Senior Manager for End User Support Services at Five9
Real User
Top 10
2023-11-21T18:27:00Z
Nov 21, 2023
Espressive Barista's natural language processing and conventional AI still have room for improvement. We haven't yet found anything that resembles true AI that can learn autonomously without human intervention. However, Barista does help us identify and address some of these areas, allowing my team to step in and create intents and responses to questions. When a user asks a question that Barista doesn't immediately understand, we can recognize the pattern, capture it, and link it to a common intent. This is highly beneficial for acquiring such data, but it's a reactive approach and still requires curation. Natural language processing still has some way to go. One of our challenges is that our internal employees haven't yet adopted a natural way of interacting with Barista. Getting people to be concise and to the point, rather than being verbose as if they were interacting with a human, has been an ongoing challenge. While they may feel comfortable being conversational in Slack, expecting a human-like response, Barista is a different entity. Barista isn't interested in their recent vacation; it just wants to know they're locked out of their account. So, some users may assume Barista understands their intent when they say, "I'm back from vacation and locked out of my account." Barista, however, may interpret this as a request for the holiday schedule. Therefore, we're gradually educating our users to adapt their communication style for better success with Barista. Conversely, we desire Barista to adapt its behavior based on the interaction, the language used, and the way people communicate. I wholeheartedly desire an AI that can continuously learn and adapt to our organization's evolving needs. This is the most challenging aspect, as it involves understanding our organization's terminology, procedures, and toolsets. We've made significant progress in this area. However, from an NLP standpoint, we still face challenges with our nearly 3,000 Slack channel users, each with their unique communication styles. People ask questions in various ways, and sometimes there are misunderstandings. They want to interact with us naturally. However, we still struggle with natural language processing. People don't always realize that the bot is a virtual agent designed to be concise and efficient. Sometimes, less is more. It's been a difficult transition for people to grasp that they're conversing with a virtual agent, not a human. They still expect human-like interactions, such as discussing their weekend or holidays or simply pasting screenshots of errors. However, the bot can't interpret screenshots. If they provide the error code and some context about the application, the bot can better understand the issue. So, the key challenge is bridging the gap between human expectations and the bot's capabilities in terms of natural interaction.
Expressive Barista could improve by adding native integration with WhatsApp, one of the top communication channels in South Africa. When we're trying to sell Barista to customers, we have to tell them that the solution doesn't have out-of-the-box support for WhatsApp. We can develop it, but then we need to have a conversation about how much that will cost.
Manager at a manufacturing company with 51-200 employees
Real User
Top 20
2023-06-09T16:10:00Z
Jun 9, 2023
What would make things easier is easier access to detail about out-of-the-box interactions and what Barista has brought in natively that the employees are using. I am loving the opportunities that are upcoming on the Espressive product roadmap!
Sometimes, when a ticket is opened, we need to find out its pending status and provide the information to the person who opened the ticket. This is because they are not automatically notified of the status change. The reports provided by the solution are not customizable. I would like to be able to apply filters to the reports, as we require them on a daily basis, and provide them to management. The reports have room for improvement.
Business Services Technology Manager at a recreational facilities/services company with 5,001-10,000 employees
Real User
2022-10-14T19:24:45Z
Oct 14, 2022
The knowledge management could definitely be improved. There's no easy way to see or understand the information you have in your system by categories and subcategories. Right now, you can search by what your FAQ title is or the questions, but there needs to be improvement so you can understand what workflows and FAQs you have out there by category and subcategory. That would be a lot more beneficial for maintaining it. Right now, you have to look through miss hits and be like, "Oh shoot, we updated that." Or, "That needs to get corrected." If you have a big update that you need to make and you need to go back into all of your conversation history, you need to keep a good record of it on your own.
IT Desktop Support Lead (IT Analyst III) | Application Administrator at a energy/utilities company with 5,001-10,000 employees
Real User
2022-04-29T00:14:00Z
Apr 29, 2022
Although they've done some work on their metrics dashboard, there is some fine-tuning to do for people that just want to go in there at a glance and see their metrics. This doesn't affect me as much because I pull the metrics from them and upload them to my own Power BI dashboard. It would be nice if their out-of-the-box dashboard were improved.
Help Desk Manager at a manufacturing company with 5,001-10,000 employees
Real User
2022-04-28T12:45:00Z
Apr 28, 2022
There aren't really any areas for improvement. It's a virtual support agent that integrates ServiceNow, leveraging ServiceNow workflows. My only comment would be, if Espessive wanted to make this an IT service management tool, maybe they could think about Barista making tickets and adding a feature which will have change management and problem management capabilities. Maybe they could have an ITSM style of service management route through Barista. That would be my only suggestion for improvement. Maybe it could eventually replace ServiceNow altogether. That said, as of today, I don't see anything that needs to be improved.
The solution has provided a solid set of automation capabilities but would like to see the continued expansion of even more advanced automation capabilities. Having more prebuilt connectors for people is always preferred because it's something you can start from versus having to go and build something custom. They are starting to do that with some of the recent connectors that I've seen for Workday and some of the Microsoft stack. They're moving aggressively in that direction.
