Causes of the problem
Lack of scalable infrastructure – most solutions operate on limited capacities and do not adapt to the load.
Problems with processing large volumes of data – systems do not have time to analyze calls in real time.
Limited server capacity – most solutions do not use modern distributed data processing technologies.
✅ The system can handle millions of minutes of calls monthly without data loss .
✅ Distributed server architecture allows for stable operation even under peak loads.
✅ Automatic scaling of server capacity as traffic grows.
🔬 SalesAI runs on a cloud infrastructure costa rica email data with automatic scaling, allowing it to handle thousands of calls simultaneously without interruption.
- Slow data processing
Some speech analytics systems process calls with a delay of several hours or even days, which makes the analytics useless for operational management.
Why is the result of implementing such speech analytics disappointing?
📉 Managers cannot quickly analyze errors and improve sales in real time.
📉 Managers lose the ability to quickly respond to problems in the sales department.
📉 Slow analytics reduces the speed of adaptation of business processes to changes.
Causes of the problem
Call processing is performed in batch mode - data is updated once a day, which does not allow receiving up-to-date information.
Use of outdated analysis algorithms that require a lot of time to process speech.
Limited computing power – competitors’ servers cannot handle fast analysis.
How does SalesAI solve this problem?
✅ Call processing in just 1 minute – analysis results are available almost immediately.
✅ Instant transfer of information to CRM without delays.
✅ Automatic recommendations to managers based on calls in real time.