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Applied Artificial Intelligence Services
What is it?
It is the interpretation of digital texts written in free format by means of Natural Language Processing (NLP) algorithms and classification of the same into predefined categories.
What Does It Do?
Digital texts written in free-format, such as e-mails sent to corporate and generic addresses, service desk requests etc. are interpreted and classified according to the content, and are forwarded directly to the relevant person/department.
What are the advantages?
- No manpower required for interpretation and classification
- You only use your workforce to solve/evaluate the relevant incident.
- Every correspondence is certainly evaluated, and the human error rate is close to 0.
- Non-classified correspondence can be taught to the system again with ML and forwarded to positions related to backward analysis.
- Response time to customer demands can be shortened by 80%.
- By meeting the committed SLA values, customer satisfaction is increased.
- All texts are classified and forwarded 24/7 without any interruption.
Response time to customer demands can be shortened by 80%.
Installation & Integration
- No installation or modification is required for any application running on the existing infrastructure.
- Communication is available via web services.
Retrospective texts are analyzed and labeled according to their content and categories. The system can be trained by developing a special ML model for the tagged texts, and the texts sent to the models with a certain performance can be classified according to their types.
It is the interpretation of Natural Language Processing (NLP) algorithms according to free-format texts such as e-mail, instruction, petition, suggestion, event log and service request according to the content of the texts and classification of the same into categories.
These are our advanced technologies deployed on our digital workforce integrated with all estimation and inference like machine learning and artificial intelligence algorithms such as image processing, natural language processing (NLP) from Google, Amazon and Microsoft. You can easily and quickly perform operations such as meaningful data extraction from any image, asset or object recognition, face recognition, popular place or product logo detection, by means of robots. You can use the same features on videos that are stored or streamed. Thus, you can easily search your media, make it discoverable, and give meaning to your existing archives. You can convert your videos to text or add subtitles.
Natural language algorithms use machine learning methods to reveal the meaning of any textual expression. By analyzing social media flows, call center recordings or customer conversations, you can analyze whether text expressions are emotionally positive, negative or neutral. You can classify the expression in any text by interpreting. By interpreting e-mails or correspondence from any channel, you can forward the texts to the relevant units or persons without human intervention.
Thanks to the Text to Speech or Speech to Text algorithms, you voice the written texts or transcribe any speech to text.
You can detect in which language the texts written in more than a hundred and twenty languages language are written, and you can translate the text to the language you want instantly or in batches. You can detect and extract the assets in the text.
You can develop chat or intent bots to be directly integrated with websites, mobile applications, popular messaging platforms, and with the developed bots, you can understand the purpose of the user in the speech environment, extract the date, time, numbers or any type of pre-trained data from the speech text instantly and forward them directly to the robots. It can automatically correct the user's erroneous expressions in the speech or correspondence environment, and the developed bot can be directly integrated with 14 different speech environments. If desired, the developed bot can be integrated with IVR technologies and used in phone calls.
You can automatically compile and deploy cutting-edge machine learning models on structured data faster and at large scale. With this method, you can make predictions and inferences about your processes by utilizing your corporate data to perform critical tasks such as supply chain management, fraud detection, potential customer conversion optimization and increasing customer lifetime value. You can perform your association, data anomaly and trend analysis works on sensor data in an integrated manner with robots. By getting to know your current customers better, you can learn about their preferences, make personalized preference suggestions, gain your customer's trust and increase customer loyalty.