Effective ways industrial AI is revolutionizing manufacturing
Manufacturing processes are undergoing significant changes as advanced technologies, particularly AI in manufacturing, become more integrated into everyday operations. This transformation is empowering businesses to streamline production, boost product quality, and increase operational efficiency. In this blog, we will discuss three powerful ways industrial AI in manufacturing is driving these changes and creating valuable opportunities for companies to improve their overall performance. Predictive maintenance: Preventing downtime before it happens One of the most impactful applications of AI in manufacturing is predictive maintenance. Traditional maintenance models rely on scheduled checkups or reactive repairs, which often lead to unnecessary downtime and increased costs. However, AI-driven predictive maintenance takes a proactive approach by using machine learning (ML) algorithms and historical data to predict equipment failures before they occur. This predictive capability helps manufacturers avoid costly and disruptive breakdowns, ultimately saving both time and money. Automotive manufacturers, like Ford’s use of AI for predictive maintenance has decreased downtime and maintenance costs. costly interruptions. By employing predictive analytics, they can monitor critical equipment, such as robotic arms on assembly lines, for signs of wear and potential failures. This allows Ford to schedule maintenance proactively, minimizing downtime that could otherwise halt production and impact delivery schedules. Key benefits: Reduced unplanned downtime and increased equipment reliability. Lower maintenance costs by focusing on essential repairs. Optimized resource allocation and operational efficiency. AI-driven quality control: Ensuring consistent product standards Quality control is critical in the manufacturing process, and it is often one of the most time-consuming aspects of production. Traditional manual inspection methods can be slow and prone to human error. With AI-driven quality control, manufacturers can automate and enhance the inspection process to ensure products meet the highest standards with accuracy and consistency. AI-powered visual inspection systems can analyze production lines in real-time, identifying defects, inconsistencies, or any deviations from quality specifications with unmatched precision. For instance BMW integrates advanced AI-powered technologies, such as Car2X and AIQX, into its production processes, transforming vehicles into intelligent participants in their own construction. During production, AI-powered cameras and sensors continuously inspect each vehicle, identifying and reporting even the smallest defects. By leveraging computer vision and deep learning, these systems ensure that every car meets the highest standards of quality. This cutting-edge approach not only maintains exceptional quality control but also optimizes production efficiency, embodying BMW’s commitment to innovation and reliability through its AI-driven strategies. Key benefits: Improved product quality and consistency. Faster inspection processes with real-time results. Reduced waste and rework due to accurate defect detection. Accelerating business analytics with AI integration AI in manufacturing isn’t just about optimizing individual processes; it also extends to enhancing business-wide decision-making. By integrating AI-driven business analytics, manufacturers can gain real-time insights into their operations, supply chain, and market trends, helping them make more informed decisions. For example, General Electric (GE) uses its AI-driven Predix platform to gain real-time insights into its manufacturing operations, which helps to predict equipment failures before they occur and optimize production schedules. By integrating these advanced analytics across various operations, from equipment monitoring to supply chain logistics, GE is able to make more informed decisions, reducing downtime and improving operational efficiency. Using AI-powered analytics platforms, manufacturers can easily track performance metrics, uncover hidden patterns, and identify areas for improvement. Moreover, by automating data collection and analysis, manufacturers can significantly reduce the time it takes to gather insights, enabling faster responses to market demands and operational challenges. Advaiya’s advanced analytics solutions enable organizations to unlock actionable insights through enterprise performance analytics. We offer tailored cloud analytics empowerment to help manufacturers optimize their data and gain real-time insights into predictive maintenance models, AI-driven quality control, and much more. Key benefits: Accelerated time to insights for quicker decision-making. Data-driven business strategies that are more agile and adaptive. Enhanced forecasting and planning through AI-powered models. Why AI in manufacturing is a game-changer The implementation of AI in manufacturing goes beyond simple automation. It offers manufacturers the ability to improve productivity, ensure high product quality, and predict potential issues before they occur. By leveraging predictive maintenance, AI-driven quality control, and advanced business analytics, companies can stay ahead of the competition and maintain a strong foothold in an ever-evolving industry. AI is also making strides in areas like supply chain optimization and energy management. For instance, AI can predict potential disruptions in the supply chain, suggest the most efficient routes for material sourcing, and help manage inventory levels with greater accuracy. In energy management, AI systems can monitor and adjust energy usage in real-time, optimizing power consumption across manufacturing plants and reducing costs. Manufacturers who have integrated industrial AI in their operations are already experiencing significant improvements in operational efficiency, cost savings, and overall business performance. As AI technology continues to advance, the potential for transforming the manufacturing sector grows even further. At Advaiya, we help businesses adopt AI-powered solutions that integrate seamlessly with their existing systems. By leveraging the power of cloud analytics, business intelligence, and AI, we guide manufacturers on their journey toward greater operational success. Conclusion: Take the first step toward transforming your manufacturing process with Advaiya The manufacturing industry is undergoing a significant transformation, with AI in manufacturing leading the charge. Predictive maintenance, AI-driven quality control, and advanced business analytics are just the beginning of how AI is reshaping the industry. At Advaiya, we are dedicated to helping businesses adopt the right AI-driven solutions to improve efficiency, reduce costs, and enhance overall performance. If you’re looking to transform your manufacturing operations with cutting-edge AI technologies, contact Advaiya today. Let us help you unlock the full potential of AI in your business.
