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AI agents for companies

Fourteen tasks, five components, one shared approach

T-NEX builds AI agents and custom software for companies in Malaysia, for each of the 14 tasks in this register, from customer service and accounting to manufacturing and clinic administration. The agents work with a company's own documents and systems: they answer enquiries, read and route documents, move data between systems and produce reports. They are built on T-NEX's own components for knowledge assistants, document processing, chatbots, workflow automation and AI reporting.

Discuss your task and starting pointExplore the details
AI agents for 14 tasks
  1. 01What the agents take on across the 14 tasks
  2. 02Five components of our own and one approach for all tasks
  3. 03More providers for these tasks in Malaysia

Aligned with your processes

In daily work

What the agents take on across the 14 tasks

Each task has its own page, and the cards below this text lead there. Here is a first grouping by type of work. We decide which task comes first as part of the project.

  • Customers and enquiries: customer service, marketing and sales, financial services and healthcare. The agents answer enquiries from the company's own documents, prepare quotations and application documents and organise forms. In healthcare they support administration, not diagnosis.
  • Office processes: accounting and finance, process automation, HR and recruitment. The agents read and route documents, pass data to other systems, prepare approvals and track deadlines.
  • Analysis and operations on site: data analytics and forecasting, manufacturing and logistics, buildings and energy. The agents combine figures, answer questions on order and stock data in natural language, process inspection records and freight documents and produce consumption and maintenance reports.
  • Software, operation and onboarding: AI software development, AI infrastructure and cloud operation, AI consulting and governance, and training for teams. This covers applications built to order, running agents in a cloud account, a start with rules for data and approvals, and training teams on their own use case.
Solutions and services

The right solutions for your team.

Overview

Five components of our own and one approach for all tasks

T-NEX uses the same components for all 14 tasks. Which of them an agent gets follows from the task. The AI chatbot answers questions from approved documents with source references. AI knowledge management keeps sources, responsibilities and access rights together. Document AI recognises the required details and places them next to the original so the business team can check them. AI reporting turns a business question into a dashboard on the connected data.

Workflow automation separates fixed rules, AI suggestions and approvals. The T-NEX solution pattern for workflow automation is a concept example; the concrete system actions are developed only for your operation. Where no component fits, T-NEX builds custom software, and we set up the operating environment as part of hosting and operations.

The approach is the same for every task. A defined use case comes first. An AI pilot with a measurable goal shows on your sample data what can be improved. Data access, approvals and logging are settled before the agent works with your data. A successful pilot is not yet a finished production solution.

Overview

More providers for these tasks in Malaysia

The register of AI providers in Malaysia lists further providers for these 14 tasks. The T-NEX task pages describe only what T-NEX itself offers.

The workflow

How we introduce the solution.

  1. 01

    Choose a use case: From the 14 tasks we begin with a defined case that has a clear input and a result that can be checked, and for which reliable documents and responsible people exist. For a first conversation, a description of the process and the types of data involved is enough.

  2. 02

    Set the rules: Which sources the agent may use, who may see what, where a person signs off and what is logged are settled before any data is connected. For the test, too, it is decided beforehand which data may be used.

  3. 03

    Pilot with a measurable goal: Goal, scope and success criteria are fixed before the build. The business team checks errors and limits as well as the most convincing examples, and the effort for corrections is recorded.

  4. 04

    Operation: Based on the measured results, you decide whether the solution is extended or the task is changed. Responsibilities, access and handover are settled before operation, and support and response times are agreed for the specific application.

FAQ

Questions about the solution

Do I have to choose one of the 14 tasks?

Not for the first conversation. The tasks are there for orientation and are not a fixed package. Whether your use case belongs to one task or touches several, we clarify together. Actual customer records or confidential documents are not needed for that.

Is workflow automation a finished product?

No. The T-NEX solution pattern for workflow automation is a concept example of how a workflow can be designed, and the concrete system actions are developed for each company's own processes. A successful pilot is not yet a finished production solution either. At the end of the pilot, we list what is still missing before operation as next steps.

Does an agent access all the data in my company?

No. The agent uses only sources that were approved before connection. Access groups define which users may use which content, and the test checks whether different users actually receive only the information intended for them. We decide for each use case which content an AI model may receive, and what is logged for the process is fixed beforehand.

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Which task would you like to solve next?

Bring a concrete task. Together, we will define what the application needs to do.

Discuss your task and starting point