Step up your automation game with AI

Best practices for a successful AI Agent

To ensure that your new AI Agent will remain a valuable addition to your team for many years to come, we would like to share some tips and tricks for a successful AI Agent with you.

Sometimes, less really is more

When adding new knowledge to your AI Agent, it can be easy to get carried away and keep adding more and more data to your datasets. But this is a classic case where more is not always better. Having too many question variants in your dataset can greatly increase the chance of overlap with other datasets with their own questions. This can cause unnecessary confusion and Mismatches.

To overcome and even prevent this from happening, think of your AI Agent as a tree. Sometimes, if you want a tree to grow better, you need to trim some of its branches so they don’t get in the way of each other. By selectively pruning unnecessary branches your tree can grow steadily and stay healthy.

In your AI Agent this translates to keeping your datasets neat and clean. Instead of constantly adding any new question to your datasets, occasionally take the time to evaluate your datasets and remove unnecessary questions or variants. This way you can prevent overlap between datasets and will increase the success rate of your AI Agent.

Be specific

Good datasets are key to the success of your AI Agent and to make sure that your dataset is good, be specific with your questions and variants.

It’s no use to add short or vague questions to your dataset. When you’re adding questions, try to phrase the questions the same way your customers would. Make longer phrases with synonyms for key words to make sure your AI Agent really understands the intention behind the questions.

By keeping your datasets specific and clear, you can prevent a lot of trimming work in the future and your AI Agent will be much easier to maintain.

Ask for feedback, then ask for more

The last important part of maintaining a successful AI Agent is to ask customers for feedback. Finding out what your customers think of your AI Agent can be of great help when optimising your AI Agent. By letting your AI Agent ask for feedback whenever it answers a question, you can immediately see whether your AI Agent was successful in recognising the customer's question and if it provided the right answer.

You can then use this feedback to know exactly where you need to improve your AI Agent to provide your customers with the optimal service experience.