Why chunking fails on Tables in RAG, & 4 proven strategies to fix it

In this blog, we break down why standard chunking fails for structured data and how to design table-preserving chunking strategies using modern RAG best practices. Each approach comes with implementation guidance, use cases, and architecture fit. Why chunking fails on tabular data? Tables aren’t text — they are relational knowledge graphs compressed into rows and […]

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LatentMAS explained: A new architecture for faster multi-agent AI systems

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If you’ve ever built or evaluated multi-agent LLM systems, you’ve hit the same bottleneck:agents collaborate by dumping text back and forth. This works, but comes with structural problems: LatentMAS proposes a fundamentally different inter-agent communication model:skip the token channel completely and operate directly in latent space. Below, we break down its architecture, performance characteristics, practical

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Hive to improve accuracy in AI solutions

How prompt data types are costing 40% in AI performance?

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Prompt data types matter more than most developers realize. It started with a simple anomaly. We were building a complex multi-turn conversational agent for a client. The logic was sound, the model was the latest GPT-4, and the context retrieval was optimized. Yet, the agent felt… sluggish. Worse, it was hallucinating during complex reasoning tasks, and

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Architecting a scalable AI-driven sales agent training platform

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A Singapore-based AI-first startup partnered with InteligenAI to transform its innovative sales training platform into a robust, enterprise-ready SaaS platform. We re-engineered their AI modules, rebuilt the core architecture, and created a unified workspace designed for performance, scalability, and real-world enterprise adoption. The client set out with a clear vision:to reinvent how sales teams practice,

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Architecting an AI native video intelligence platform with agentic orchestration and on-demand vision models

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In the rapidly growing video intelligence market—where organizations rely on real-time monitoring, alerting, and analytics—our client had already built one of the most robust computer-vision infrastructures in the industry. Their platform could process thousands of live video feeds, generate alerts in milliseconds, and manage a diverse ecosystem of devices across cloud and edge environments. But

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AI-powered mortgage filing system for faster, more accurate loan origination in USA

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Loan origination in the modern mortgage industry presents unique challenges.When a fast-growing fintech entered the mortgage brokerage space, they quickly discovered that speed was their biggest competitive advantage and their biggest bottleneck. Every loan file arrived with a stack of unstructured documents: bank statements in different formats, income proofs that varied from customer to customer,

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AI in EdTech: Building a domain-tuned exam proctoring system for reliable cheating detection

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As online examinations grow globally, EdTech platforms need accurate, scalable, and cost-efficient AI proctoring systems. This case study shows how InteligenAI helped a US-based exam proctoring platform replace generic vision APIs with a fully custom AI-based remote proctoring solution—designed to improve detection accuracy, reduce operational cost, and eliminate manual review bottlenecks. This work demonstrates InteligenAI’s

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GPT-5.1: Discover What’s New in OpenAI’s Latest AI Model

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November 13, 2025 OpenAI has officially launched GPT-5.1, introducing meaningful improvements in reasoning depth, responsiveness, and conversational flow. Rather than a raw capability jump, GPT-5.1 feels like an upgrade to how users experience the model: Faster where needed More deliberate when required and more controllable overall. This release marks another step toward AI systems that

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Why the launch of IndQA by OpenAI matters for global AI — and why India is key

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OpenAI’s IndQA benchmark shifts the conversation from translation to native, culture-aware reasoning. Here’s what it means for AI product teams, startups, and enterprises, Published by InteligenAI — 12 November 2025 In today’s age of large-language models (LLMs) and generative AI, one major gap persists: language and cultural depth. Most benchmarks, systems and deployments assume English

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3 open-source projects every engineer should try in 2025

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November 8, 2025 Open source projects for engineers are transforming development workflows. Discover three open-source projects (opencode, DeepCode, Llama-Factory) that bring AI into developer workflows: inside the terminal, from paper-to-code, and from model-to-deployment. Modern engineering teams want AI that fits their workflow. Whether you’re a backend engineer, a research scientist, or a DevOps lead, developer-native

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