Case Study

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 It Works

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.
Get Started

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