Rchilli vs. Resume Parser by Affinda

This is a great tool if you need to imbed the functionality (as we have done). Perhaps not a well suited to standalone use.

Affinda is especially appropriate for larger organisations, like ours with internal CRMs. For those who use a fully fledged cloud-based ATS, Affinda will not meet their needs, as Affinda is just one step in the chain.

• Parsing of Candidate Resumes with good accuracy
• Around 70 to 80 different Candidate Fields
• Supports Individual, Bulk Online and Offline Parsing

• Quality
• Service
• Price

• So far, we have nothing to complain about.

• Resume Parser by Affinda is a few seconds slower than the other parsers I used (Part of this may just be due to propagation delay, considering my data center is halfway around the world). Regardless, for my needs, Affinda's accuracy outweighed the extra latency.

Quick responsiveness to inquiries. Willingness to customize the product to the customer's needs.

We recently evaluated Azure Cognitive AI Services. It was not economical and we were asked to partner with another partner of Microsoft for specific Resume Parsing Services. Looking at the cost benefits, efficiency of parsing and ease of use of RChilli, we decided to continue with our very good partner RChilli

I was assigned this project by our operations manager. We evaluated four competing saas solutions, and after the evaluation we found that [Resume Parser by Affinda] scored best on quality, service and price, and was third best on speed. Wasn’t a hard choice.

• Using Rchilli saved us thousands of dollars in development costs and avoided on-going maintenance.
• Using their taxonomy's means we don't have to maintain our own, saving us time and subscription costs.

• Time savings and easily gathers data in a useful manner to make decision making better.