Insights into AIGC

Insight into what AIGC is

ContextInsight AIGC is a knowledge management and content generation platform designed for companies in the life sciences sector.

It belongs to the Mailuo Huidu system; it is not a consultation tool designed to provide diagnostic or treatment recommendations to patients.

Product positioning

Main functions

• Provide unified management of enterprises’ multi-modal content assets.
• Business tags are automatically generated for knowledge content.
• Generate a content outline based on the title and related documents.
• Generate PPTs automatically based on an outline.
• Editable graphic and text content is generated through dialogue.
• Perform one-click summarization and translation for a single file.
• Ask questions and answer them regarding documents, PPTs, as well as audio and video materials.
• Provide evidence from the knowledge base to answer.
• Automatically breaks down the content and generates review comments.
• Detect prohibited terms related to advertising laws as well as custom rules.
• Connects the creators with the reviewers in the collaboration process.
• Personalized content delivery is achieved by utilizing HCP tags.

Enterprise-level intelligent knowledge base

The knowledge base serves as the factual foundation for generation, question-answering, and review, and it is also crucial for the quality of projects.

• It can receive documents, PPTs, graphics, as well as audio and video materials.
• Parse, tag, and manage content in a unified manner.
• Assign permissions by department, product, disease, and purpose.
• Record the version, source, and validity period of the content.
• Tags and associations are continuously maintained based on business feedback.
• It provides a traceable basis for subsequent generation and review.

Tutorial on building a knowledge base

1. Identify business objectives, the initial use cases, and the responsible departments.
2. Review literature, guidelines, training materials, and marketing content.
3. Verify the rights, version, and expiration date of each document.
4. Remove duplicate, expired, and unverifiable files.
5. Create tags for diseases, products, audiences, and channels.
6. Configure permissions for viewing, editing, generating, and approving.
7. Test retrieval and evidence return using real-world problems.
8. Establish processes for feedback on updates, invalidations, and errors.
9. Complete medical, legal, and security inspections before going live.
10. Continuously monitor knowledge coverage and usage effectiveness.

Support for multimodal content

Intelligent outline generation

After the user enters a title, selects their requirements, and attaches relevant files, the system generates an editable outline of the content.

• First, clarify the audience, channels, and purpose of the content.
• Only files directly related to the task are associated.
• Each key conclusion must be supported by evidence.
• Manually adjust the structure, focus, and order of presentation.
• Remove inferences that are not supported by the knowledge base.
• Enter PPT or image generation only after confirmation.

Fully intelligent PPT generation

After the outline is confirmed, the platform breaks down the associated files and combines the old and new pages and elements to create a PPT.

1. Select the approved outline and related materials.
2. Specify the purpose, number of pages, language, and target audience.
3. Select a PPT template preset by the company.
4. After generation, verify the medical information and data page by page.
5. Check the charts, images, and references.
6. Add the necessary statements and scope of application.
7. Submit for medical, legal, and compliance approval.
8. After approval, it can be used for internal or external dissemination.

Dialog-based image and text generation

The graphic-text module reorganizes the content of the knowledge base into more flexible articles, materials, or communication content.

One-click summary

The one-click summary is used to quickly understand the key information and structure of a single file.

• Confirm whether the documents are complete before drafting the abstract.
• Distinguish between the research purpose, methods, results, and conclusions.
• Retain the sample size, endpoints, and constraints.
• Do not turn the author’s conclusions into universal facts.
• The key data is returned in its original form for item-by-item verification.

One-click translation

The platform supports the translation of individual files in both Chinese and English, and it is also possible to translate certain paragraphs within conversations.

• Create a glossary of terms for drugs, diseases, and endpoints.
• Retain doses, units, abbreviations, and numbers.
• Check the tables, footnotes, and figure captions separately.
• Key content is reviewed by bilingual medical personnel.
• Translation does not change the evidentiary status of the original text.

Multimodal intelligent question answering

Users can ask questions regarding a single file or the entire knowledge base, and view the evidence corresponding to the answers.

Tracing the origin of evidence

Answers and review comments can be linked to the source documents in the knowledge base, allowing users to return to the original text for further verification.

• Check whether the evidence supports the current conclusion.
• Check whether the reference omits any constraints.
• Confirm the file version and effective date.
• Distinguish between internal materials, public documents, and expert opinions.
• Record the reasons for the final acceptance or rejection.

On AI hallucinations

By restricting the models to respond to and generate content based on the company’s knowledge base, the platform aims to reduce the presence of unfounded content.

Database constraints cannot guarantee absolute accuracy; medical content may still contain errors due to issues in retrieval, parsing, or comprehension.

• The knowledge base itself may be outdated or contain conflicts.
• The model may cite correct information but draw incorrect conclusions.
• Details may be lost in the parsing of tables, images, and audio/video.
• If there is no evidence, the request should be declined or transferred to a human agent.
• High-risk content must be reviewed by professionals.

