Experience sharing: How far is the distance from buying a DeepSeek all-in-one device to implementing it in real-time application scenarios?

Written by

Silas Grey

Updated on:July-02nd-2025

After the Spring Festival holiday, the AI circle was extremely hot. Deepseek-driven all-in-one machines for various industries emerged one after another. Lao Wang also took advantage of the popularity and was very busy. In recent days, it seems that the popularity has decreased, and I am not as busy as before. When I am free, I have time to write something, so I will write down some of my recent work feelings and share them with you.

Many people feel that the whole world is talking about DeepSeek, and many companies and individuals have introduced DeepSeek all-in-one machines, expecting the "magic effect" of the all-in-one machine. But the reality is that there is still a long way to go from "buying equipment" to "using it well". Today, let's talk about how far this distance is and how to complete this journey efficiently.

Step 1: Buying equipment ≠ being able to use it well - Three core challenges

1. Technical adaptation is not suitable for local conditions

Although DeepSeek all-in-one machine claims to be "out-of-the-box", it may face problems such as hardware compatibility and local knowledge base construction during actual deployment. For example, a chemical equipment manufacturer I served spent two weeks adjusting the adaptation plan because the domestic chip was incompatible with the original system.

Solution key: Choose all-in-one products with compatible hardware and software to reduce the technical adjustment period. You can apply for testing from the product manufacturer and test before paying.

2. The “invisible threshold” of data security

Government affairs, medical care and other industries have extremely high requirements for data privacy. For example, a government affairs system requires that data be processed locally throughout the process and must pass a four-level content security review (such as identifying confidential information and sensitive intent). This requires the all-in-one machine to have built-in end-cloud collaborative protection capabilities.

Key to solving the problem : Choose an all-in-one product with integrated content security components, which supports 99.9% of illegal content identification and secure responses to sensitive issues.

3. “Precise Matching” of Scenario Implementation

Many companies only discovered after purchasing that general models could not meet segmented needs. For example, a city’s 12345 hotline achieved intelligent work order classification by connecting to DeepSeek, but in the early stages, it needed to customize the knowledge base for local policies, and customized development took time.

Key to solving the problem : Choose an all-in-one product that supports "model customization + pre-installed industry knowledge base" to quickly match specific application scenarios.

Step 2: “Practical experience” in shortening the distance

Case 1: The secret to improving government hotline efficiency by 28% After a city in Sichuan introduced DeepSeek to its 12345 hotline, it increased the speed of responding to citizens’ demands by 28% through functions such as intelligent form filling and direct dispatch of work orders. The key lies in:

a. Knowledge base localization: Upload local policy documents and train the model to understand dialects and local processes.

b. End-cloud collaborative architecture: 99% of known issues are handled offline, and risk strategies are updated in seconds when connected to the Internet.

Case 2: "Win-win Model" in Medical Scenarios A hospital in Zhejiang Province connected DeepSeek ( small parameter volume ) to its electronic medical record system, and AI assisted doctors in correcting medical record errors and optimizing treatment plans. Success factors:

a. Lightweight deployment: The memory usage is less than 200M and does not affect the operation of the original system.

b. Human-machine collaborative design: AI only provides suggestions, and the final decision-making power is reserved for doctors.

Step 3: Four keys from “usable” to “easy to use”

1. Selection stage: customized on demand

a. For high-frequency office scenarios (such as meeting minutes and document generation), you can choose DingTalk's "out-of-the-box" solution.

b. Highly sensitive industries (such as finance and government affairs) need to focus on security components. For example, the software of all-in-one machines must have a trusted data traceability function.

2. Deployment phase: small steps and fast progress

First choose a single scenario pilot (such as smart customer service), and then gradually expand it. Avoid spreading the concept too thin .

3. Operational stage: continuous evolution

Based on enterprise feedback, we continuously optimize the model and reduce the “illusion” problem of general models.

4. Ecosystem co-construction: cross-border cooperation

Develop jointly with universities and technology service providers, leveraging the advantageous resources of all parties to create the best implementation solutions for specific application scenarios.

Future Outlook: Technology Inclusiveness and Explosion of Scenarios

As the cost of DeepSeek all-in-one machines decreases, more small and medium-sized enterprises will join the wave of intelligence. It is expected that by 2025, the AI PC replacement wave will accelerate the popularization of equipment, and the real competition will focus on the ability to deeply cultivate scenarios - whoever can transform technology into business value faster will win the future.

Conclusion: From purchase to implementation,DeepSeekall-in-one machine is neither "one-step" nor "out of reach". The key lies in: clarifying needs, selecting adaptation solutions, and gradually releasing value through the closed loop of "pilot-optimization-expansion". As a certain enterpriseCIOsaid: "AIis not magic, but a toolbox-only when used in the right scenario can it turn into real money."