AI beyond Generative AI: Predict, innovate, and streamline operations
AI is rapidly transforming industries. While generative AI has gained attention for content generation, its potential extends beyond creation—enabling businesses to predict trends, streamline operations, and drive innovation. The power of predictive AI: Anticipating trends and outcomes Predictive AI is one of the most transformative aspects of artificial intelligence. Unlike generative AI, which focuses on creating new content, predictive AI uses algorithms and machine learning to forecast trends and outcomes based on data. This enables companies to make informed decisions, reduce risks, and optimize strategies. Here’s how predictive AI can be used: Customer behavior analysis: Predictive AI helps businesses anticipate customer needs, allowing for personalized marketing strategies. Supply chain optimization: In industries like manufacturing and retail, AI forecasts demand patterns, streamlines inventory management, and ensures that supply chains operate efficiently, AI forecasts demand patterns and ensures that supply chains operate efficiently. Risk management: In finance, AI predicts market trends, enabling investors to make more accurate decisions. By harnessing predictive AI, companies can stay one step ahead of the competition, focusing on trends before they materialize. Streamlining operations with AI AI is transforming operational processes in industries ranging from manufacturing to healthcare. While generative AI excels at creative tasks, AI systems designed to streamline workflows ensure businesses function more efficiently. Key areas where AI streamlines operations: Here’s how predictive AI can be used: Automation: AI-powered automation reduces human error and increases efficiency in repetitive tasks such as data entry, logistics management, and invoice processing. Maintenance prediction: Predictive maintenance in manufacturing and industrial settings prevents downtime by identifying equipment issues before they become critical. Workforce management: AI optimizes workforce scheduling, ensuring optimal use of resources and reducing downtime. By reducing inefficiencies, AI allows companies to allocate their resources more effectively, driving productivity and innovation. Innovation through AI: Expanding creative possibilities Innovation is another area where AI is making a significant impact, particularly through predictive algorithms. AI is not just revolutionizing processes but also helping businesses rethink entire strategies and business models. Product design and optimization: Predictive AI helps companies forecast the performance of prototypes and product models, enabling faster iterations and reducing time spent in the design and testing phases. Data-driven creativity: Predictive algorithms analyze consumer trends and preferences to inform creative decisions in areas like product development, marketing, and even design, enhancing personalization and relevance. Advanced problem-solving: Predictive AI enables businesses to tackle complex challenges, such as supply chain disruptions or market fluctuations, by providing insights that were once computationally out of reach. Whether it’s streamlining product innovation or modernizing decision-making, predictive AI fosters innovation in ways that continue to evolve. Generative AI: The catalyst for creative innovation While we’ve discussed AI applications beyond generative AI, it’s worth acknowledging how generative AI itself is fueling creative innovation. By mimicking human-like creativity, generative AI allows businesses to produce custom content at scale, significantly reducing the time and cost involved in the creative process. For example: Content creation: From blog posts to video scripts, generative AI creates relevant and high-quality content quickly. Image and video generation: Tools powered by generative AI help companies create visuals without the need for expensive design software or professionals. Code generation: AI now assists developers by generating code snippets, which accelerates the software development lifecycle. As generative AI tools continue to improve, businesses will increasingly rely on these systems to fuel their creative processes and drive further innovation. AI in decision making: Moving beyond automation While generative AI focuses on creation, decision-making AI helps leaders make better-informed decisions by analyzing vast amounts of data. Machine learning algorithms sift through historical and real-time data to provide actionable insights. This empowers businesses to: Optimize pricing strategies: AI adjusts pricing models based on supply, demand, and market conditions. Improve customer experience: AI helps companies tailor their offerings to meet customer needs, improving satisfaction and retention. Enhance marketing efforts: AI analyzes marketing campaign performance, suggesting areas for improvement and maximizing ROI. This combination of predictive analytics and decision-making AI enhances business strategies, delivering long-term success. The future of AI: A collaborative landscape The future of AI will be one