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Notes from building data products
Practical writing on AI, data, and automation from the team doing the work.

Latest Article

When Order Documents Disagree: How DocValidator Turns Document Checks into a Reliable Business Control

October 15, 2026

DocValidator
When Order Documents Disagree: How DocValidator Turns Document Checks into a Reliable Business Control
October 15, 2026
DocValidator · 7 min read
When Order Documents Disagree: How DocValidator Turns Document Checks into a Reliable Business Control
Mismatched purchase orders, invoices and payment instructions delay cargo and invite fraud. See how DocValidator checks every order document automatically.
October 15, 2026
Insurance
Why Insurance Data Still Fails Businesses and How InsurePulse Changes the Equation
October 12, 2026
Insurance · 11 min read
Why Insurance Data Still Fails Businesses and How InsurePulse Changes the Equation
For many insurers, the challenge is no longer collecting data. The real challenge is making sense of it. Over the years, insurance organisations have invested heavily in policy administration systems, claims platforms, finance applications, actuarial software, broker portals, and third-party integrations. Most of these systems were introduced independently to address specific operational needs at different stages of growth, rather than being designed to operate within a single connected ecosystem. The result is a fragmented operational environment in which critical information is scattered across disconnected systems. Teams spend significant amounts of time locating, validating, and reconciling data before they can begin analysing it. Reporting cycles become slower, operational visibility decreases, and confidence in business data starts to erode. InsurePulse was created to address this problem directly. Instead of requiring insurers to replace existing infrastructure, the platform connects legacy systems and consolidates fragmented information into a single, unified data environment that enables faster reporting, greater visibility, and more informed decision-making.
October 12, 2026
Industry
The Digital Doctor: AI’s Role in Healthcare
August 29, 2026
Industry · 9 min read
The Digital Doctor: AI’s Role in Healthcare
Artificial intelligence is rapidly transforming healthcare from a future promise into a present reality. No longer limited to research settings, AI tools are being deployed in hospitals and clinics across continents, offering earlier diagnoses, streamlined workflows, and new avenues for treatment. These advances highlight both the vast potential of AI and the pressing need to ensure its safe, equitable, and sustainable integration into health systems worldwid
August 29, 2026
Industry
AI in Surveillance: A Game-Changer for Security and Efficiency
August 20, 2026
Industry · 10 min read
AI in Surveillance: A Game-Changer for Security and Efficiency
Over the last decade, surveillance technology has evolved far beyond simple cameras that record video footage. With the rapid advancement of artificial intelligence (AI), CCTV monitoring has transformed from a reactive, manual process into a proactive, intelligent security solution. Traditional CCTV monitoring had a fundamental limitation: it required human operators to watch hours of footage and manually identify suspicious activities. This often meant that security teams were reacting after incidents had occurred. With AI integration, however, CCTV systems are no longer passive. They actively process video streams in real-time using advanced algorithms, computer vision, and machine learning models. This means they can recognise faces, detect objects, track movement patterns, and even understand context. This transition marks a profound shift from surveillance as a deterrent to surveillance as an active safety and operational tool.
August 20, 2026
Insurance
Can Insurance Really Do Self-Service BI? Lessons from the Field
December 30, 2025
Insurance · 16 min read
Can Insurance Really Do Self-Service BI? Lessons from the Field
Self-service business intelligence has been promised to the insurance industry for years. The pitch is always compelling: faster access to data, fewer reporting bottlenecks, and empowered business users making better decisions without waiting for IT. Yet the lived experience inside many insurers tells a different story. Dashboards multiply. Metrics drift. Confidence in the numbers quietly declines. Business users either feel overwhelmed by complexity or disappointed that “self-service” still involves queues and workarounds. So, can insurance really do self-service BI? Based on practical experience across insurers of different sizes and levels of maturity, the answer is yes, but only when it is approached with realism, discipline, and a clear operating model. This article explores why self-service BI so often fails in insurance, what makes it work when it succeeds, and the technical and organisational foundations that matter most.
December 30, 2025
Insurance
From Fragmented Systems to Unified Intelligence: The InsurePulse Advantage
November 28, 2025
Insurance · 8 min read
From Fragmented Systems to Unified Intelligence: The InsurePulse Advantage
The insurance industry holds vast volumes of data, yet meaningful insight often remains out of reach. Years of dependence on legacy systems have created complex, disconnected technology estates where each platform stores information in isolation. This environment of fragmented data requires significant manual effort to reconcile, frequently leading to delays, inconsistencies, and reduced confidence in the outputs. Rather than supporting timely and well-informed decisions, critical information is constrained by systems that were not designed for modern analytical demands. InsurePulse was developed to address this structural challenge and provide insurers with a unified, dependable foundation for data-driven operations.
November 28, 2025
10 min read
Why AI ‘Inbreeding’ and Poor Data Quality Threaten the Reliability of the Next Generation of Models
October 30, 2025
10 min read
Why AI ‘Inbreeding’ and Poor Data Quality Threaten the Reliability of the Next Generation of Models
The rapid ascent of Large Language Models (LLMs) and other generative AI tools has been nothing short of revolutionary, demonstrating high performance across a variety of tasks. Yet, as these models become pervasive and begin to generate much of the content online, a critical crisis is brewing in the very datasets that sustain them. If we continue on our current trajectory, ignoring the foundational issue of data quality, the next generation of AI may become unreliable, biased, and ultimately nonsensical.
October 30, 2025
9 min read
The Bias Dilemma: Is Artificial Intelligence Reflecting Us or Shaping Us?
September 29, 2025
9 min read
The Bias Dilemma: Is Artificial Intelligence Reflecting Us or Shaping Us?
Artificial Intelligence (AI) and Large Language Models (LLMs) have rapidly evolved, transforming how we interact with technology, make decisions, and access information. From chatbots and virtual assistants to automated content generation and decision support systems, LLMs are becoming integral to both business and everyday life. Yet, as these models grow in influence, questions about fairness, objectivity, and bias have become increasingly urgent. Can AI, particularly LLMs, truly operate without bias, or are they inherently shaped by the limitations of their human creators and the data they consume?
September 29, 2025
Industry
When AI Meets Education: The Lessons of Tomorrow
September 27, 2025
Industry · 10 min read
When AI Meets Education: The Lessons of Tomorrow
Artificial intelligence is no longer a futuristic promise in education. It is increasingly woven into classrooms, assessment systems and institutional planning. As schools, colleges, and universities grapple with rising student numbers, pressure on staff, and demands for more personalised learning, AI offers powerful tools and new questions.
September 27, 2025

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