Ender Turing SaaS by Lidiia Suslova is a highly esteemed winner of the very prestigious 2023 Bronze A' Design Award in Interface, Interaction and User Experience Design Competition Category.
BronzeInterface· 2023
Ender Turing SaaS
Client: Ender Turing
Bronze A' Design Award Winner in Interface Category
Verified Award Winner
Verify Award Status for #149673The Design
About Ender Turing SaaS
Ender Turing is a cloud-based software platform for call center quality management. A real-time dashboard allows supervisors and managers to monitor performance with live updates. The displayed metrics include call volume, average handle time, first call resolution, customer satisfaction scores and agent availability. Automated pre-scoring of calls and chats shortens quality reviews, and flexible filters allow a small sample to be selected instead of every conversation. Scorecards can be created and edited without engineering support. The interface is offered in more than ten languages.
The Recognition
About the Bronze A' Design Award
Ender Turing SaaS is a Bronze A' Design Award winner, a highly prestigious recognition granted to outstanding designs distinguished by creativity, ingenuity, and astuteness. Bronze winners are amply skillful and strikingly creative artifacts that authenticate the vast experience, imagination, and resourcefulness of their designers. Ender Turing SaaS is expected to be a highly regarded, admired, and cherished object that is notably professional and innovative. This Bronze A' Design Award-winning design incorporates best practices in art, science, design, and technology, and is excellent for its attention to detail. Ender Turing SaaS splendidly satisfies needs, touches desires, charms feelings, and appeals to curiosity.
Interviews
Design Interview
What is the main principle, idea and inspiration behind your design?
The core principle guiding the design of Ender Turing is to create an intuitive and efficient user experience that leverages AI to enhance call center operations. Inspired by the potential of AI to transform customer interactions, the design focuses on clarity, accessibility, and user empowerment. By integrating advanced analytics seamlessly into the user interface, we aim to provide users with actionable insights without overwhelming them.
What has been your main focus in designing this work? Especially what did you want to achieve?
The primary focus was to ensure that complex AI-driven analytics are presented in a user-friendly manner. The goal was to enable call center managers and agents to easily access and interpret data to improve performance and customer satisfaction. Achieving a balance between sophisticated functionality and simplicity was paramount.
What are your future plans for this award winning design?
Future plans include iterative enhancements based on user feedback, integrating more advanced AI capabilities, and expanding the platform's adaptability to various industries beyond call centers. Continuous improvement will ensure the design remains at the forefront of user needs and technological advancements.
Grand Interview
Your innovative approach to transforming call centers through Ender Turing SaaS has earned recognition with the Bronze A' Design Award - could you share the journey that led to developing this groundbreaking AI-powered solution?
It all started with recognizing the gaps in traditional call centers — like inefficient processes and missed opportunities to improve customer satisfaction and sales conversion rates. We focused on building practical AI tools like real-time speech recognition and agent assist to make life easier for agents and deliver better outcomes for customers. Working closely with users and refining the solution along the way helped us create something that truly works. Winning the Bronze A' Design Award is a great acknowledgment of that effort.
The real-time dashboard in Ender Turing SaaS provides comprehensive monitoring of call center KPIs - what inspired your decision to focus on these specific metrics, and how did you determine which data points would be most valuable for supervisors?
The decision to focus on specific metrics came from conversations with call center supervisors and other management roles who shared their biggest challenges — like tracking agent performance, spotting trends early, and ensuring customer satisfaction in real time. We identified the most common pain points and aligned the dashboard with actionable data, like customer sentiment, average handling time, agent adherence, etc. The goal was to give supervisors the insights they need without overwhelming them.
Given that Ender Turing SaaS analyzes customer interactions in 24 languages, how did you approach the complex challenge of ensuring accurate sentiment analysis and scoring across such diverse linguistic contexts?
We tackled this challenge by combining advanced natural language processing models with language-specific customizations. Each language required careful tuning to account for nuances like tone, context, and cultural differences. Collaboration with native speakers and leveraging multilingual datasets ensured we captured sentiment accurately. Continuous testing and feedback loops helped refine the models, ensuring consistency in analysis and scoring across all 24 languages.
Behind the Design
Press Kit
Credits, team members and technical details provided by the designer.
- Unique Properties
- A real-time dashboard allows supervisors and managers to monitor call center KPIs and agent progress with live updates. It displays metrics such as call volume, average handle time, first call resolution, customer satisfaction scores, and agent availability. This helps identify areas of improvement, detect issues, and optimize call center performance through proactive management and data-driven decision-making, leading to improved efficiency, customer satisfaction, and business outcomes.
