Ender Turing Software ea Tlhahlobo ea Puisano le Bareki ka Lidiia Suslova

Moralo oa Ender Turing Software ea Tlhahlobo ea Puisano le Bareki ka Lidiia Suslova ke mohlodi oa khau e hlomphehang haholo ya 2026 Moputso oa Tšepe oa A' Design Award Mokhahleong oa Tlhodisano oa Moralo wa Softwere.

TšepeSoftwere· 2026

Ender Turing Software ea Tlhahlobo ea Puisano le Bareki

ka Lidiia Suslova

Moreki: Ender Turing

Mohlodi oa Moputso oa Tšepe oa A' Design Award Mokhahleong oa Softwere

6,731

Mohlodi oa Khau ea Netefaditsweng

Netefatsa Boemo ba Khau bakeng sa #157760

Etela Sebaka Sheba ho A' Design Award Tokollo ya Boraditaba Baeche ya Moputso

Mebala

Moralo

Mabapi le Ender Turing Software ea Tlhahlobo ea Puisano le Bareki

Ender Turing ke sethala sa software se thehiloeng lerung bakeng sa tlhahlobo ea lipuisano tsa litšebeletso tsa bareki. Mehala le lipuisano tsa marang-rang li fuoa lintlha ka boiketsetso ke bohlale ba maiketsetso, e leng se khutsufatsang mekhoa ea netefatso ea boleng. Ho sebetsoa ha puo ea tlhaho ho tšehetsa khethollo ea mongolo, tlhahlobo ea maikutlo, temoho ea lintho, phetolelo le kakaretso. Mehlala e ikhethileng e ka hahuoa ka sebopeho sa ho hula le ho beha, 'me mehlala e seng e koetlisitsoe e ka eketsoa ho lits'ebetso tse ling. Lisefe tse feto-fetohang, likarete tsa lintlha tse ikhethileng le pontšo ea data ka litšoantšo li thusa balebeli ho beha leihlo lipuisano.

Kamohelo

Mabapi le Moputso oa Tšepe oa A' Design Award

Ender Turing Software ea Tlhahlobo ea Puisano le Bareki ke mohapi oa Moputso oa Tšepe oa A' Design Award, kananelo e hlomphehang e fuoang meralo e metle e finyellang litlhoko tsa porofeshenale le tsa indasteri tse lebelletsoeng ho lintho tse hlahisitsoeng tse entsoeng hantle. Bahapi ba Tšepe ba bontša bokhoni bo boholo, bokhethehi bo phahameng, kutloisiso ea litsebi le bokhoni ba boqapi ba baqapi ba bona. Ender Turing Software ea Tlhahlobo ea Puisano le Bareki e lebelletsoe ho ba ntho e hlahisitsoeng e hlomphuoang haholo, e ratoang le e ratehang, e sebetsang le e nang le mehopolo e mecha. Moralo ona o hapileng Moputso oa Tšepe oa A' Design Award o kenyelletsa mekhoa e metle ka ho fetesisa ea indasteri mme o na le litšobotsi tsa theknoloji tse nang le bokhoni tse amanang le tsebo le talenta. Ka lebaka la botlalo ba eona, Ender Turing Software ea Tlhahlobo ea Puisano le Bareki e tšoanelehela tlhompho mme e entsoe ho fana ka ntlafatso ea bophelo e thusang ho etsa hore lefatše le be sebaka se molemo.

Ka Mora Moralo

Sete ya Boraditaba

Litlhaku, ditho tsa sehlopha le lintlha tsa botekgeniki tse fanoeng ke moetsi wa moralo.

Boleng bo Ikhethang: 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.
Boholo le Phuthelo: 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.
Lithegi: 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
Theknoloji ya Tlhahiso: 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.
Phephetso ya Moralo: 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.
Dipatlisiso: 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.
Kgothaletso: 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.
Nako ya Projeke: 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!
Tsamaiso ya Mosebetsi: 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.
Diphatente: 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
Litlotla tsa Setshwantsho: Lidiia Suslova