Designveloper

Designveloper An AI-driven software development company in Vietnam, providing web and app solutions to businesses since 2013.

Designveloper is the leading software development company in Ho Chi Minh City, Vietnam, founded in early 2013 with a team of professional and enthusiastic Web developers, Mobile developers, UI/UX designers and VOIP experts. Following a systematic approach, we intend to deliver the best and most cost-effective software services to our clients.

Google has launched Gemini 3.8 Flash, a new model focused on programming and AI agents through deeper reasoning and mult...
04/09/2026

Google has launched Gemini 3.8 Flash, a new model focused on programming and AI agents through deeper reasoning and multi-step task ex*****on.

For coding tasks, it can analyze problems, write code, use supporting tools, review results, and refine its output. Google says it outperforms Gemini 3.7 Flash on software engineering evaluations and performs strongly on finance and legal AI agent benchmarks.

Pricing remains at $0.75 per million input tokens and $3.75 per million output tokens. However, the model may use more tokens to achieve higher performance, potentially increasing the actual cost.

Google has also introduced Gemini 3.8 Flash Cyber for governments and trusted partners. Combined with CodeMender, it can help detect and fix security vulnerabilities. Both versions include safeguards against misuse in CBRN and cyber offense-related domains.

According to Google, these upgrades aim to better support developers, automate software workflows, and enable more capable AI agents.

Does every business need custom software?The answer is: not always.If your needs are common, ready-made software can hel...
03/09/2026

Does every business need custom software?

The answer is: not always.

If your needs are common, ready-made software can help you launch quickly, reduce costs, and get started with ease.

However, when your business has unique processes, needs to connect multiple systems, or plans to add more features in the future, off-the-shelf software may become limiting.

That is when custom software can be a better option. Your business gets a system designed around its specific needs, from features and user interface to security and scalability.

Before making a decision, ask yourself:
• Does your current software require too much manual work?
• Do your systems sync data effectively?
• Do you need unique features to gain a competitive advantage?

If the answer is “yes,” it may be time to consider a solution built specifically for your business.

Designveloper provides end-to-end custom software development services, from requirements analysis and design to development, deployment, and maintenance.
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Contact us:
📞 +84 328 08 0606
📩 [email protected]

A love story ruined by debugging 😖
27/08/2026

A love story ruined by debugging 😖

You do not need to be an AI expert to understand the language of AI.Start with these 15 terms, moving from familiar conc...
26/08/2026

You do not need to be an AI expert to understand the language of AI.

Start with these 15 terms, moving from familiar concepts to more advanced ideas:

1. Artificial Intelligence (AI): Technology that performs tasks normally requiring human intelligence.
2. Machine Learning: AI that learns patterns from data instead of fixed rules.
3. Generative AI: AI that creates new text, images, audio, video, or code.
4. Large Language Model (LLM): A model trained to understand and generate human language.
5. Prompt: The question or instruction you give to an AI.
6. Token: A small unit of text that an AI model processes.
7. Context Window: The amount of information an AI can consider at one time.
8. Hallucination: When AI confidently provides incorrect or invented information.
9. Multimodal AI: AI that can work with text, images, audio, and video.
10. RAG: A method that helps AI retrieve external information before answering.
11. AI Agent: AI that can plan, use tools, and take actions toward a goal.
12. MCP: A standard that helps AI connect to external tools and data sources.
13. Mixture of Experts (MoE): A model that activates selected specialized components for each task.
14. World Model: An internal representation that helps AI predict how an environment may change.
15. Artificial General Intelligence (AGI): A proposed form of AI with broad, human-like intellectual abilities.

These are only a small selection of the terms shaping how we understand and use AI.

In the images below, you will find the full collection of Must-Know AI Terms, organized into six levels from everyday basics to advanced and future concepts.

Save this post and explore the terms at your own pace. Which AI term would you like to understand better?

Training an AI model is not simply about feeding data into an algorithm. It is a process of turning a business need into...
25/08/2026

Training an AI model is not simply about feeding data into an algorithm. It is a process of turning a business need into a system that can be measured, deployed, and operated reliably.

Before exploring the process in the infographic, here are the key considerations at each step:

Step 1: Define the Problem
Do not begin by asking, “Which model should we use?” First, clarify what input the AI will process, what output it should produce, and what impact an incorrect result could have.

Step 2: Choose the Right Approach
Not every AI problem requires model training. Rules, existing AI APIs, or RAG may be faster and more cost-effective. Fine-tuning is appropriate when a product needs consistent behavior that existing solutions cannot deliver reliably.

Step 3: Prepare the Data
Data quality matters more than volume. Examples should represent real-world situations, follow consistent labeling guidelines, and include rare but high-risk cases.

Step 4: Train the Model
Training usually involves multiple experiments. Every change to the data, configuration, or model should be documented so the results can be compared and reproduced.

Step 5: Evaluate with a Pilot
Do not rely only on average accuracy. Evaluate critical errors, response time, operating costs, and how much human review is still required.

Step 6: Integrate It into the Product
The model must connect securely with data, permissions, logging, and user support workflows. The team should also prepare a rollback plan in case a new version performs poorly.

Step 7: Monitor and Improve
Model performance may decline as data and user behavior change. Monitoring, feedback collection, and retraining are therefore essential parts of the product lifecycle.

Explore the infographic to see the complete journey from an initial idea to an AI model ready for production.

21/08/2026

OpenAI Just Paused Part of Its AI Development. What Happened?

AI is quietly creating a new competitive gap between businesses. While some still spend hours on repetitive tasks, other...
20/08/2026

AI is quietly creating a new competitive gap between businesses. While some still spend hours on repetitive tasks, others are using AI to complete them in minutes.

According to McKinsey’s The State of AI 2025 report, 88% of surveyed organizations are already using AI in at least one business function. From customer service and data analysis to software development, AI is helping businesses work faster, improve accuracy, and optimize resources.

Actually, businesses do not need an AI tool that merely performs tasks on command. They need an AI product that understands the essence of their business, becomes an integral part of their operations, adapts to their workflows, solves the right problems, and delivers measurable results.

Designveloper turns those needs into practical solutions through AI Software Development, Generative AI, and AI Chatbot Integration. Each solution is tailored to the business, easy to use, compatible with existing systems, and ready to scale.

Discover how Designveloper can turn your AI idea into a real-world product in the comment below👇🏻

What is the correct answer? 🧐
19/08/2026

What is the correct answer? 🧐

A high-accuracy AI model does not automatically mean a reliable AI system.In production, we need to evaluate more than j...
19/08/2026

A high-accuracy AI model does not automatically mean a reliable AI system.

In production, we need to evaluate more than just the final answer:
- Can the system retrieve the right information?
- Does it stay grounded and avoid hallucinations?
- Can a coding agent complete tasks with minimal retries?
- Can multiple agents coordinate and hand off work correctly?

That’s why AI evaluation should be designed around what we need to prove:
Task → Dataset → Metrics → Thresholds → Failure Analysis → Regression Testing

LLM-as-a-Judge can be useful, but it should not be the only signal. Unit tests, human review, and real-world production metrics matter too.

Building an AI system is only half the job. Proving that it works reliably is the other half.

What metrics do you use to evaluate your AI systems?

14/08/2026

How much does it cost to develop an AI app?

Address

53-55-57 Pho Duc Chinh Street, Ben Thanh Ward
Ho Chi Minh City
700000

Opening Hours

Monday 09:00 - 18:00
Tuesday 09:00 - 18:00
Wednesday 09:00 - 18:00
Thursday 09:00 - 18:00
Friday 09:00 - 18:00

Telephone

+84886017191

Website

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