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September 29, 2026

When AI Goes Off Script: What Kuya A Teaches Us About Securing Production AI

On September 21, the Philippine government launched eGovAI and its AI assistant, Kuya A, as part of the eGovPH Super App. The government described it as an AI-powered assistant intended to help Filipinos access government services and information more easily.Link: https://pia.gov.ph/news/luzon/ncr/marcos-jr-admin-launches-egov-ai-unveils-kuya-a-assistant-in-egovph-superapp/ Within days, however, two incidents highlighted challenges that every organization deploying large language models should be thinking about.

September 21, 2026

ROI or RIP: What Production AI Taught Us About Making AI Investments Work

At Echelon Philippines 2026, ChatGenie CEO and Co-Founder Ragde Falcis joined the panel “ROI or RIP: How to Measure Whether Your AI Spend Is Working” to discuss a question many enterprises are now facing:How do you know if an AI deployment is actually creating business value?For us at ChatGenie, this is no longer a theoretical question.Through production deployments with enterprises such as Angkas and LBC Express, we’ve seen that successful AI implementation depends less on having the newest model and more on identifying the right workflows, measuring their economics, and proving value before expanding.

September 3, 2026

From Chatbots to Business Decisions: The Rise of Agentic AI

AI is moving beyond generating answers.The next phase is about taking action.Following ChatGenie CEO and Co-founder Ragde Falcis’ recent appearance on ANC’s Startup, ABS-CBN News published a follow-up feature titled “Agentic AI is moving into business decisions.”Link to the article here: https://www.abs-cbn.com/news/technology/2026/8/29/agentic-ai-is-moving-into-business-decisions-1400The article captures a shift we are already seeing in enterprise AI: from systems that simply respond to users, to systems that can increasingly execute workflows, interact with business systems, and make decisions within defined boundaries.

September 2, 2026

August 19, 2026

ChatGenie Joins Echelon Philippines 2026 to Talk About Making AI Work in the Real World

ChatGenie CEO and Co-Founder Ragde Falcis will join industry leaders at Echelon Philippines 2026 on August 25–26 at SMX Aura to discuss what it really takes to turn AI investments into measurable business outcomes.AI has quickly moved from experimentation to boardroom priority.But as more companies invest in AI, a more important question is emerging:

September 29, 2026

The Agentic AI Evaluation Playbook: How We Compared GPT-5.2, Claude Sonnet 4.5, and Qwen for Enterprise Deployment [Compressed Version]

ChatGenie's production customer support automation platform was built on Microsoft Azure. Our Orchestrator Agent ran on GPT-5.2 — tuned from a GPT-4o baseline — and it had earned its place: 99% resolution accuracy, a 77% reduction in support OPEX, and a customer team rightsized from 39 to 9 agents for our flagship enterprise client. When we migrated to Amazon EKS and AWS Bedrock, we lost access to Azure AI Foundry and with it, our path to GPT-5.2. We needed a replacement sourced entirely from Amazon Bedrock. This article documents what we found.

May 20, 2026

The Agentic AI Evaluation Playbook: How We Compared GPT-5.2, Claude Sonnet 4.5, and Qwen for Enterprise Deployment [Complete Version]

When we set out to evaluate large language models for ChatGenie's core agentic workflow, we quickly realized that the benchmarks published by model providers — MMLU, HumanEval, MATH — told us almost nothing useful. We were not building a trivia assistant. We were running a production customer support automation system with real enterprise clients, live conversation volume, and service-level commitments that could not absorb experimental failure. The question we needed to answer was not "which model is smartest?" It was "which model behaves most reliably inside a constrained, multi-agent pipeline operating under production conditions?

January 22, 2026

How We Cut Latency by 50% by Simplifying Our Agentic Architecture

When we first designed ChatGenie's agentic system for customer chat operations, we followed a principle that seemed intuitive: separate concerns into separate agents. Intent classification? That's one agent. Policy enforcement? Another agent. Response generation? Yet another.The result was a five-agent core chain that was clean, modular, and easy to reason about. It was also slow.Each agent in the chain required a separate LLM call. Five agents meant five round-trips to the model. In customer chat, where users expect near-instant responses, this cumulative latency was becoming a problem. Users would see typing indicators for seconds before receiving a response. Containment rates suffered as impatient users escalated to human agents.We needed to rethink our architecture.

