Rajesh Iyengar, Bestselling Author and CEO of Lincode Labs
The organization behind Rajesh Iyengar, Lincode Labs
Lincode CEO Rajesh Iyengar's handbook on reliable AI for manufacturing has reached Amazon bestseller status and gained a spotlight in New York's Times Square.
DETROIT, MI, UNITED STATES, September 16, 2026 /EINPresswire.com/ — The book authored by Lincode Labs CEO Rajesh Iyengar, titled Teach the Factory to See: How Production, Manufacturing Engineering, and Quality Teams Make AI Inspection Dependable, has earned the designation of an Amazon best seller (https://youtu.be/xXcc-ildpv4), along with a feature in New York's Times Square (https://youtu.be/ueJO6Va3EcU).
These accomplishments highlight a core question that sits at the center of how manufacturing is adopting artificial intelligence: what is required to ensure AI inspection is dependable when operating on an active factory floor?
Within his best-selling work, Iyengar lays out a usable framework to address this issue. Leveraging insights from his work on real-world factory implementations, Iyengar links the technical choices behind AI vision to the day-to-day operational concerns of production, manufacturing engineering, and quality assurance teams.
The book puts forward a key premise: achieving dependable inspection relies on coordinated decisions spanning people, processes, optics, data, and technology. A camera's ability to capture imagery and a model's capacity to classify it represent components of a broader system designed to maintain consistent decisions under genuine factory conditions.
Iyengar explores the divide between a promising AI demonstration and a system that gains the confidence of those managing a production line. Through examples drawn from factory settings, the book looks at how lighting, reflections, surface contamination, and shifting production variables affect inspection outcomes. These specifics provide readers with a clear grasp of why an approach that appears effective in a controlled setting might need considerable engineering and operational groundwork prior to actual deployment.
The text also tackles the necessity of outlining the inspection requirement before choosing the technology. Teams must reach consensus on what defines a defect, which attributes need measurement, and whether the planned inspection method can identify the relevant condition. This method gives leaders a basis for assessing technical options and establishing meaningful standards for acceptance.
Teach the Factory to See enables manufacturing leaders to pose more incisive questions regarding AI investments, readiness for deployment, and tangible production value. Its insights apply to organizations starting their first visual-inspection initiative, working through a difficult pilot phase, or looking to scale a current system across more lines and facilities.
Iyengar approaches quality inspection from a business standpoint, analyzing how missed defects and false rejections impact workflow, expenses, and customer trust. Iyengar describes how a rejected good part can trigger extra handling, reinspection, or scrap, while a defect that goes unnoticed may add further cost as it advances through production and ultimately reaches the buyer. Recognizing these effects assists teams in linking inspection performance to the wider financial picture of manufacturing.
Human knowledge represents another key focus. The book underscores the importance of operators and quality engineers, whose expertise is vital for training, overseeing, and enhancing manufacturing AI. Their grasp of acceptable variation, production circumstances, and frequent issues helps shape systems that are both usable and reliable for people.
Iyengar's concept of Industry 5.0 positions human judgment as central to technological advancement, illustrating how intelligent systems can enhance workforce capabilities. The book examines the collective duties that arise when production, engineering, quality, and technology groups collaborate to embed inspection into routine operations.
It goes beyond the immediate pass-or-fail decision as well. Iyengar outlines how traceability, defined responsibility, and feedback from inspection can support organizations in investigating recurring problems and steering corrective measures. Iyengar's viewpoint connects visual inspection to the broader objective of creating a factory that learns from its operational history.
Targeted at engineering managers, quality leaders, plant managers, operations executives, and their support teams, Teach the Factory to See makes complex implementation topics approachable without demanding that readers be data scientists. It provides a shared framework that teams can apply during project assessments, vendor conversations, and manufacturing strategy planning.
With its bestseller status and Times Square feature, Teach the Factory to See brings wider attention to Iyengar's grounded outlook on where manufacturing AI is headed.
Rajesh Iyengar serves as CEO at Lincode Labs, an AI visual-inspection firm dedicated to manufacturing quality. Iyengar's book brings together his background in technology, entrepreneurship, and factory deployment to assist manufacturing organizations in aligning AI capabilities with production requirements.
Teach the Factory to See: How Production, Manufacturing Engineering, and Quality Teams Make AI Inspection Dependable is available for purchase on Amazon (https://www.amazon.com/dp/B0HHYMQ27Y).
Nitin Kartik, CEO at Caribou Strategic, supported Iyengar in bringing his best-selling book to publication.
ABOUT LINCODE LABS:
Lincode Labs builds AI-driven visual inspection solutions designed to help manufacturers identify defects and reinforce quality control. Under the leadership of CEO Rajesh Iyengar, the company combines artificial intelligence, machine vision, and manufacturing expertise to tackle inspection challenges in live production settings. Lincode partners with manufacturing teams to align technology with operational requirements, enabling more consistent inspection decisions and allowing people to apply their skills toward improving factory performance. For additional details, visit https://lincode.ai
ABOUT CARIBOU STRATEGIC:
Caribou Strategic turns CEOs into best-selling authors (the gold standard of thought leadership) using a 100% pay-for-performance approach (pay ZERO upfront, and only pay per week your book achieves Amazon bestseller status – which less than 2% of books achieve according to Forbes), managing all the work including ghostwriting, cover design, launch, promotion, publicity, and more. For additional details, visit https://cariboustrategic.com/p
Nitin Kartik
Caribou Strategic
+1 847-652-2149
email us here
Rajesh Iyengar, a Caribou Strategic client, CEO at Lincode Labs, and best-selling author, sees his book 'Teach the Factory to See' showcased in New York Times Square
