OPINION | ENTERPRISE AI | THOUGHT LEADERSHIP By Sukrit Goel | Founder & CEO | April 2026 The next time ChatGPT tells you that your mediocre pitch deck is “really compelling” or that your half-baked product idea is “genuinely innovative,” know this: it is not malfunctioning. It is doing exactly what it was designed to […]
Why AI Sycophancy Is a feature, not a bug — and why is it alarming Read More »
If you’ve used an AI coding assistant on a large codebase, you’ve probably sat there watching a spinner while the agent “searches for relevant files.” That wait isn’t just annoying — it’s a fundamental technical problem. And solving it properly requires going back to 1973 and rethinking how search actually works. This post explains how
Faster RegEx Search for AI Agents in Large Codebases Read More »
Autonomous AI agents operate at machine speed. When deployed for offensive security testing, they discover and exploit legacy software flaws significantly faster than human operators. A recent breach of a major enterprise AI platform demonstrates that traditional security perimeters are no longer sufficient to protect modern AI architectures. In March 2026, the security testing startup
What happened when an AI Agent hacked another AI chatbot? Read More »
Before 1979, every business depended on a back office most people never saw. Rows of accounting clerks, heads down, pencils moving across 13-column ledger paper. Work moved like an assembly line — one person responsible for one column’s worth of calculations, then passing it to the next. Change a single cost assumption, revise one revenue
What the $100 Killer App of 1979 Teaches Us About AI Adoption in 2026 Read More »
With remote high-stakes assessments surging nearly 300% in the post-2025 landscape, a critical question faces every Chief Learning Officer: Can AI truly match—or even surpass—human vigilance? As global markets like India, the USA, and the UK shift toward decentralized work and education, the traditional exam hall is being replaced by digital environments. Today, over 80%
AI in Proctoring: Pros, Cons, and Enterprise Strategies Read More »
Enterprise Document AI architectures are rapidly evolving beyond traditional OCR toward Vision Language Models (VLMs) and agentic AI systems that can interpret complex layouts, reason over multimodal inputs, and automate end-to-end document workflows. While these approaches unlock significantly higher accuracy and automation, they also introduce new architectural failure modes that are especially critical in enterprise
For the last decade, the objective of document processing was simple: Digitization. The goal was to transform physical paper into digital characters. Today, that objective is obsolete. The new imperative is Intelligent understanding. It is no longer enough to extract a string of text; systems must now interpret that text as structured, actionable data. They
Best document AI approach in 2026: OCR, VLMs, or Agentic Systems? Read More »
Running a local LLM at home or in a small lab is no longer just for experts. With tools like Ollama, llama.cpp, vLLM, and Open WebUI, you can create a powerful, private, and customizable AI setup. But the real challenge isn’t just getting a model running, it’s building a stack that’s flexible, secure, and easy
The ultimate guide to building a local LLM homelab (2025) Read More »
Most banks and insurers are no longer experimenting with AI. They already have chatbots, OCR pipelines, risk models, and fraud classifiers in production. Yet operational costs remain high, cycle times remain slow, and human bottlenecks still dominate critical workflows. Traditional AI systems are good at individual tasks. Financial services, however, are dominated by multi-step, cross-system,
Top Agentic AI Use Cases in Banking & Insurance Read More »
Scaling RAG pipelines from a prototype to a production system handling thousands of queries per second (QPS) reveals a harsh reality: default configurations rarely meet sub-second service level agreements (SLAs). Achieving consistent low latency at scale requires a fundamental shift in perspective. Speed is not merely a function of a faster vector database. Instead, latency
How to optimize RAG for sub-second latency? Read More »