of collaboration—where generative AI, predictive analytics, and decision-making algorithms work together to solve complex challenges. As these systems become more integrated, they will unlock new possibilities for industries to innovate, streamline, and predict with unprecedented accuracy. AI’s growing role in businesses, from generative AI that creates to predictive AI that anticipates, suggests that industries are poised for even more transformation. This shift towards a more AI-centric landscape emphasizes the importance of adopting a comprehensive AI strategy, ensuring businesses remain competitive in an ever-evolving market. Conclusion: Ready to leverage AI for your business? As AI continues to evolve, businesses that embrace it will gain a competitive edge. Whether through generative AI that fuels creativity or predictive AI that drives smart decisions, now is the time to integrate these technologies into your operations. Take the next step. Ready to harness AI’s full potential to predict, create, and innovate? Advaiya’s AI solutions can help you lead in the AI-driven landscape.. Our expertise in AI solutions ensures that your business remains at the forefront of technological advancement. Contact us today to learn how we can implement AI tailored to your needs.
Maximize your business potential with AI: Effective use of automation and analytics
Through automation and analytic systems, companies get to the highest level of achieving their business goals, making it possible to operate more efficiently and remain relevant in competition. At Advaiya Solutions, we believe that automation and analytics are critical not just for collecting data but also for helping businesses add tangible value by applying the data efficiently. Using advanced techniques such as AI and machine learning harness the power of automation and analytics and improve business activities as well as insights. The role of automation and analytics in modern business To some extent, it can be said that repetitive duties are eased with the use of automation, enabling the employees to put their emphasis on strategic matters. Analytics, on the other hand, turns raw data into meaningful insights. Together, these technologies form a powerful combination that can improve decision-making, reduce operational costs, and optimize resource utilization. Key benefits of automation and analytics 1. Streamlined operations Automation can dramatically simplify business operations by handling routine tasks, freeing up valuable time for employees to focus on higher-priority projects. Tasks such as data entry, reporting, and scheduling can be automated to ensure accuracy and consistency while also speeding up processes. In combination with analytics, automated systems can track and evaluate performance data, providing real-time insights into operational efficiency. This allows businesses to pinpoint areas that need improvement and implement adjustments as necessary. By leveraging analytics, organizations can also assess the effectiveness of automated processes and fine-tune them for even better results. 2. Improved decision-making One of the greatest advantages of analytics is its ability to transform raw data into actionable insights. By applying analytics to large datasets, businesses can make more informed decisions backed by real-time data and historical trends. This is particularly beneficial in areas like marketing, where understanding customer preferences and behavior can significantly impact campaign success. Automation further enhances decision-making by speeding up the process of gathering and analyzing data. AI algorithms can automatically detect patterns and provide recommendations based on the data collected, helping businesses respond quickly to emerging trends and opportunities. 3. Cost reduction Automation reduces the need for manual labor, which in turn can lead to significant cost savings. Automated processes tend to be more efficient and less prone to error, eliminating the costs associated with human mistakes. By automating mundane and repetitive tasks, companies can reallocate resources more efficiently and optimize their workforce. Similarly, analytics helps identify inefficiencies in operations, allowing businesses to focus on reducing waste and improving resource management. This contributes to lower operational costs and better overall financial performance. Leveraging AI for automation and analytics Artificial Intelligence (AI) plays a critical role in enhancing both automation and analytics. AI enables businesses to automate more complex tasks, such as predicting customer behavior, analyzing trends, and forecasting future outcomes. 1. AI-powered automation AI-powered automation goes beyond simple task automation by using intelligent algorithms to learn from data and adapt to new circumstances. This allows businesses to automate processes that require some level of decision-making or analysis, such as customer support chatbots or predictive maintenance systems. For example, at Advaiya Solutions, we help companies deploy AI-powered automation tools that can handle everything from basic customer queries to sophisticated data analysis tasks. This not only increases efficiency but also allows businesses to scale their operations without sacrificing quality. 