# A real-time alerts company replaced a lost source in about 1 week

1 week of side-by-side checks against its own records, then straight to production.

About 1 week from first check to production · About 8x growth in month 2 · Pipelines run by its own engineers, by API

## At a glance

- **Customer:** Real-time alerts company
- **Sources:** 1 source to start, searched every hour
- **Volume:** Up about 8x in its second month
- **Delivery:** By API, into its own alerting
- **In production:** About 1 week after its first check

## About the customer

A company that sends real-time alerts to its clients.

**Industry:** Social Listening and Alerts

## The Story

Challenge, solution, results.

### The Challenge: The alerts went quiet

The company sends its clients real-time alerts when they're mentioned online, along with deeper historical research when they need it.

Then its data provider stopped supplying one of the sources those alerts depended on. The alerts went quiet, and its clients noticed. It needed a replacement fast, but it couldn't swap in data it hadn't checked.

### The Solution: Check it, then switch

It ran Datastreamer side by side with its own records for 1 week and compared the results. Once the data held up, it went straight to production.

Its own engineers build and run the pipelines through the Datastreamer API, with searches running every hour and results delivered straight into its alerting.

### The Results: Clients covered again

The alerts were back, and its clients were covered again. In its second month, its usage grew about 8x as more of its alerting moved onto the pipeline. It started with 1 source.

## How the pipeline works

1. **Source:** 1 source, replacing the one its provider dropped.
2. **Collection:** Searches every hour, plus historical pulls on demand.
3. **Control:** Pipelines created and run by its own engineers through the API.
4. **Delivery:** Straight into its client alerting.

## Lost a source? Run a proof.

We'll run the data side by side with your own records, so you can check it before you commit.

[Talk to Sales](https://datastreamer.io/book-demo/) · [Read the Documentation](https://docs.datastreamer.io)

## Related

- [Risk Intelligence Case Study](https://datastreamer.io/risk-intelligence-case-study/)
- [Media Monitoring Case Study](https://datastreamer.io/media-monitoring-case-study/)
- [Data Pipelines for Social Listening Platforms](https://datastreamer.io/data-pipelines-for-social-listening-platforms/)