Automated solutions like OCR can help tackle retail data transcription at scale, but maintaining data quality remains a major challenge.
Exception Processing
![How Retailers Can Keep Up with Post-Pandemic Data Demands](https://blog.cloudfactory.com/hubfs/04-blog-img/How_Retailers_Can_Keep_Up_with_Post-Pandemic_Data_Demands.png)
Retail data transcription is time-consuming and tedious work, not to mention notoriously hard to scale. Here’s how retailers can overcome those challenges.
![The AI & Automation Must-Have: Humans-in-the-Loop](https://blog.cloudfactory.com/hubfs/shutterstock_114700177.jpg)
Humans are necessary while automating decisions and processes with AI, machine learning, and RPA. Experts discuss the need for humans in the loop (HITL).
![3 Examples: Solving Automation and ML Exceptions with Humans in the Loop](https://blog.cloudfactory.com/hubfs/04-blog-img/solving-automation-and-ml-exceptions-with-humans-in-the-loop.png)
Learn how CloudFactory’s managed workforce worked with 3 companies, each with a problem involving data, automation, and/or ML.
![Optimizing Decision Making by Combining Automation and People](https://blog.cloudfactory.com/hubfs/04-blog-img/optimizing-decision-by-combining-people-and-automation.png)
An incremental design approach to automation and machine learning affords strategic opportunities for choosing to route exceptions to machines or people.
![3 Common Mistakes Automation and ML Modelers Make](https://blog.cloudfactory.com/hubfs/04-blog-img/common-mistakes-automation-and-ml-modelers-make.png)
Automation and AI hold great potential to innovate, improve, and make predictions. Here are three mistakes you’ll want to avoid.
![Maximizing ROI for ML, Decision Management, and RPA](https://blog.cloudfactory.com/hubfs/04-blog-img/maximizing-roi-for-ml.jpg)
Could the secret to developing ML be more boring than we think? It’s time to give up the quest for the perfect model.