TALKING

Machine vision does not just have to be a way to compensate for labour shortages or validate worker decisions . Machine vision can be the mechanism used to build trust in the brand and protect the bottom line . Real-time analytics and data capture capabilities can help engineering teams become confident that defective parts or vehicles are not slipping past human inspectors and enable quick intervention when issues are identified .

Many automotive OEMs and suppliers likely turned to machine vision in the past to make it easier to meet stringent production tolerances , ensure precise quality control , and keep pace with evolving industry standards .

Sabah Corm , Marketing and Innovations Director ,

IT Max Global

It also meant systems were pieced together over time to meet the need for new capabilities to satisfy increasingly complex production demands , maintain consistency with inspections , and reduce defects .

Integrating cloud , CRM , AI to boost real estate buying experiences

With the UAE ’ s real estate sector continuing to experience market demand , technology has played a vital role in enabling real estate brokers and agents to provide exceptional buyer experience . By leveraging cloud-based omnichannel contact centre that features advanced communication tools and AI-powered chatbots , real estate agents can provide personalised and automated customer communication support , resulting in enhanced customer engagement and improved sales performance .

CRM tools centralise customer data , enabling agents to track interactions , manage leads effectively , and tailor their approach to individual clients . AIdriven analytics offer valuable insights into market trends , allowing agents to identify potential opportunities and optimise their sales strategies .

Dialling modes , AI-powered features , and automated tasks increase talk time and significantly improve sales performance . The concurrent agent model enables agents to handle multiple communication channels simultaneously , improving response times and customer satisfaction .

AI-powered tools provide agents with accurate property information in realtime during calls , enhancing customer engagement . Integrating with CRM solutions offers agents a unified interface for dialling and accessing customer interactions , improving data accessibility and efficiency .

CRM tools provide a centralised platform for tracking and nurturing leads . Personalised communication and targeted marketing campaigns improve conversion rates . Tracking client history and interactions allows agents to offer personalised recommendations based on individual preferences and needs .

AI analytics provide insights into market trends , enabling agents to identify potential opportunities and optimise their sales strategies . Cloud-based solutions offer flexibility to scale operations as needed to meet changing business demands .

By leveraging the combined power of these technologies , real estate companies can achieve significant improvements in both business performance and customer satisfaction .

It is difficult to maintain higher throughput and regulatory compliance without automating . But in the effort to gain efficiency and ensure repeatable accuracy , the automotive industry ended up with a collection of various software packages and related challenges .

As the automotive industry evolves , machine vision software must evolve with it . The automotive industry must be able to make incremental changes to machine vision system as business needs change , as we are seeing with the growth in electric , hybrid and autonomous vehicles .

A unified software platform should not only handle current tasks but also support future technologies such as AI-driven inspection and deep learning models . This flexibility ensures that as electric and autonomous vehicles require more complex inspections , plant software will scale to meet those demands without requiring a major system overhaul .

So , next time there is a conversation about automating inspections , the technology provider or system integrator should be asked if the system design they are recommending can be set up to run from a single software suite , even if the hardware is from different vendors .

If the answer is yes then other , important questions can follow . These should include questions about interoperability , data security , the ability to scale the solution , support for 2D , 3D inspection , current and future AI applications including deep learning models , and training time needed .

Swapping out hardware is easy , and the right software will make future workflow updates feel like minor tweaks rather than major overhauls . Engineering teams and programmers should focus on finding flexible , futureproofed software that can run any hardware they want . p

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