Insights
What we've learned shipping AI systems: architecture, trade-offs and the failure modes worth knowing about in advance.
A pilot that hits 94% accuracy on a curated sample and then dies in review is the normal outcome, not the exception. The failure is rarely the model. It is everything the pilot was allowed to skip.
Read articleThe two approaches solve different problems, and most teams reach for fine-tuning when retrieval would have been cheaper, faster to update and easier to audit. Here is how to tell them apart.
Read articleModel development is rarely the largest line item. A realistic breakdown of where budget goes across discovery, data, build and the first year of running the thing.
Read articleDefects are rare, labels are contested and the answer has to reach the reject gate inside the cycle time. What actually determines whether a vision inspection system survives the factory floor.
Read articleDiscover how multiple specialized AI agents working together can solve complex business problems that single AI systems can't handle. Learn how PplTech builds multi-agent systems.
Read articleAI agents are powerful, but they also introduce unprecedented security risks. From prompt injection to data poisoning, learn how to protect your organization.
Read articleA comprehensive comparison of low-code automation platforms and full-code AI frameworks, helping you decide when to use visual workflows versus custom development for your AI projects.
Read articleLearn the fundamentals of artificial intelligence and how it can transform your business operations. From machine learning basics to real-world implementation strategies.
Read articleDiscover the most impactful ways businesses are leveraging AI to drive growth and efficiency. Real examples with measurable ROI from customer service automation to predictive analytics.
Read articleUnderstanding the key distinctions between ML and DL, and when to use each approach. Technical clarity for business leaders making AI investment decisions.
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