Intelligent review

Intelligent review breaks down the content, matches it with knowledge bases and rules, and generates identifiable annotations and evidence.

• Review locally uploaded files.
• Review the online PPT generated by the platform.
• Identify prohibited terms related to the Advertising Law.
• Apply enterprise-customized approval rules.
• Attach traceability documents to each annotation.
• Click the annotation to navigate to the corresponding content section.
• Submit the results to the reviewers for a second review.

Tutorial for Intelligent Review Usage

1. Select the currently valid knowledge base and review rules.
2. Upload a local file or select an online PPT.
3. Confirm the product, audience, channels, and regions.
4. Initiate content breakdown, fact comparison, and rule detection.
5. Review the annotations, evidence, and locations one by one.
6. Distinguish between factual errors, risk warnings, and formatting issues.
7. The decision is made by medical, legal, or compliance personnel.
8. Review again after making the changes and save the version history.
9. It can only be released or distributed after formal approval is obtained.

Prohibited words and custom rules

Team collaboration

The platform integrates creation and review into the same process, thereby reducing the need for files to be transferred back and forth between various systems.

• Configure different permissions for creators, reviewers, and administrators.
• Record content, annotations, revisions, and approved versions.
• Re-approve the settings for high-risk modifications.
• Retain the release version and evidence snapshots.
• Avoid using shared accounts to circumvent responsibility tracking.

Applicable departments

HCP content distribution

After content approval, it is possible to use HCP tags to match audience interests and deliver personalized messages.

• The origin and purpose of labels must be legal and transparent.
• Only the version that has passed approval is used.
• Control the display range based on channel restrictions.
• Monitor metrics related to reach, content, and customer feedback.
• Do not consider model recommendations as medical diagnoses.
• Regularly evaluate label bias and incorrect associations.

Data security and permissions

• Classification and grading of medical data, marketing data, and personal data.
• Grant the minimum permissions required based on roles and business needs.
• Sensitive data is masked or anonymized before being stored.
• Log download, generation, review, and distribution operations.
• Define the data processing boundaries for external models and services.
• Develop plans for backup, recovery, data breaches, and service disruptions.
• The contract specifies data ownership and procedures for exiting the agreement.

Price and procurement methods

The information below was verified on August 31, 2026; the official website does not disclose the prices of the standard packages.

The final cost, deployment, taxes, acceptance procedures, and service commitments shall be subject to the official quote and contract.

Apply for a trial and demonstration

1. Organize the company’s background, departments, and target use cases.
2. Prepare representative content samples after desensitization.
3. Apply for a product trial or demonstration.
4. Manufacturers are required to demonstrate the entire process using real tasks.
5. It records the outcomes of generation, Q&A, review, and tracing.
6. Evaluate security, interfaces, permissions, and operational requirements.
7. Define the pilot scope, indicators, budget, and timeline.
8. Expand the scope of procurement after the pilot is successful.

Purchase acceptance criteria

API and open-source status

The ability to connect to external large models and provide enterprise interfaces does not mean that the Nuo Mai Hui Du platform itself is open source.

Usage restrictions

• The product does not provide diagnostic or treatment recommendations for patients.
• Knowledge base constraints cannot completely eliminate generation errors.
• AI review cannot replace medical, legal, and compliance approvals.
• Expired knowledge directly affects the quality of Q&A and content generation.
• Personalized distribution must comply with data and marketing rules.
• Prices, deployment, and interfaces require confirmation at the project level.

Frequently Asked Questions

Insight into which companies are suitable for AIGC?

Suitable for marketing, medical, digital, sales, and compliance teams in pharmaceutical companies, equipment manufacturers, and other life science firms.

Insight into what content can be generated by AIGC?

It is possible to generate editable outlines, PPTs, and text with images based on the company’s knowledge base, and it also supports summarization and translation.

Can ContextInsight AIGC be used to answer questions related to medical literature?

Supported: It allows questions and answers regarding documents, PPTs, audio and video materials, and provides evidence from the knowledge base.

Can AI-based content moderation replace human approval?

No, the system is used to identify risks and provide evidence; ultimately, it is still up to medical, legal, or compliance professionals to make a decision.

Can ContextInsight AIGC prevent AI hallucinations?

Knowledge base constraints help reduce risks, but they cannot guarantee absolute accuracy; important conclusions must be verified against the original source.

How much does ContextInsight AIGC cost?

The official website does not list standard packages; the costs are determined based on licensing, knowledge bases, models, review services, integration options, and various service plans.

Is ContextInsight AIGC an open-source platform?

No, at present there is no official open-source repository for a complete platform, and enterprise APIs do not imply that the product is open source.