Are you looking to automate your quality management by automatically scoring all of your calls and streamlining your QA processes? Then you probably came across both Level.ai and MiaRec and wondered how both solutions compare.
Here at MiaRec, we have helped hundreds of organizations worldwide improve contact center efficiency and customer experiences. We pride ourselves on providing unbiased, helpful, and transparent information so that you can make the right choice for you.
In this article, we will compare Level.ai and MiaRec's solutions. By the end of the article, you will have a good understanding of their similarities and differences and which vendor is more suitable for which type of organization.
For other vendors, please check our Conversation Intelligence Market Guide.
Let's look at both in more detail:
Both Level.AI and MiaRec offer automated QA as their flagship products. They are both based on Large Language Models' proprietary speech recognition and transcription engines. Level.ai takes pride in having optimized its engine for accurately detecting speech in "noisy contact centers" and offers an accuracy of 85%. MiaRec's proprietary transcription engine offers an accuracy of 85%.
Both companies provide their customers with comparable functionality as both solutions allow contact centers to automatically and accurately score 100% of their calls for quality assurance. However, there are some subtle differences in the approach.
Level.ai's Auto QA solution is built on a custom Large Language Model that each customer needs to train on their own contact center data. The company claims that this makes the Auto QA process more accurate. However, the downside to that is that you will need to train the model first. One customer remarked that they needed to wait for several months before being able to use Level.ai because they needed to record enough customer calls in stereo to train the model. Level.ai also claims to "evaluate over 80% of standards and metrics that scorecards cover," but it is not really clear what that entails.
MiaRec, on the other hand, utilizes one of the largest commercially available Large Language Models that doesn't require any training. While you will also require to record calls in stereo, you can start auto call scoring immediately. Having developed AI solutions for more than a decade, our philosophy is that while there are scenarios a custom LLM makes sense, for Auto QA the additional return on investment of a custom LLM is absolutely negligible. We have found that the accuracy of results depends much more on the quality of prompts and how much flexibility you have when writing the prompts. With this in mind, we introduced ground-breaking AI Prompt Designer functionality that will allow you to create custom prompts and test them in a safe environment before applying at scale.
Level.ai is not really focusing on manual evaluation although they do offer some support to human evaluators by having the AI suggest scores and reasoning for those scores. However, in our experience this can lead to unwanted bias. Because manual evaluations can be tedious and very time-consuming, this can also result in evaluators just accepting the suggestions to get through the calls faster.
With MiaRec, customers have multiple options on how to use our manual and hybrid QA tools:
Both companies feature many additional agent- and supervisor-supporting AI features, such as auto data redaction, auto call summary, VoC insights, and more, which are comparable in scope and functionality.
In addition, it is worth noting that Level.ai's AgentGPT is like a ChatGPT for customer service personal. First released into Alpha in January 2023, the feature is trained on the customers' organization's data with the goal to eliminate the need to create and maintain a manual documentation or knowledge base articles. Agents can quickly type in questions or customer concerns into a ChatGPT-like UI to get Generative AI-generated responses quickly. If the answer is useful and correct, the agent can give it a thumbs up, if the answer is garbage or useless, they can vote it down.
Additionally, MiaRec offers Machine Learning and AI-driven sentiment and topical analysis (included in the Advanced package) comprehensive approach to provide in-depth and comprehensive insights. MiaRec's engine meticulously examines the entire conversations for positive or negative customer sentiment which is then conveyed through various means, including scores (total, customer, and agent score) accompanied by emojis, as well as a short explanation why AI assigned this score.
Furthermore, you can discover call reasons and Voice of Customer Insights with MiaRec's Topical Analysis and AI Insights functionality. It understands the context of the entire conversation and conducts an analysis based on your specific criteria. This tool's flexibility allows you to extract as much or as little information as needed, making it a potent asset when combined with automated AI-based call scoring. This gives you the ability to categorize calls based on the reason for calling, extract key data from the conversations, and create AI Call Summaries in different custom formats, all using our powerful AI Prompt Designer for crafting and finalizing the prompts for the most accurate results that work for your business goals.
In conclusion, both Level.ai and MiaRec offer comprehensive automated QA solutions with unique approaches and features. While Level.ai focuses on AI-powered knowledge bases and coaching, MiaRec excels in highly customizable AI insights and hybrid QA, combining AI with human evaluation.
To experience the power of MiaRec firsthand, we encourage you to try our free online demo without any sign-up required. For more in-depth information, don't forget to read our Buyer's Guide to Conversation Intelligence.