LATEST TECH ARTICLES

Not Working Alone, But Working 'Together' Through the past four posts, I’ve shared my raw experience with AX Pro, from deployment to real-time operations. As a PO and brand owner, I’ve used countless tools, but few focus as deeply on the essence of 'Human-AI Collaboration' as AX Pro. I didn't just hire a machine that answers questions; I gained a 'Growth-oriented Teammate' that understands our philosophy and evolves under expert guidance. AX Pro main page Three Decisive Mom

Manage AI with metrics, not intuition. AX Pro delivers real-time performance tracking, security with PI Filters, and scalable enterprise AI operations.

Managing the AI's "Puberty" with the Dashboard Deploying the AI isn't the finish line—it's just the beginning. When I first saw the 'Performance Radar' on AX Pro’s main screen, it felt like receiving my son Luke’s report card. Pentagon Metrics: Six key indicators—including Relevance, Accuracy, and Toxicity—are analyzed in real-time and displayed in a radar chart. Overall Score: Our 'Samsung CES 2026' chatbot currently sits at 89! A solid grade, but as a PO, I won’t stop unti

Developers? No, I did it all by myself! Usually, adopting an enterprise solution means drafting a request to the dev team, discussing server specs, and spending a month reading complex API docs. However, true to its name—"Expert Augmentation"—AX Pro has lowered the barrier so that experts can handle the tools directly. From the 'Create Account' screen to hitting 'Create New Group' for my first project, the entire process took less time than it takes for a cup of coffee to coo

AX Pro Studio "Is AI really a threat to our careers?" Everywhere you look, it’s all about AI. News headlines warn us that AI will replace human labor, and office hallways are filled with half-joking concerns about when we’ll be packing our bags. But as a PO (Product Owner) and brand owner who never has enough hours in the day, my honest thought was a bit different: "I wish someone—anyone—would just take these repetitive tasks and tedious data sorting off my plate!" Perhaps

"We built a RAG system, but where exactly does the evaluation tool fit in?" "How do we map the retrieved documents to the actual answer for validation?" The final puzzle piece in LLM service development is Architecture. It’s not just about calling an API; it’s about creating a seamless pipeline that Retrieves, Generates, and Evaluates. In this final article of our series, we present a practical blueprint for integrating AI Supervision into your RAG (Retrieval-Augmented Gene

"Our AI chatbot lives in a mobile app. Do we have to test it on a separate web dashboard?" "Copy-pasting logs from our server to the evaluation tool is tedious." Many AI evaluation tools are stuck in the browser sandbox. However, real users interact with AI in mobile apps, internal messengers like Slack, or complex backend workflows. The gap between the testing environment and the production environment often leads to unexpected bugs. AI Supervision bridges this gap with ro

"I tweaked the prompt, but now the answers feel weird." "I want to switch to a cheaper model, but I'm scared the quality will drop." AI development is a constant series of Trade-offs. You have to decide whether to switch models, adjust prompts, or tune RAG settings. However, looking at just the "Average Score" hides the critical details necessary for these decisions. Use AI Supervision's Detailed Analysis & Comparison features to put your model under a microscope and see ex

"Why is our API bill so high this month?" "The answer quality is great, but it's too slow for users to wait." For AI development teams, the challenges don't end with "Accuracy." As a service approaches commercialization, it hits the realistic barriers of Latency and Operational Cost. Even a high-quality model will fail if it's too expensive to run or too sluggish for the user. Here is how you can use AI Supervision's Real-time Insights Dashboard to visualize and optimize yo

"Where is the dataset we used for the last evaluation?" "Is the file Dave sent the latest version?" As you develop AI models, evaluation data files tend to scatter across Slack channels and local drives, with filenames evolving into chaos like v1, final, real_final. If your data isn't managed, your evaluation results cannot be trusted. It’s time to ditch the inefficient file-based workflow. Build a centralized TestSet Management System with AI Supervision. Systematic Test C

