Knowledge & Service Intelligence
Turn enterprise documents, rules, and accumulated experience into traceable intelligent Q&A and customer-service capabilities.
Official corporate website
We build verifiable, deployable, and continuously improvable AI products and solutions around knowledge Q&A, content processing, intelligent assessment, and cross-border operations.
Shenzhen Mizhi Intelligent Technology Co., Ltd.
Capabilities
We organize technology around real workflows: first fix the inputs, outputs, and validation approach, then shape software delivery that can be maintained over time.
Turn enterprise documents, rules, and accumulated experience into traceable intelligent Q&A and customer-service capabilities.
Convert video, document, and web sources into structured content that stays editable, reusable, and deliverable.
Build an extensible exam-assessment loop around scoring, evidence, diagnosis, explanation, and practice.
Turn platform rules, store data, and operating procedures into risk-identification and decision-support tools.
Product portfolio
Some products are ready to explore today; others are delivered as custom solutions within a defined business boundary. Every status reflects the actual current stage.
English editing asset packages from Chinese video
Intelligent marking and learning diagnosis for DSE Mathematics
Structured processing for document and web sources
Enterprise knowledge Q&A with citations, versioning, and quality validation
A RAG service foundation for website and messaging channels
Store risk diagnosis for Mercado Libre sellers
A general intelligent exam-assessment engine
Overseas brand | A collection of calming casual web games
This website is an informational showcase for the company and its products. It does not process user files, exam answers, store accounts, or online payments. Actual product capabilities are defined by the corresponding product site or a mutually confirmed delivery scope.
How we deliver
We break cooperation into confirmable checkpoints so that scope, responsibility, and results stay clear to both sides.
Start by fixing the users, inputs, outputs, acceptance criteria, and risk boundary.
Prefer existing scaffolds and quality gates over building features from scratch.
Prove reliability through tests, citations, logs, or human acceptance review.
Product principles
Four principles guide whether a requirement is worth building, and how far it should go.
Business contact
In your email, please describe the business scenario, the current process, the data you already have, the expected inputs and outputs, and your timeline. We will first assess whether existing capabilities can validate it quickly.