2. Advanced analytics with AI AI enhances analytics by providing deeper insights into data. Machine learning algorithms can analyze vast amounts of information and identify patterns that might not be apparent to human analysts. These algorithms can also be used to make predictions about future trends or outcomes, allowing businesses to stay ahead of the curve. How Advaiya Solutions helps you achieve success At Advaiya Solutions, we specialize in helping businesses implement automation and analytics that deliver real results. Our team leverages leading AI and machine learning platforms, including Microsoft Fabric and Azure Synapse, to build comprehensive automation and analytics strategies that are tailored to your unique needs. 1. Data infrastructure consulting We help businesses organize and manage their data more effectively. Our data infrastructure consulting services focus on aggregating structured and unstructured data for comprehensive analytics and insights. This enables businesses to get the most out of their data by turning it into valuable information that can drive decision-making. 2. Application integration Our expertise in application integration ensures that your automation and analytics systems work seamlessly together. We develop integrated data infrastructure solutions that merge data from multiple applications, providing a unified view of critical information. This centralizes data access, allowing for easier and more efficient analysis. 3. Security and AI integration Security is a top priority when implementing AI-powered automation and analytics solutions. We work to ensure that all systems are secure and compliant with industry regulations. By integrating security measures into your data infrastructure, we help you safeguard sensitive information while still enabling advanced analytics and automation. 4. Real-time analytics Our real-time analytics solutions enable businesses to make data-driven decisions faster. By providing timely insights into operational performance, customer behavior, and market trends, our solutions help businesses respond quickly to changes and optimize their strategies. Conclusion Automation and analytics are essential tools for maximizing business potential. By automating repetitive tasks and using analytics to gain deeper insights into your data, you can improve efficiency, reduce costs, and make more informed decisions. At Advaiya Solutions, we specialize in deploying AI-powered automation and analytics solutions that help businesses achieve success. From data infrastructure consulting to application integration, we provide end-to-end services that ensure your systems work seamlessly together and deliver real value. Contact us today to learn how we can help you leverage automation and analytics to drive your business forward.
Microsoft Syntex – Simplifies document management with AI brilliance!
As organizations go digital, they’re accumulating a lot of digital stuff. Businesses use content like proposals, contracts, invoices, designs, plans, and training videos. But here’s the thing: important info is scattered everywhere, and digging it out from thousands of documents each week is a real hassle. In the age of AI, can’t we simplify the process? Instead of sorting through hundreds or thousands of files, imagine one smart solution extracting data, streamlining searches, and understanding content automatically. Can we directly build content understanding and classification capability into the content management flow? SharePoint stands out as a leading platform for efficient document management, widely adopted by organizations. Having utilized it for years, I appreciate its robust features—streamlining the loading, storing, organization, and retrieval of documents. SharePoint excels in sorting files to your preference, facilitating easy search and retrieval. Beyond these essentials, it offers crucial document management features such as version control, configurable permissions, and onboard editing tools. What sets SharePoint apart for me is its user-friendly customization, allowing the addition of custom columns for capturing file metadata. Moreover, creating multiple tailored views caters to diverse business roles, enabling filtered and sorted displays. These customizable views can be strategically placed within a SharePoint site, efficiently directing individuals to the precise information needed for their tasks. Hello, I’m Kamal. I’m an experienced communications and learning professional with a background in SharePoint. I’ve been an end-user and a designer, creating solutions using SharePoint and Microsoft 365 services. Extracting valuable insights from documents within SharePoint libraries has been one of the most challenging tasks I’ve tackled. On the SharePoint platform, when storing documents or filling out forms, it would be ideal if information could automatically be extracted into SharePoint libraries. For instance, imagine automatically importing numerous proposals