Barista, Espressive’s innovative virtual support agent (VSA) platform, takes on the role of the service agent, bringing the best of human experience with the best of artificial intelligence. Leveraging a proprietary and domain-specific large language model (LLM), the Employee Language Cloud, as well as integration with generalized LLMs, Barista automates resolution of employee questions, issues, and requests with personalized experiences that result in employee adoption of 80 to 85% and...
Espressive Barista's natural language processing and conventional AI still have room for improvement. We haven't yet found anything that resembles true AI that can learn autonomously without human intervention. However, Barista does help us identify and address some of these areas, allowing my team to step in and create intents and responses to questions. When a user asks a question that Barista doesn't immediately understand, we can recognize the pattern, capture it, and link it to a common intent. This is highly beneficial for acquiring such data, but it's a reactive approach and still requires curation. Natural language processing still has some way to go. One of our challenges is that our internal employees haven't yet adopted a natural way of interacting with Barista. Getting people to be concise and to the point, rather than being verbose as if they were interacting with a human, has been an ongoing challenge. While they may feel comfortable being conversational in Slack, expecting a human-like response, Barista is a different entity. Barista isn't interested in their recent vacation; it just wants to know they're locked out of their account. So, some users may assume Barista understands their intent when they say, "I'm back from vacation and locked out of my account." Barista, however, may interpret this as a request for the holiday schedule. Therefore, we're gradually educating our users to adapt their communication style for better success with Barista. Conversely, we desire Barista to adapt its behavior based on the interaction, the language used, and the way people communicate. I wholeheartedly desire an AI that can continuously learn and adapt to our organization's evolving needs. This is the most challenging aspect, as it involves understanding our organization's terminology, procedures, and toolsets. We've made significant progress in this area. However, from an NLP standpoint, we still face challenges with our nearly 3,000 Slack channel users, each with their unique communication styles. People ask questions in various ways, and sometimes there are misunderstandings. They want to interact with us naturally. However, we still struggle with natural language processing. People don't always realize that the bot is a virtual agent designed to be concise and efficient. Sometimes, less is more. It's been a difficult transition for people to grasp that they're conversing with a virtual agent, not a human. They still expect human-like interactions, such as discussing their weekend or holidays or simply pasting screenshots of errors. However, the bot can't interpret screenshots. If they provide the error code and some context about the application, the bot can better understand the issue. So, the key challenge is bridging the gap between human expectations and the bot's capabilities in terms of natural interaction.
Expressive Barista could improve by adding native integration with WhatsApp, one of the top communication channels in South Africa. When we're trying to sell Barista to customers, we have to tell them that the solution doesn't have out-of-the-box support for WhatsApp. We can develop it, but then we need to have a conversation about how much that will cost.
What would make things easier is easier access to detail about out-of-the-box interactions and what Barista has brought in natively that the employees are using. I am loving the opportunities that are upcoming on the Espressive product roadmap!
Sometimes, when a ticket is opened, we need to find out its pending status and provide the information to the person who opened the ticket. This is because they are not automatically notified of the status change. The reports provided by the solution are not customizable. I would like to be able to apply filters to the reports, as we require them on a daily basis, and provide them to management. The reports have room for improvement.
I would like to see improvement to the out-of-the-box verbiage, with the questions going to the right place.
The knowledge management could definitely be improved. There's no easy way to see or understand the information you have in your system by categories and subcategories. Right now, you can search by what your FAQ title is or the questions, but there needs to be improvement so you can understand what workflows and FAQs you have out there by category and subcategory. That would be a lot more beneficial for maintaining it. Right now, you have to look through miss hits and be like, "Oh shoot, we updated that." Or, "That needs to get corrected." If you have a big update that you need to make and you need to go back into all of your conversation history, you need to keep a good record of it on your own.
Although they've done some work on their metrics dashboard, there is some fine-tuning to do for people that just want to go in there at a glance and see their metrics. This doesn't affect me as much because I pull the metrics from them and upload them to my own Power BI dashboard. It would be nice if their out-of-the-box dashboard were improved.
There aren't really any areas for improvement. It's a virtual support agent that integrates ServiceNow, leveraging ServiceNow workflows. My only comment would be, if Espessive wanted to make this an IT service management tool, maybe they could think about Barista making tickets and adding a feature which will have change management and problem management capabilities. Maybe they could have an ITSM style of service management route through Barista. That would be my only suggestion for improvement. Maybe it could eventually replace ServiceNow altogether. That said, as of today, I don't see anything that needs to be improved.
The solution has provided a solid set of automation capabilities but would like to see the continued expansion of even more advanced automation capabilities. Having more prebuilt connectors for people is always preferred because it's something you can start from versus having to go and build something custom. They are starting to do that with some of the recent connectors that I've seen for Workday and some of the Microsoft stack. They're moving aggressively in that direction.