Ender Turing Software voor Klantinteractieanalyse door Lidiia Suslova

Het ontwerp Ender Turing Software voor Klantinteractieanalyse door Lidiia Suslova is een hoog aangeschreven winnaar van de zeer prestigieuze 2026 A' Design Award in IJzer in de competitiecategorie Software Ontwerp.

IJzerSoftware· 2026

Ender Turing Software voor Klantinteractieanalyse

door Lidiia Suslova

Opdrachtgever: Ender Turing

Winnaar van de A' Design Award in IJzer in de categorie Software

6,731

Geverifieerde Prijswinnaar

Verifieer de prijsstatus voor #157760

Bezoek Website Bekijk bij A' Design Award Persbericht Award Badge

Kleuren

Het Ontwerp

Over Ender Turing Software voor Klantinteractieanalyse

Ender Turing is een cloudgebaseerd softwareplatform voor de analyse van klantenservicegesprekken. Gesprekken en chats worden automatisch beoordeeld door kunstmatige intelligentie, waardoor kwaliteitsborgingsroutines worden verkort. Natuurlijke taalverwerking ondersteunt tekstclassificatie, sentimentanalyse, entiteitsherkenning, vertaling en samenvatting. Aangepaste modellen kunnen worden gebouwd met een drag-and-drop-interface, en vooraf getrainde modellen kunnen aan andere applicaties worden toegevoegd. Flexibele filters, aangepaste scorekaarten en datavisualisatie helpen supervisors bij het monitoren van interacties.

De Erkenning

Over de A' Design Award in IJzer

Ender Turing Software voor Klantinteractieanalyse is winnaar van de A' Design Award in IJzer, een prestigieuze erkenning die wordt toegekend aan goede ontwerpen die voldoen aan de professionele en industriële eisen die worden verwacht van goed ontworpen creaties. Winnaars in IJzer tonen grote vaardigheid, hoge specialisatie, deskundig inzicht en het creatieve vermogen van hun makers. Ender Turing Software voor Klantinteractieanalyse wordt verwacht een hooggewaardeerde, bewonderde en gekoesterde creatie te zijn die praktisch en innovatief is. Dit ontwerp dat de A' Design Award in IJzer heeft gewonnen, integreert de beste praktijken uit de sector en heeft bekwame technische kenmerken die verbonden zijn met knowhow en talent. Ender Turing Software voor Klantinteractieanalyse wordt gerespecteerd om zijn grondigheid en is ontworpen om verbeteringen van de levenskwaliteit te bieden die helpen de wereld een betere plek te maken.

Achter het Ontwerp

Perskit

Credits, teamleden en technische details verstrekt door de ontwerper.

Unieke Eigenschappen: Ender Turing offers unique customer experience solutions, enhancing revenue and loyalty. Real-time analytics on employee-customer interactions empower informed decision-making.

Our AI platform automates QA routines, uncovers business insights, and boosts agent performance through continuous coaching.
Afmetingen & Verpakking: The core purpose of the Ender Turing engine is to facilitate users in crafting and refining AI models capable of comprehending and generating human-like language. This platform offers a comprehensive suite of Natural Language Processing (NLP) capabilities, encompassing tasks such as text classification, sentiment analysis, entity recognition, language translation, and text summarization, among others. Users have the flexibility to construct tailored models through Ender Turing's intuitive drag-and-drop interface, or seamlessly integrate pre-trained models into their applications via the platform's API.
Tags: Artificial intelligence, AI, Natural language processing, NLP, Machine learning, ML, Text classification, Sentiment analysis, Data processing, Text summarization, API, Cloud-based platform, Language modeling, Text mining, Call center, Analysis, Scoring
Productietechnologie: Utilizing a data-driven design methodology, we collected feedback by directly observing and interviewing our product's customers. Our decisions were guided by the identification of user pain points and areas of frustration. The outcome is a product solution that effectively addresses the concerns of business. Leveraging insights gained, our solution drives revenue growth by enabling informed decision-making and strategic planning, enhancing business productivity, reducing stress, and offering an intuitive user experience. Moreover, our interface supports over 10 languages, ensuring accessibility and usability across diverse user bases.
Ontwerpuitdaging: Experiments were conducted to assess hypotheses and validate design decisions. Our findings revealed that our user base consists largely of non-technical individuals who favor a more prominent communication style. Consequently, we refrain from employing complex logic constructions and cumbersome interface designs. Instead, our UX solutions undergo continual refinement to ensure simplicity and ease of use.
Onderzoek: Engaging with end users, including data center supervisors and stakeholders, we collected data via interviews, surveys, observations, and competitive analysis. Our key finding is the potential of call center data analysis to boost revenue through invaluable insights for informed decision-making. This approach unveils user and business needs, guiding tailored solutions.
Inspiratie: Market Demand: Recognizing the growing need for effective CX solutions in various industries.

Efficiency: Seeking ways to streamline processes within contact centers, QA automation, real-time analysis and revelation business insights.

Customer Satisfaction: Understanding the importance of delivering exceptional customer service to foster loyalty and drive revenue growth.

AI Technology: Leveraging advancements in AI and ML to develop innovative solutions that can adapt and evolve over time.
Projectduur: The project commenced its journey in June 2020 in Tallinn, Estonia. Design efforts for the project began in January 2022 and are currently ongoing, with continuous development and enhancement. Notably, the product achieved recognition as the winner at the Latitude59 pitching competition in May 2022, held in Tallinn, Estonia. Additionally, it secured the 2nd place position at the Infoshare Startup Contest in October 2022, hosted in Gdansk, Poland, amidst stiff competition from 500 startups worldwide. Moreover, our team achieved the distinction of Best Seed startup at the Valencia Digital Summit conference in October 2023!
Werkproces: Our solution offers a 20-fold speed increase in scoring calls and chats, powered by automated AI pre-scoring and quality assurance. It also extracts valuable business insights, allowing users to efficiently monitor interactions with flexible filters. With seamless scorecard customization and robust data visualization tools, informed decision-making is empowered. These capabilities optimize operations and enhance customer experiences, contributing to revenue growth.
Patenten: 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
Beeldcredits: Lidiia Suslova