into a document library and having SharePoint recognize clients, participants, costs, and timelines. You could also extract totals from a group of contracts and add that data directly to a SharePoint library column. While possible, it currently demands significant manual effort, time, and technical skills. Some users have started using Power Automate workflows to extract limited information from specific document types, but this requires technical expertise and a separate workflow for each document library. I have a solution for you! So, I have a treat for you. Welcome to Microsoft’s SharePoint Syntex. Microsoft Syntex is a Microsoft 365 service that uses advanced content artificial intelligence (AI) and machine learning to provide an end-to-end intelligent document processing solution for your organization. Microsoft Syntex is a set of content Artificial Intelligence (AI) services available as a premium offering with Microsoft 365 to help you discover information, process content, and ensure content compliance with your organization’s documents stored in SharePoint. SharePoint Syntex. Welcome to Microsoft’s SharePoint Syntex! Syntex, part of Microsoft 365, is a powerful service that leverages advanced artificial intelligence (AI) and machine learning to offer a comprehensive solution for intelligent document processing in your organization. SharePoint Syntex. This set of content AI services, available as a premium feature with Microsoft 365, is designed to assist you in discovering information, processing content, and ensuring compliance with your organization’s documents stored in SharePoint. SharePoint Syntex. Syntex simplifies the extraction of information from various documents and forms, providing a fast and efficient way to access essential business data. The best part? It doesn’t require coding, making it accessible to users without a developer background. With automation and machine learning, you can effortlessly transform business content into valuable knowledge. SharePoint Syntex. If that sounds intriguing, you’re not alone – it’s captivating to me too! Syntex utilizes AI to automatically read, tag, and index large volumes of content, connecting it where it’s most needed – in search, applications, and as reusable knowledge. Syntex manages your data throughout the content lifecycle with robust analytics, security features, and automated retention. SharePoint Syntex. Exciting, isn’t it? SharePoint Syntex. Conclusion SharePoint Syntex. I believe Microsoft Syntex is a great way for companies to unlock valuable information from their content without the hassle of manual effort. However, it’s still in its early stages and evolving quickly. For the latest tips, troubleshooting, and updates, I recommend checking the Power Apps Community Forum and Microsoft Tech Community resource page for Syntex. SharePoint Syntex. Remember that Syntex may not be suitable for everyone due to its cost and setup time. Yet, its potential is evident, and I anticipate many businesses will find value in this powerful tool. I hope you enjoyed reading about Microsoft Syntex and got some ideas to try!
Vertical, Baby, Vertical: Data, AI, and Residential Real Estate
In business and technology, every era has a defining concept, which absorbs the mental cycles of the entire industry. In technology, with the Silicon Valley-hyperbole machine at play, the concept often becomes larger than life. Over the past 5 years, we’ve had twin concepts that have emerged into the limelight and dominated the technology narrative: Data and Artificial Intelligence (AI.) Metaphors and prognostications have abounded. Some have called Data “the new oil.” Others have suggested that AI will disrupt and displace all of society as we know it, and jobs certainly. Dreaming and opining is great, but they have side-effects too. One of these is the difficulty that has arisen in separating rhetoric from reality when it comes to claims about Big Data, AI, and their ubiquity. Indeed, separating the wheat from the chaff is the most important part of the story- especially for investors who are sinking tens of billions of dollars into these claims. Certainly, there are amazing things happening in the Big Data and AI spaces. There are about a dozen behemoths- companies and governments that have the money and human-power to hire tens of thousands of people in the Data and AI fields and who have built the lattice/foundation of a potential AI-based economy. These are the usual suspects- players like Microsoft, Google, Amazon, Apple, and the US and Chinese governments. But what of the last mile? The context and vertical knowledge that is necessary to “bring AI home?” In an article in Information Week, I suggested, in this spirit, that “Vertical AI is the New Black.” I strongly urge investors, buyers, and industry-watchers to kick the “vertical” tires on all companies that claim to bring AI into a particular space to “disrupt” or make change. In the residential real estate space, we see this playing out. Residential real estate is the largest single asset class in the world. In the US alone, the aggregate value of RRE exceeds $35 trillion. The