AI agents for 14 tasks
The 14 tasks for which T-NEX builds AI agents, with the shared components, a pilot with a measurable goal and the rules for running the agents.
Learn moreAI agents for companies
Support the administrative work of clinics, practices and laboratories
T-NEX builds AI agents for the administration of clinics, practices and laboratories: answering appointment enquiries, organising forms and records, preparing billing documents and making internal procedures searchable. The agents support administration, not diagnosis.
- 01What the agents take on in administration
- 02Support for administration, not for diagnosis
- 03Components for enquiries, documents and procedures
Aligned with your processes
In daily work
What the agents take on in administration
The starting point is the paperwork that clinics, practices and laboratories already produce. Which area we start with is decided together in the project.
- Answer appointment enquiries: questions about opening hours, how a visit works or which documents to bring are answered from your own information sheets.
- Capture appointment requests and ask for missing details, so that the team receives a complete case.
- Sort forms: incoming forms are assigned by document type and the required details go into fixed fields. Unclear passages go to a person for review.
- Organise records: documents are assigned to the right case and missing items become visible. The medical assessment stays with your clinical staff.
- Prepare billing documents: the agent collects what is needed for billing and flags missing details before the documents move to the next step.
- Make procedures searchable: staff ask about a process and receive the valid instruction with its source reference.
Overview
Support for administration, not for diagnosis
The agents do not make diagnoses and do not assess findings. Medical decisions stay with your clinical staff. If an agent cannot assign something with confidence, it refers the case to a person.
Health data is particularly sensitive. Before anything is connected we define which sources an agent may use and who may see what. Which details an AI model may receive, and whether personal data is needed for that at all, is recorded in the project documents, as are log contents, retention and who gets access for set-up and support. We also clarify in advance which data may be used in testing.
An agent does not answer freely when there is no sourced answer. It says that the information is insufficient, asks a clarifying question or hands over to the responsible person. Whether this works reliably is shown by a pilot on ordinary enquiries, alternative wording and questions without a matching answer, before the agent goes into operation.
Overview
Components for enquiries, documents and procedures
Appointment enquiries and questions about processes are answered by the AI chatbot with source references. It finds maintained answers and shows their stored source location. A supplementary RAG function can compose answers from document passages; that stage is developed and tested as a separate scope.
For forms, records and billing documents we use Document AI. It recognises the document type and the required details, places them next to the original and presents unclear passages for review. Only after that review is the data passed to the intended target system, by file or interface.
For the procedures we set up AI knowledge management: content owners are assigned to each source, the change history stays traceable, and a changed instruction can trigger a fresh review of linked knowledge pages and test questions. Handover to a person follows the principles of workflow automation, with a work queue and a log. The specific system actions are developed for each company.
Overview
More providers for this task in Malaysia
The register of AI providers in Malaysia lists further providers for this task, including clinic and practice software, medical documentation, telemedicine, health benefits for employers, and pharma and clinical trials. This page describes only what T-NEX builds itself.
All 14 tasks for which T-NEX develops AI agents are in the overview.
The workflow
How we introduce the solution.
- 01
Choose a use case: We begin with a defined administrative area, such as the most frequent appointment enquiries or one type of form, and check whether reliable material and responsible content owners exist.
- 02
Set data access and approvals: Released sources, access roles, the details a model may receive, log contents and retention are fixed before any patient or record data is connected. The test data is agreed in advance as well.
- 03
Pilot with a measurable goal: Together with your administration team we define what a correct result is and which errors are not acceptable. We measure correctly captured details, whether answers point to the right source, correction effort and the human intervention needed.
- 04
Operation and expansion: Only after the pilot do we extend the document collection, the audience or further tasks. Questions without an answer expose gaps in the knowledge base and have a recipient, and new or changed procedures go through a release step.
FAQ
Questions about the solution
Does the agent make diagnoses or assess findings?
No. The agents support administration. They do not make diagnoses and do not assess findings; that stays with your clinical staff. The agent assigns records to a case and makes missing items visible, nothing more.
Which patient data can the agent see?
Only the sources released for the audience concerned. We clarify the access roles before sources are connected. Whether and which personal details an AI model receives, and where data is processed, follows from your requirements and is documented before use.
Can the agent book appointments or submit billing?
That requires a connection to the system concerned and is part of the scope only if it explicitly belongs to the process. Additional system actions are planned separately. Without a connection, the agent captures appointment requests and prepares billing documents, while booking and submission stay with your staff.
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AI chatbot for companies with source references
Internal knowledge search and chatbots built around your content: approved answers or RAG with a language model. T-NEX scopes access, data and implementation.
Learn moreDocument AI
Document processing as a custom project: define required fields, test extraction against examples and connect the next step in your workflow.
Explore serviceWhich task would you like to solve next?
Bring a concrete task. Together, we will define what the application needs to do.
Discuss your administration use case