Discover the Next-Level Capabilities of NeuralSeek: Boost Customer Retention and Team Organization

Welcome to our blog!?

We are excited to introduce the latest features and updates of NeuralSeek.?

In these bi-weekly posts, we will explore how the new innovative features of NeuralSeek can enhance operational efficiency, boost your virtual agent conversation containment rates, and improve customer retention and satisfaction.

Join us to see how NeuralSeek utilizes ‘trustworthy AI’ to empower your business.?

In this post we will discuss:

1. Intent Matching: Flexible options for accurate intent generation and improved understanding of user queries.
2. Intent Categorization: Organize intents effectively, map queries to teams, and streamline intent management.
3. Notes and Flagging: Enhance collaboration, share insights, and prioritize tasks through notes and flags.
4. Filter on Semantic Scores: Deliver focused search results aligned with user intent, improving the search experience.
5. Table Understanding: Simplify the processing of table data for conversational queries, unlocking its power in interactions.

Intent Matching: Flexible and Accurate Options

NeuralSeek automatically generates and groups user inputs into intents. Intent refers to the purpose or goal behind a user's input. When a user input does not match an existing intent, a new intent is created. This capability allows the system to intelligently analyze and categorize user inputs. NeuralSeek streamlines the process of understanding and addressing customer queries through intent matching, saving valuable time and resources

In the past, intent matching was limited to exact matches. Now there are four total matching options to enhance the accuracy and flexibility of intent generation:

Exact Match:

• NeuralSeek continues to support exact matches for precise intent identification.
• When a user input perfectly matches an existing intent, the system will assign it to that specific intent.

Fuzzy Match:

• To accommodate variations and potential errors in user inputs, NeuralSeek now incorporates fuzzy matching.
• Fuzzy Match allows the system to recognize inputs that are similar, but not an exact match, to existing intents.
• This flexibility enables better handling of spelling mistakes, minor variations, or alternative phrasings.

Keyword Match:

• In addition to fuzzy matching, NeuralSeek introduces Keyword Match capabilities.
• By leveraging keywords or key phrases, NeuralSeek identifies the underlying intent even when the input does not entirely match.?

Fuzzy Keyword Match:

• This advanced feature allows the system to identify intents based on keywords or key phrases, even if there are slight variations or errors.
• It provides flexibility in recognizing intents based on keywords or key phrases, even with slight variations or mistakes.

Intent Categorization: Enhanced Team Organization

Intent categorization plays a crucial role in managing and organizing the ever-increasing number of intents within your NeuralSeek instance. As your number of intents grows, the curate tab can become overwhelming to navigate and handle effectively. Intent categorization offers a solution by providing a structured approach to managing the vast amount of data.

By creating intent categories, users can map queries to specific teams or departments responsible for managing them within the overall process flow. This categorization process simplifies the management of intents and ensures that they are appropriately handled by the relevant teams. Categories can be created under “Configure” -> “Intent Categorization”.

When a categorization is created it is important to give a detailed description of the intents that should be included in the category. The description you provide will be used in the backend to match intents to categories. In addition to automatic categorization, you can also add intents manually under the “Curate” tab. When you do add to a category this is further utilized in training and allows NeuralSeek to further understand what type of questions should be included in the given category.

Categories also play a role in analytics. With categories set up, users can gain specific insights and analytics related to each category. This allows teams to track and measure the performance of intents within their respective categories, enabling data-driven decision-making and optimization of the conversational AI system.

Notes and Flagging: Efficient Collaboration and Documentation

NeuralSeek's notes feature allows team members to add valuable insights and information directly into intents. Whether you're working across teams or collaborating on a specific project, the ability to add notes brings clarity and context to the intent management process. By leveraging the notes function, team members can seamlessly share updates, provide feedback, or highlight important details, ensuring everyone stays informed and aligned.

The combination of flagging and notes takes collaboration to the next level. By using flagging and notes in tandem, teams can efficiently coordinate their efforts, identify priority tasks, and address specific issues. Flagging important intents or queries allows for quick recognition and focused attention, enabling teams to prioritize their actions and respond promptly to customer needs.

Filter on Semantic Scores: Delivering Focused Results

Semantic scoring analyzes the similarity between the user's query and the content of the search results. By considering the underlying meaning and intent of the query, NeuralSeek can identify the most relevant results and present them at the top of the search results list.

This feature ensures that the search results align closely with the user's intent, making it easier for them to find the information they need quickly and accurately. By reranking the search results based on semantic match, NeuralSeek enhances the overall search experience and improves the chances of users finding the most relevant and useful content.

Table Understanding: Unlocking the Power of Table Data

Traditionally, processing table data has been a costly and time-consuming task. However, with Table Understanding, NeuralSeek simplifies the process and ensures that the extracted table data is in a format that can be seamlessly integrated into conversational interactions.

It's important to note that Table Understanding is an ‘opt in’ feature, as it involves additional computational resources. For each table preprocessed, one seek query is consumed. Please be aware that Web Crawl Collections are not eligible for Table Understanding due to the recrawl interval and its impact on compute usage.

While Table Understanding is available by ‘invite only’ for Lite plans, we encourage you to reach out to [email protected] with details about your opportunity and use case. By doing so, you can be considered for access to this cutting-edge feature.

Closing: Additional Resources

Thank you for joining us in exploring the new features of NeuralSeek! We hope this blog post has shed light on how NeuralSeek can enhance operational efficiency, boost your virtual agent conversation containment rates, and improve customer retention and satisfaction.

To stay updated with the latest advancements in AI and NeuralSeek, we invite you to follow us at TechD and Cerebral Blue on LinkedIn, as well as on our YouTube channels:

• TechD
• Cerebral Blue

Stay tuned for future posts, where we dive deeper into the possibilities of ‘trustworthy AI’ and its potential to empower your business!