January 27, 2026

A Baseline Standard for Minimum End-to-End Agentic Customer Chat Operations

This document proposes a baseline standard for the minimum requirements of an end-to-end agentic system for customer chat operations. It is not intended as a complete specification, but as a starting point for teams building production-grade agentic support systems.

December 10, 2025

How a Leading Ride-Hailing Platform Cut Support Headcount by 77% with ChatGenie AI Agents

When we describe ChatGenie, we don’t start with “chatbot” or “ticketing system.” We start with Agentic AI Systems.ChatGenie builds multi-agent AI systems that autonomously analyze, decide, and act across complex enterprise workflows. Customer support operations are simply the first — and most visible — foundation where this approach creates tangible impact.

September 17, 2025

Trust is king in AI deployments: ChatGenie secures ISO/IEC 27001 certification

Manila — September 16, 2025 — ChatGenie is now ISO/IEC 27001 certified. This means that an independent auditor has reviewed our information protection practices and confirmed that our security measures meet a widely recognized international standard.

August 15, 2025

Why Your AI Projects Are Stuck in the Proof-of-Concept Stage: Common Pitfalls and How to Avoid Them

Organizations are investing heavily in artificial intelligence, yet many projects struggle to move beyond the proof-of-concept (POC) stage. AI implementers and project leaders often face significant hurdles when transitioning from experimental validation to practical, scalable deployment. This article examines the most common pitfalls that hinder AI projects from reaching production and shares insights supported by industry reports and studies.

August 1, 2025

ChatGenie at Bizkarteng Pinoy 2025: Sharing Stage with Converge’s Visionaries 🚀

Last July 17, 2025, ChatGenie attended Converge’s Bizkarteng Pinoy 2025, the inaugural MSME-tech conference held at Megatrade Hall 2, SM Megamall. Our CEO, Ragde Falcis, stood alongside industry leaders on the panel, sharing our insights on AI-driven customer service, seamless chat commerce, and powering SMEs to scale.

April 22, 2025

ChatGenie’s Evals Process for Production-Ready Chatbots

With today's large language models (LLMs), building a proof-of-concept (POC) for a chatbot is relatively easy, but turning that into a production-ready system is far more challenging. Early prototypes often impress in demos but can behave unpredictably in real-world use. The AI hype led to an explosion of AI projects and investments that have yet to produce return on investment. In large enterprises nearly nine out of 10 senior decision-makers said they have gen AI pilot fatigue and are shifting their investments to projects that will improve business performance, according to a recent survey from NTT DATA.”

February 11, 2025

Mood, Meet Machine: How Agentic AI Eliminates the Guesswork from Sentiment Analysis

Traditionally, sentiment analysis relied on manual reviews, periodic surveys, and basic keyword matching to gauge customer mood—a process that was both slow and limited in scope. In today’s fast-paced digital landscape, these methods fall short. Agentic AI sentiment analysis now processes vast amounts of data in real-time, delivering more accurate and actionable insights.

November 21, 2024

It Takes a Team of AI Agents to Power ChatGenie Chatbots

As we transitioned toward becoming an AI-focused company by developing an AI Copilot to assist businesses in managing their stores, we realized that delivering substantial value might take longer than anticipated. We created several useful AI-powered features such as product description generators, welcome and greeting message creators, and automated comment-reply configurators for existing Facebook posts.

July 26, 2024

ChatGenie: Revolutionizing Auto-Responses (Chatbot) with Multi-Agent Design Using Llama3

A significant portion of social media users have experienced at least one frustrating chatbot interaction online. One major reason for this frustration is that most chatbot responses are rigidly designed using predefined conversation flows. Users must follow a specific sequence to obtain the information they need, which can feel like navigating a maze. This often results in users going in circles, hitting dead ends, and ultimately giving up and reverting to calling a hotline or emailing customer support.

July 26, 2024

Ensuring Safe and Accurate ChatGenie Chatbot Interactions with Llama3

LLMs powered by transformer models have taken the world by storm, with products like ChatGPT reaching over a million users within the first month of release and surpassing 180 million users by May 2024. While these technologies are incredibly useful, ensuring their safety and accuracy is paramount.

October 10, 2023

ChatGenie Joins Techstars Future of eCommerce Powered by eBay: A New Chapter in In-App Store Revolution

We are thrilled to announce a significant milestone in ChatGenie's journey: our acceptance into the prestigious Techstars Future of eCommerce Accelerator Program Powered by eBay. This marks an exciting step forward for ChatGenie and a testament to our commitment to helping businesses through our In-App Stores.

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