targenio Assistance Platform

targenio Assistance Platform darbina ar targenio

targenio stiprina vidēja lieluma rūpniecības uzņēmumus, izmantojot tehnoloģisko progresu klientu apkalpošanā.<br/>Automatizējam pakalpojumu pieprasījumu apstrādi ar digitālajiem asistentiem starptautiskiem uzņēmumiem automobiļu, aviācijas un mašīnbūves nozarē. Targenio asistenta platforma ļauj organizācijām izstrādāt, izvietot un darbināt adaptīvos palīgus, kas pielāgoti viņu pakalpojumu procesiem.<br/><br/>Mūsu risinājumi nozīmē draudzīgumu, jo digitālajiem palīgiem jābūt tikpat empātiskiem kā cilvēkiem, kuri tos izmanto. Viņi aizstāv brīvību, jo palīgi sniedz atvieglojumu, nenoņemot kontroli. Un tie nozīmē progresu, jo mēs izmantojam mūsdienīgas tehnoloģijas, lai servisa darbu padarītu vieglāku, ātrāku un labāku.

Atklājiet targenio

Kāpēc Automate service processes and scale customer experiences?

The targenio assistant platform digitises and automates customer service processes through modular assistants, integrated AI and flexible workflows. Companies accelerate processes, increase service quality and achieve measurable efficiency gains. Ideal for organisations that want to manage complex service processes in a scalable way.

AI assistant platform interaction diagram

Priekšrocības

The knowledge pool is created dynamically: the assistant searches through data and answers queries. If it cannot find a suitable answer, an expert takes over. Their answer automatically expands the knowledge pool and is immediately available for future use.
Assistants handle standard cases quickly and confidently. They guide customers through processes, provide clear recommendations and increase the first-time resolution rate. Service managers benefit from stable, scalable processes with consistent quality.
Experts are only involved when specialist knowledge is really needed. They correct or supplement answers, thereby further enriching the knowledge pool. This reduces effort, improves quality and takes the pressure off the team.
Engineers configure rules, data flows and integrations. They ensure that the assistant accesses up-to-date information and acts correctly. Changes can be rolled out quickly and with minimal risk.
Trainers analyse case histories, check response quality and optimise decision-making logic. They ensure the continuous development of the system and provide measurably more stable KPIs in the service team.

Piedāvātās iespējas

Task management and task prioritization UI

Digital assistants with AI

The assistants are based on modern language models (LLMs), algorithms and extensive domain knowledge in order to understand natural language and make targeted enquiries.

Workflow diagram for skill orchestration

Adaptive skill architecture

Skills - i.e. specialised skills - are offered in different variants (rule-based, ML-based, mixed, external skills). The degree of automation increases continuously with each new or improved skill.

Low code / no code integration

Users can customise the assistant to their needs via intuitive dashboards and configuration options.

Tasks dashboard with statistics and graphs

Human-machine collaboration

Trainers continuously optimise the quality and efficiency of the assistants via the trainer cockpit. Experts can view relevant information and options for action in the expert view and thus continuously train the assistant.

Incident report form with chat interface

Multi-channel customer interaction

The assistant can be used flexibly and interacts directly with customers via chats, web forms, customer portals or e-mail.

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Making machine service knowledge accessible

Service knowledge is distributed across many systems and tied to individuals. The assistant searches technical data sources, answers machine-specific queries and involves experts when needed. Expert feedback automatically enriches the knowledge base, enabling precise service answers within seconds.