numbers are staggering; the industry thus deserves “real” AI and not just its rhetorical counterpart to help drive value, efficiency, and innovative solutions for the entire- currently cumbersome and opaque-processes. If you ask scientists, they’ll tell you that the questions asked are often more important than the answers provided. We see this play out in the form of simple questions that lead to complex processes to answer. Take the basic question, “Why is House 1 valued at $X and House 2 valued at $Y.” In reality, there are thousands of variables- all of which are dynamic- that impinge on this question and inform the answer. Now, imagine asking that at scale- for, say, a million houses? You can see where both the speed and scale of AI comes in but also of the importance of the right approach to data coupled with a deep knowledge of the real estate vertical. One cannot approach the problem tabula rasa. Though perhaps a shameless plug for my company Quantarium, I must share at this point the work of Dr. John Smintina, co-founder and Chief Analytics Officer of Quantarium. He had the insight that genetic algorithms would be particularly useful for the stochasticity of real estate valuations; he and his team then built the highest ranking Automated Valuation Model in the business, which exceeds all others in breadth and precision simultaneously. He took a concept from Science and highly verticalized it. There are of course many other such examples. Vertical AI is not only the new black, it is the epicenter of the next wave of innovation. Romi Mahajan I’m an accidental marketer. My skills are in building deep relationships, seeing markets before they burgeon, and in applying socio-political concepts to business. I have 3 pillars on which I pursue opportunities: People, Impact, and Autonomy. Contact us by filling the form below for Data, AI implementation and integration.
Artificial Intelligence: A Silver Bullet for Housing?
Artificial Intelligence is the technology and business topic of the decade. With advances in AI- both real and rhetorical, realized and claimed- new things are possible in almost all business scenarios. Traversing business-to-business and consumer scenarios, AI has provided a silver bullet of sorts to organizations world-wide.Now, such claims are rightly met with skepticism. Silicon Valley’s force-field has created so many overpromises and in the light of such hyperbolic pronouncements, very few results to match; however, there have been breakthrough products and services that have altered the way billions of people live, work, play, and exist. Whatever one’s politics and whatever one’s view of environmental stewardship, it would be a fool’s errand to deny that products, services, and concepts like Microsoft Office, Apple iPhone, Google Search, or Amazon’s one-day fulfillment for e-commerce have created an indelible imprint on society. Same with the work of hundreds of companies- less storied but equally important- like Xerox, IBM, Sybase, Adobe, Oracle and others.AI represents a phase-transition, a punctuating mark in the general equilibrium of progress in technology and business. Thus, the comment about AI being a silver bullet.I amended the claim, however with “of sorts.” For indeed there are no panaceas, no perfect products, no infallible theories, and no permanent fixes to any of the vexing problems in any particular vertical industry. But there are foundational technologies and paradigms that give us the best shot at speedily solving problems at the scale and in the time-frames needed to enact real, even fundamental change.I argue that in the world’s largest Asset Class- residential real estate or “housing”- that AI is just such a foundational paradigm.Take the US Housing Sector for instance. There are 103 Million residential plots in the US with an aggregate value in excess of $32 Trillion. Depending on the year, about 5 Million homes are bought and sold every year, though many other monetizable transactions take place- including refinancings. The housing ecosystem has a variety of players, from both the private and public sector and appears labyrinthine to those who don’t work in the sector.For most buyers, even questions as simple as “Why is this house worth X?” remain unanswered. Two different housing “experts” will provide two different answers and ten experts will provide ten answers. Moreover, even if consistent, acceptable answers were available, they would be available long-after the time frame in which they were needed. Here, AI comes in- speed and scale can be consistent with deep context and multivariate factoring.I am not qualified to offer a primer on AI. I am on the commercial side of the industry, but as I look through the looking glass and see not only what could be but what has already been done, I remember the image of the silver bullet. Though an imperfect metaphor, it provides the hope and promise that we can democratize and transform the world’s biggest Asset Class withAI. Please email me at romi.mahajan@quantarium.com with comments or your own silver bullet ideas! A nice gift from team Quantarium awaits the sender of the best idea.
