AI/ML

Prompting Is Architecture: Why Understanding Systems Matters More Than Ever

A Spark story about scale, grain, and why speed makes system awareness non-negotiable.Image generated using ChatGPTRecently, I ran into a Spark job that looked perfectly fine. I used Claude in this case to generate code, which wasSyntactically correctSemantically correctEasy to read and reason aboutThis worked on the sample dataset. Assuming Spark will manage the scale, we pushed it to production. However, on prod, it took more than 3 hours to complete on a 40-node EMR cluster. It was trying to...

Read

Delivering a 40% Velocity Boost in the Modernization of Talon Plato's Legacy System with GenAI

Sahaj Software modernized Talon's Media Owner Portal from legacy Angular 17 to a contemporary React architecture. This initiative went beyond a simple rewrite, piloting "intelligent Engineering", an AI-augmented, Gen-AI-powered workflow. This approach effectively managed evolving UX needs and technical debt, ensuring predictable delivery and establishing a scalable modernization blueprint, which positions Talon as a digital innovation leader in the OOH space. Talon is a specialist Out-of-Home (OOH) agency with over 30% UK market share and operations in the UK, USA,...

Read

Project xEMR: Building an AI-Powered EMR System with Agentic AI Workflows

Project xEMR demonstrates the successful use of advanced, automated AI systems to build a complex medical records platform that strictly adheres to all healthcare regulations. The intelligent Engineering approach fundamentally transformed the software development lifecycle by having AI agents handle 90% of the work, resulting in a 300% increase in engineer productivity.October 2025The healthcare industry is bogged down with complex, time-consuming paperwork and tasks, and often the standard Electronic Medical Records (EMR) systems are part of the problem. That's why...

Read

Driving Success of AI Initiatives Using the Power of Systems Thinking

The key to scaling AI from proof-of-concept to enterprise success in B2B is adopting systems thinking, which integrates the right user experience, value definition, and complementary non-AI features into the solution.In today’s tech landscape, Artificial Intelligence is often presented as the ultimate solution to every challenge. This can lead one to experience the ‘Law of the Instrument’ phenomenon. When AI is your powerful new hammer, you start seeing every problem as a nail. We rush to apply complex models and...

Read

Building an AI-Powered EMR Extension with Agentic AI Workflows

The healthcare industry is bogged down with complex, time-consuming paperwork and tasks, and often the standard Electronic Medical Records (EMR) systems are part of the problem. That's why we embarked on Project xEMR to build an AI-augmented EMR Extension platform. The purpose was to dramatically cut the administrative work for medical staff. Project xEMR is an AI layer that sits on top of existing EMR systems. It doesn't replace them; it only makes them smarter. It strictly follows essential healthcare...

Read

Latency Diet for Large Language Models: Cutting Millisecond Fat Without Losing IQ

When I first started building my own model (a language model for my need ), I went through a lot of videos and built it from scratch. While doing so I noticed something interesting: A model that answers in 300ms feels brilliant, while the same model taking 3 seconds feels broken, even if the answers are identical. Of course, not all extra time is wasted. With reasoning models, those additional seconds often reflect deeper “thinking” running through more steps, generating...

Read

Harnessing Agentic AI to Drive Competitive Advantage

Our global Emerge series hosted an invitation-only roundtable in New York on September 17th, 2025. Representatives from a variety of industries including financial services, B2B commerce, cloud services, social media technology, and community and social services gathered to discuss “Harnessing the Value of Agentic AI to Drive Competitive Advantage.” The discussion compared agentic AI with programmatic workflows, described a strong agent, and agreed on important points and next steps.AI agents are goal-seeking loops, not fixed scripts. An agent plans a...

Read

Using AI to Simplify Developer Onboarding

Today, the market is filled with LLM-powered tools, with new and more advanced options emerging almost daily. In this article, we focus on one use case: integrating AI into the software development process to simplify onboarding for new developers.Onboarding a new developer involves a mix of tasks for both the newcomer and the existing team, often making the process hard to standardise or automate. Early days typically include reading documentation, meeting the team, attending sessions, and waiting for access to...

Read

Redefining Risk Management With AI

Across industries, AI is revolutionizing risk management by overcoming the limitations of traditional methods. It achieves this by analyzing large datasets to identify emerging threats and anomalies, while generative AI interprets unstructured information and provides clear answers to complex risk-related questions.To explore these advancements, Sahaj Software recently hosted a roundtable with leaders from multiple industries in New York. The conversation revolved around specific risk challenges in sectors like finance, healthcare, pharma, manufacturing, and publishing, emphasizing the need for AI-driven solutions....

Read

MCP and Doc-Monitor Transform External Services Integration

(AI-generated image)In today's interconnected world, integrating with a vast ecosystem of SaaS providers presents a significant challenge. It is not just about understanding and creating OpenAPI REST clients for numerous APIs, but also mapping them to our internal domain model. The real hurdle lies in the continuous maintenance of both the client and the mapping code as these third-party SaaS APIs evolve.Imagine we're building a neobank in the UK. A key feature of our app is providing users with a...

Read