- Dimensions & Packaging
- The primary function of Ender Turing engine is to help users create and train AI models that can understand and generate human-like language. The platform provides a range of NLP capabilities, including text classification, sentiment analysis, entity recognition, language translation, and text summarization, among others. Users can build custom models using Ender Turing's drag-and-drop interface or integrate pre-trained models into their applications using the platform's API.
- Tags
- Artificial intelligence (AI), Natural language processing (NLP), Machine learning, Text classification, Sentiment analysis, Data processing, Text summarization API, Cloud-based platform, Language modeling, Text mining, Call center, Scoring
- Production Technology
- We used a data-driven design approach to gather feedback for our design, which involved observing and interviewing customers of the product. All of our decisions were based on identifying user pain points and areas of frustration. As a result, we developed a product solution that eliminates most pain points for call center supervisors, increases their productivity, reduces stress and frustration, and features an intuitive UX interface covered with more than 10 language options.
- Design Challenge
- Experiments were done to test hypotheses and validate design decisions. We found that our users are non-technical and prefer a more prominent communication style. We avoid using complex logic constructions and heavy interface decisions. Our UX solutions are continuously simplified.
- Research
- As we maintain ongoing communication with our end users, including data center supervisors and stakeholders, we have collected data through a range of research methods, such as interviews, surveys, and observations.
This has allowed us to gain valuable insights into usesr needs, preferences, and behaviors, which will inform the design of effective solutions that meet their specific requirements. - Inspiration
- Call centers handle up to 1000 calls per agent per day. Measuring and analyzing this data with metrics similar to those used by humans is crucial to improve client service and call center productivity. A productive call center saves businesses revenue and promotes polite and friendly communication with customers, enhancing a business's reputation, improving customer satisfaction, and increasing their overall quality of life.
- Project Duration
- The project started in June 2020 in Tallinn, Estonia. The Design for the Project started at January 2022 and still developing and enhancing. Product was nominated as winner at Latitude59 pitching competition in May 2022, Tallinn, Estonia and took 2nd place at Infoshare Startup Contest where been selected among 500 startups from all over the world in October 2022, Gdansk, Poland.
- Operation Flow
- Our solution provides a 20-fold increase in speed for scoring calls and chats. This is made possible by automated AI pre-scoring and call center quality assurance. Using flexible filters, you can randomly select only a small number of calls and chats for quality monitoring, rather than monitoring all of them.
Moreover, our system allows for flexible setup of scorecards with no limitations. This means that you will no longer need engineers or Excel sheets to modify or create new scorecards. - Patents
- Scientific publications:
1. Transferability Evaluation of Speech Emotion Recognition Between Different Languages
January 2022
DOI:10.1007/978-3-031-04812-8_35
In book: Advances in Computer Science for Engineering and Education (pp.413-426)
Ievgen Iosifov
Olena Iosifova
Oleh Romanovskyi
Vladimir Sokolov
2. Automated Pipeline for Training Dataset Creation from Unlabeled Audios for Automatic Speech Recognition
July 2021
DOI:10.1007/978-3-030-80472-5_3
In book: Advances in Computer Science for Engineering and Education IV (pp.25-36)
Oleh Romanovskyi
Ievgen Iosifov
Olena Iosifova
Vladimir Sokolov
3. Analysis of Automatic Speech Recognition Methods
January 2021
Conference: Cybersecurity Providing in Information and Telecommunication SystemsAt: Kyiv, Ukraine
Olena Iosifova
Ievgen Iosifov
Vladimir Sokolov
Oleh Romanovskyi
Igor Sukaylo
4. Sentence Segmentation from Unformatted Text using Language Modeling and Sequence Labeling Approaches
October 2020
DOI:10.1109/PICST51311.2020.9468084
Conference: 2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S&T)
Ievgen Iosifov
Olena Iosifova
Vladimir Sokolov
5. Methods and components of natural language processing
August 2020 Adaptive automatic control systems 1(36):93-113
DOI:10.20535/1560-8956.36.2020.209780
Olena Iosifova
Ievgen Iosifov
Oleksandr Rolik
6. Techniques Comparison for Natural Language Processing
June 2020
DOI:10.5281/zenodo.3895814
Conference: 2nd International Workshop on Modern Machine Learning Technologies and Data ScienceAt: Lviv-Shatsk, Ukraine
Olena Iosifova
Ievgen Iosifov
Oleksandr Rolik
Vladimir Sokolov
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