathos.com/pipelines/nuvia-api-clickhouse](https://www.erathos.com/pipelines/nuvia-api-clickhouse)
- Nuvia to Snowflake: [https://www.erathos.com/pipelines/nuvia-api-snowflake](https://www.erathos.com/pipelines/nuvia-api-snowflake)

## Get started

[Create your Erathos account](https://app.erathos.com/signup?slug=blog&button=cta&utm_campaign=nuvia-api_release) and connect Nuvia to your warehouse in minutes. With an API token, your first data loads into its destination without a single line of pipeline code to write, maintain, or monitor.

AI-generated sales and customer support data shouldn't stay locked inside a SaaS, disconnected from the rest of your analytical model, or worse, in an in-house pipeline that demands engineering attention month after month, forever.

Check out the full connector documentation at [docs.erathos.com/connectors/apis/nuvia-api](https://docs.erathos.com/connectors/apis/nuvia-api).