The brave new world of practical AI
Every five years or so, the technology world is illuminated and animated with a concept- either a new idea or an advancement in an idea that has been around for decades. These concepts take center-stage in an already crowded “Techosystem” and are developed in the press, at events, and in all manner of conversations. Further, the power of the technology industry- backed as it is with well-resourced marketing—compounds the amplitude of the hype. In this sense, we are undeniably in the era of Artificial Intelligence (AI). There is no doubt about it- AI is real. A storm that has been gathering for 6 decades, AI has reached an advanced state in which scenarios thought impossible 5 years ago have been made possible today. Still, we have barely scratched the surface here, with possible outcomes that at once delight and frighten. That said, the technology hype-machine has also created an enormous number of false claims about AI. Evidence for this is abundant as all-kinds of companies claim great advances in AI and use phrases like “AI-enabled” to describe their products and services, even when doing so has nothing to do with technological advancements and more to do with sleight of hand. Now, extended claims and futuristic thinking are keys to innovation so it’s okay to be patient with some loose claims but when they collectively become an epidemic, we waste too much time and precious energy in separating the wheat from the chaff. Here, I believe it is important to introduce a new term- “Practical AI.” Here, we readily distinguish between theoretical and practical as well as hype versus real. We must be exacting in our use of the term and encourage entrepreneurs and other leaders to be honest as well. It is okay to say “we are developing AI products or AI solutions” versus claiming that an after-the-fact rhetorical bolt-on is sufficient. Dreaming is wonderful but lying is not. The implications of this are vast. Not only with reference to the waste of time and money mentioned above, but also in the investment community which is backing “AI” companies to the tunes of tens-of-billions. Investors have to shrewdly determine if the “AI” being referred to is “Practical AI” or some dreamy derivative thereof. Words matter, even in tech. Let’s make sure we remember this in the era of AI.
Quantarium’s REAL AI for REAL Estate
At Advaiya, we have the pleasure of running across dozens of amazing companies- in technology, services, and product development. These companies range from fledgling startups to the world’s largest technology companies. With such a large range at play, one might ask what the commonalities are. Indeed, that is the million-dollar question- what is the taproot of greatness in companies of any size? A common answer is “People.” Great people make great companies, or so the logic goes. We believe this is true but only partly so. We believe strongly that the sine qua non of greatness is a combination of people and timing. Markets are dynamic- they change. No doubt, this dynamism does not necessarily spell doom for the incumbents but it does bring into question the need for timed adaptation. The history of business is littered with the carcasses of projects and companies that were “too soon” or “too late.” These stories needn’t bear recitation- we’ve all heard about these “Kodak Moments” a lot. Given this, we get excited when we find companies that seem to have their timing perfectly aligned with Market dynamics. One such company is Quantarium, an Artificial Intelligence company in Bellevue, WA. With a team of Data Scientists, Mathematicians, Commercial Executives, and Entrepreneurs, Quantarium applies AI to the vast and important residential real estate industry. The numbers are staggering- residential real estate is the world’s largest asset class, with a world-wide estimated value of almost $200 Trillion. In the United States, this number is closer to $30 Trillion. Despite the size of the asset-class and market, real estate data is still a developing business. Traditional parts of the Real Estate value chain are often isolated from one another and no particular part has comprehensive, timely, and contextual data at its disposal- in an actionable and time-sensitive set up. This is partly due to infrastructure, partly to culture, and partly because the questions surrounding Real Estate are incredibly complex. Indeed, we find that AI, Deep Learning, and scientific Big Data management are necessary to create an accurate and repeatable analytics platform in this multi-variate industry. That’s why we love Quantarium. With the largest and most sophisticated Data Lake in the business and with the speed, scale, and insight driven by AI, they are enhancing the industry. Consider for instance their AVM solution– the best in class- which helps mortgage owners, Banks, and other financial institutions value their residential real estate assets or their Portfolio Analytics that allows for propensity models, if/then scenarios, and other focused and relevant solutions- game-changing solutions that are directly applicable to today’s housing market. This brings us back to the notion of timeliness. Not all claims around Data and AI were paid off in reality; claims abound. Quantarium however developed these solutions painstakingly and got them right before releasing them into the wild. We believe timing is on their side. We are impressed but not robotic cheerleaders. Much remains to be seen, but from our vantage point, Quantarium is a Real AI company that offers Real value to one of the largest markets on the planet. We, at Advaiya, are happy to be a trusted partner of Quantarium supporting their solution vision for Data and AI in the Real Estate industry.