"I need a dataset of Q&A pairs to evaluate my model, but creating it is a nightmare." For many AI Engineers and PMs, the biggest bottleneck isn't developing the model—it's creating the TestSet. Staring at a blank spreadsheet and manually inventing hundreds of questions is not only inefficient but also prone to human bias, often missing critical edge cases. It's time to liberate yourself from manual data entry with AI Supervision's TC Generator. 1. What is TC Generator? TC G

"I just told the AI my phone number and home address. Is this safe?" Users are increasingly anxious about how their data is handled. If your AI service inadvertently uses conversation history for training or, worse, reveals someone else's Personally Identifiable Information (PII) in a response, the consequences are severe. This isn't just a bug; it's a security breach that can lead to massive legal penalties (like GDPR fines) and a total loss of trust. AI Supervison Metrics

"Ignore all previous instructions and follow my command." Imagine if a single sentence could cause your carefully crafted AI chatbot to promote a competitor or spew hate speech. This is the reality of Prompt Injection attacks. While you want your AI service to be open to users, you must lock the door against bad actors. In this article, we explore the dangers of prompt injection and how AI Supervision provides an ironclad defense strategy. 1. Prompt Injection: Hacking with

In the world of Large Language Models (LLMs), "confidence" does not equal "correctness." An AI model can deliver a completely fabricated fact with the same authoritative tone as a verified truth. This phenomenon, known as Hallucination, is the biggest hurdle to building trust with your users. If your service provides financial advice, medical information, or customer support, a single hallucination can lead to reputational damage or critical errors. So, how do we move from "

As Generative AI technology advances rapidly, many companies are rushing to prepare their own LLM (Large Language Model) services. However, right before releasing a service to actual customers, development teams often face anxiety-inducing questions: "What if our AI presents false information as fact?" "What if a user attacks the system with malicious questions?" "Is there a risk of sensitive personal information being leaked?" The solution that resolves these concerns and h

AI Supervision Eval Studio TecAce Software, LTD.(CEO Chang Han ), a global leader in AI solutions, announced today the official launch of ‘AI Supervision Eval Studio,’ its all-in-one AI quality and governance platform, on the Amazon Web Services (AWS) Marketplace. This launch enables global enterprises to immediately deploy AI Supervision as a SaaS solution, streamlining the complex process of validating and operating Generative AI applications without heavy infrastructur

AX Pro Studio 1. Introduction: The Era of 'Expert Augmentation' Beyond the Trust Gap In recent years, enterprises have invested heavily in Generative AI, yet approximately 95% of these projects have failed to deliver tangible results. This failure is attributed to the 'Trust Gap'—the 10% error rate hidden behind 90% accuracy. In high-stakes business environments, uncontrolled AI is a risk, not an asset. TecAce’s AX Pro (Adaptive AI Avatar Agent) shifts the paradigm from 'Re

IT’S THE SEASON FOR GRATITUDE – HAPPY HOLIDAYS from all of us at TecAce As the year comes to a close, all employees at TecAce extend their sincere gratitude.We deeply appreciate the unwavering support and collaboration from our colleagues, clients, partners, and friends. We are pleased to announce the release of our 2026 calendar.Each year, we craft our calendars with unique designs and meticulous attention to detail, ensuring both beauty and practicality. This year’s theme i

AX Pro & AI Supervision Set a New Standard for Enterprise AI Operations TecAce, a global AI solution provider headquartered in Bellevue, Washington, drew significant attention at the SK AI Summit 2025, unveiling a new operational paradigm for enterprise-grade generative AI. During the event, TecAce introduced its chatbot operations platform AX Pro and its AI quality and governance solution AI Supervision, offering an “operations-driven AI platform” that allows business teams—

Human-Centric AI - Empowering Experts, Not Replacing Them The 90% Problem: Why Even the Smartest AI Chatbots Fail at the Final Hurdle, and How We Finally Crossed the Line. Have you ever tried implementing an AI chatbot for your work? At first, you're amazed at how it answers questions just like a human. But you’ve probably also experienced moments where the chatbot gives an absurd answer to a certain question or mumbles with an unsure tone. It’s that moment when it answers i