LATEST TECH ARTICLES

Shadow AI was involved in 43% of breach incidents, and 74% of Korean companies name AI as their single largest data security risk. Here is an 8-point checklist a 30–300 person company with no dedicated AI team can run in two weeks.

KEEP AI ON BRAND The Role of AX Hub, Skill, and Governance If AI can't be stopped, it must be made to work within the brand. AX Hub is the brand operating system for the AI era. Key Message If AI can't be stopped, it must be made to work within the brand. Executive Summary Many companies have brand guidelines. But most exist only as PDFs — created once, filed away, and consulted only when needed. The problem is that AI doesn't automatically follow that PDF. For AI to produce

WHO APPROVED THIS AI DESIGN? Consistency Matters More Than Speed Making something fast doesn't make it good design. A brand isn't protected without review. Key Message AI has made it possible for anyone to design, but not everyone can maintain brand consistency. Executive Summary In the age of AI, what's growing fastest inside a company isn't the number of designers, but the number of people creating things with AI. Sales teams create proposals, marketing teams create banners

Why AI Voice Agents Are Becoming the Standard for Appointment-Based Businesses Whether it's a restaurant, a clinic, or an auto shop, any appointment-based business knows this scene all too well. While staff are helping the customer in front of them, the phone rings, and they have to choose one of two options: leave the customer waiting to answer the call, or let the call go. Studies show that a single missed call costs an average of about $450, which adds up to as much as $42

A Forward Deployed Engineer (FDE, On-Site Engineer) is an engineer who embeds directly within a client's team to understand the actual mechanics of their business. They identify where AI belongs (and where it doesn't) and take full responsibility for building, deploying, and operating production-grade AI on top of existing enterprise systems. Target Audience: Mid-market enterprises looking to adopt generative AI but struggling to move past the Proof of Concept (PoC) phase. •

Summary: The reason 95% of enterprise generative-AI pilots never reach production isn't model performance — it's "operational fit." To get past this, manufacturers need to stop chasing flashy demos and instead automate a single job end-to-end, all the way through to the data, using a 5-step framework. At a glance Content Who is this for Decision-makers and practitioners at small and mid-sized manufacturers with no AI team, or only 1–2 people What problem it solves The "PoC gr

TecAce가 AX Diagnostic을 만든 이유와, 그것으로 무엇을 알 수 있는지에 대하여

"You want to put AI on a smartphone?" — The Beginning of a Reckless Challenge The story of how TecAce's AI Supervision Team built the On-Device LLM Tester "Um… I'd like to automatically measure LLM performance on a smartphone." A brief silence fell over the meeting room. Our team was developing our own on-device AI chatbot. The problem was that every time we swapped models, a tester had to physically hold the phone, send prompts one by one, and time everything by hand. That p

DESIGNER IS NOT DEAD In the AX Era, Design Is About Standards, Not Tools Figma or Adobe is not the real issue. In an era where AI tools are becoming part of everyday work, the more important question is this: can your brand and design standards remain consistent even when the tools change? Executive Summary As AI tools continue to grow, questions like “Can we design without Figma?” or “Do we still need Adobe?” have become more common. But these questions miss the bigger point

Gartner says 85% of AI failures come down to data-quality problems. Here are the 3 failure patterns repeatedly seen in SMBs and mid-sized companies in Korea and the U.S., plus a 20-item self-diagnosis checklist to run before adoption. Of these, only 8 truly require humans.

From 12,000 documents scattered across 5 systems to a living knowledge graph of 8,500 nodes and 23,000 relationships. The measured results of six months adopting TecAce AXKH, which combines Ontology-based RAG, a Multi-Agent pipeline, and Human-in-the-Loop governance.

AI must work even where there is no internet. TecAce On-device combines OTA updates with a hybrid offline/online architecture to deliver up-to-date knowledge anywhere — from factory floors out of signal range to campsites deep in the mountains. In this article, we explore five industry use cases where the TecAce platform can be applied, each illustrated with a concrete scenario. Case 1. An AI Manual Companion for Field Workers Field AI Companion — Factories · Shipyards · Plan

Design is no longer only something you make with a mouse. It is becoming something you shape through conversation with AI. Executive Summary: The Future of Design Conversational design tools like Claude Design are revolutionizing how we approach design. Work no longer begins with a blank canvas. Instead, a user describes their needs, and AI generates the first version. This initial output is then refined through conversation, comments, and direct edits. This shift has the pot

You ask ChatGPT to draft an email. You hand Gemini a report to summarize. It feels like having a personal assistant who works only for you. You start to trust it. And that trust is exactly where the problem begins. AI is helpful. That is precisely why it’s dangerous. In 2023, three engineers at Samsung’s semiconductor division pasted source code, internal meeting notes, and hardware design data into ChatGPT three separate times over a single month. They were debugging. They w

DESIGNER IS NOT DEAD From Maker to System Designer Core Message This is not the era where AI replaces design. It is the era where designers define the standards AI must follow. Card Summary As AI creates screens and documents faster, the designer’s role becomes more important, not less. Designers no longer need to make every artifact by hand; they need to design the brand standards and design systems that both people and AI can follow. Executive Summary AI has fundamentally c

Executive Summary AI-powered meeting summaries are nothing new. TecAce Software had already been using various solutions to boost productivity through automated meeting recaps. But two persistent pain points remained: every attendee received the same summary regardless of their role, and recurring meetings lacked the continuity needed to surface meaningful insights. To solve this, the team built an internal Personalized AI Meeting Note System — integrating Speaker Recognition

Executive Summary This case study shares how TecAce Software solved an internal challenge: revenue, cost, and cash flow data scattered across five separate systems — Excel, ERP, SharePoint, and more — made it difficult to get an accurate, real-time picture of the business. As an AI solutions company, TecAce applied its own technology directly to its own operations. Using Vibe Coding for rapid development and a Multi-Agent architecture where specialized AI agents autonomously

Click the image to view the report. Every time Google ships a new generation of the Gemma series, the question we ask first is simple: how much faster does it actually run on real hardware? To answer that directly, TecAce ran a head-to-head benchmark between Gemma 3n and Gemma 4 on the Samsung Galaxy S25 Ultra under identical conditions. We tested four model configurations using the llama.cpp CPU inference engine: the previous-generation Gemma 3n E2B Q8_0 as our baseline, a

Galaxy S25 vs S26: On-Device AI Performance Benchmark Reversal! (Snapdragon 8 Elite Gen 1 vs Gen 2) Does a newer chipset always guarantee faster AI performance? Based on real-world test data conducted by TecAce, we compared the on-device LLM performance between the Galaxy S25 and the Galaxy S26 to find out. Test Overview Devices Compared: Galaxy S25 (Snapdragon 8 Elite) vs. Galaxy S26 (Snapdragon 8 Elite Gen 2) Test Models: Gemma3 1B (INT4): An ultra-lightweight conversationa

5 Essential AI Transformation Patterns for Manufacturing Intro: Why Manufacturing Needs AI Transformation Now For owners of small and medium-sized enterprises (SMEs) in manufacturing, AI transformation is no longer a future option but a present-day task. Since the emergence of ChatGPT in late 2022, AI adoption has become a hot topic across all industries, and manufacturing is no exception. However, the reality is that the digitalization level of Korean manufacturing SMEs rem