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Still think five rounds of requirement gathering calls are what get you the deal?

ai, AI (Artificial Intelligence), AI Software Development, Artificial Intelligence, B2B Sales, Business Technology, Client Alignment, Client Engagement, Client Experience, Digital Product Development, Interactive Prototyping, product development, Product Discovery, Prototype Development, Requirement Based Prototyping, Requirement Gathering, software development, Software Prototyping, Spritle Blog

You’re wrong. Clients don’t sign off on documents. They sign off on things they can see. Every extra call you schedule to “align on requirements” is another chance for the client to lose confidence that you actually understand their business, because right up until you show them something real, you’re just another vendor with a […]

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How Spritle Built InsightTwin: A Living Digital Twin Platform for Enterprise Operating Models

agentic ai, ai, AI (Artificial Intelligence), AI & Machine Learning, AI & ML, AI & Technology, AI Agents, AI Assistant, ai development, Artificial Intelligence, Case Study, claude, Claude AI, Digital Twin, Enterprise Software, process automation, Spritle Blog

How we built a Digital Twin of an Organization, powered by Claude, from prototype to production. The Challenge Our Client Came to Us With Organizations invest millions in transformation initiatives like new systems, restructured teams, AI adoption, without a complete picture of how they actually operate today. Process knowledge lives in documents that go stale,

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Build a Reasoning LLM from Scratch: A Complete Guide to GRPO, RoPE & Pretraining.

ai, AI (Artificial Intelligence), AI in Engineering, Artificial Intelligence, Build LLM from Scratch, deep learning, GPT Architecture, GRPO, Large Language Models, Large Language Models (LLMs), LLM training, LLMOps (Large Language Model Operations), Machine Learning, QK Norm, Reasoning LLM, RMSNorm, RoPE, Spritle Blog, Transformer Architecture

Introduction A reasoning LLM is a language model trained not just to predict the next word, but to work through a problem step by step and verify its own conclusions before answering the approach behind models like OpenAI’s o1 and DeepSeek’s R1. This guide condenses a practical path to building a compact 300–400M parameter GPT-style

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Integrating an RFID Reader into a React Application Using the Web Serial API

ai, AI (Artificial Intelligence), Artificial Intelligence, Asset Tracking, Browser APIs, EPC Extraction, Frontend Development, Hardware Integration, Industrial IoT, Inventory Management, IoT Development, JavaScript, React Architecture, React Services, React.js, RFID, RFID Reader, SDK Integration, Serial Communication, Spritle Blog, spritle blogs, SpritleSoftware, typescript, Web APIs, web development, Web Serial API

Introduction Recently, I worked on integrating an RFID reader into a React application. Although I’ve integrated APIs and third-party libraries many times before, working with hardware devices was a completely different experience. It gave me an opportunity to understand how browsers communicate with physical devices and how browser APIs can be used beyond traditional web

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Why Alert Fatigue Is an Operational Risk (Not Just an IT Problem)

ai, AI (Artificial Intelligence), AIOps, alert fatigue, Alert Management, Artificial Intelligence, Devops, Incident Management, IT Monitoring, IT Operations, IT Operations / AIOps, Observability, Spritle Blog, spritle software, SRE

Why Alert Fatigue Is an Operational Risk Modern enterprises rely on thousands of monitoring tools to ensure applications, infrastructure, networks, cloud services, and security systems remain healthy. Every component generates alerts intended to notify teams of potential issues before they become business disruptions. However, more alerts do not necessarily translate into better visibility. Many IT

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How We Helped a Global FMCG Brand Process 100,000+ Quality Documents with AI

ai, AI (Artificial Intelligence), AI Case Studies, AI Case Study, AI Data Extraction, AI Document Processing, Artificial Intelligence, business process automation, Compliance Automation, compliance management, digital transformation, Document Automation, Document Intelligence, Enterprise AI, Field-Level Validation, FMCG, Intelligent Document Processing, Intelligent Document Processing (IDP), Manufacturing Automation, OCR, PDF Data Extraction, process automation, Quality Testing Documents, Spritle Blog

Here’s How We Helped a Global FMCG Brand Process 100,000+ Quality Testing Documents with AI Without Losing Accuracy When a global FMCG manufacturer came to us, the problem wasn’t a lack of data. It was too much of it, trapped in the wrong format. Every batch of product that left their manufacturing facilities came with

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Beyond the Checklist: A Practitioner’s Review of IMDA’s LLM Testing Starter Kit

ai, AI (Artificial Intelligence), AI Evaluation, AI Governance, AI safety, Artificial Intelligence, Enterprise AI, Enterprise Technology, Generative AI, IMDA, LLM Testing, Machine Learning, MLOps, Responsible AI, Spritle Blog

Introduction As large language models move from proof-of-concept into production systems that touch real users, real money, and real decisions, the industry has been crying out for structured, actionable guidance on how to test them responsibly. IMDA’s Starter Kit for Testing LLM-Based Applications is a meaningful answer to that call. It arrives at exactly the

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Testing Beyond Pass or Fail: A QA Engineer’s Lessons from IMDA’s LLM Testing Starter Kit at Spritle

Adversarial Testing, ai, AI (Artificial Intelligence), AI Application Testing, AI Governance, AI Product Quality, AI Quality Assurance, AI security, AI Security Testing, AI Testing, Artificial Intelligence, Bias Testing, Generative AI, Generative AI Testing, Hallucination Testing, IMDA LLM Testing Starter Kit, LLM Testing, Prompt injection testing, QA Best Practices, QA Engineering, Quality Assurance, Red Teaming, Responsible AI, Semantic Similarity Testing, Software Testing, Spritle Blog, SpritleSoftware

I’ve been in QA for a few years now. I know how testing works. You write a test case. You define the expected result. You run it. It either passes or fails. Simple. So when our team started working on an AI-powered feature, I thought, okay, same process. Different kind of input, but same idea.

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Lessons from IMDA’s LLM Testing Starter Kit: An AI Assurance Perspective

Agentic AI security, ai, AI (Artificial Intelligence), AI Assurance, AI assurance framework, AI Governance, AI governance and compliance, AI red teaming, AI Risk Management, ai safety testing, AI security, Artificial Intelligence, Enterprise AI assurance, Large Language Models (LLMs), LLM testing best practices, OWASP Top 10 for LLMs, Prompt injection testing, Responsible AI, Spritle Blog, SpritleSoftware

Quality Assurance has always been about understanding risk and validating systems before they reach production. After more than eight years in QA and now working in AI security, governance, and red teaming, I often compare traditional testing practices with the challenges introduced by AI systems. While the risks have evolved from software defects to hallucinations,

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Breaking the Black Box: From Traditional QA to AI Assurance and Governance

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I recently had the opportunity to review IMDA’s Starter Kit for Testing LLM-Based Applications for Safety and Reliability. As someone who has spent over 14 years in Quality Assurance, I was curious to see how established testing principles are being adapted to address the unique challenges introduced by Large Language Models (LLMs). What I expected

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