Adapting to changing consumer requirements is a primary goal for any organization to sell better and progress in managing their business from the sales point of view. When a business fails to recognize the customer’s choice and preferences, catering to the relevant market becomes more and more of a stressful scenario.
Innominds
Innominds is an AI-first, platform-led digital transformation and full cycle product engineering services company headquartered in San Jose, CA. Innominds powers the Digital Next initiatives of global enterprises, software product companies, OEMs and ODMs with integrated expertise in devices & embedded engineering, software apps & product engineering, analytics & data engineering, quality engineering, and cloud & devops, security. It works with ISVs to build next-generation products, SaaSify, transform total experience, and add cognitive analytics to applications.

Recent Posts
How NLP-based Cognitive Capabilities of AI Chatbots Increase Business Interactivity
As conversational AI technologies gain traction, they substitute hard processes, becoming valuable assets to businesses that are seeking to gain a competitive advantage among peers. Automated processes reduce the burden on employees in every office space by taking away the most time-consuming and mundane activities that plug creativity.
As businesses are growing, serving customer queries is no longer restricted to direct and personal employee interactions but has instead moved to digital channels through interactive displays and service chat bots.
Cloud-Native Application Testing: Why it is Critical for Your Business?
For every organization, innovation and resilience is the only thing that keeps them motivated to keep going amidst a global pandemic.
Why Multicloud Adoption Implies Long-term Value Instead of Lowered IT Spend
In the absence of a planned cloud strategy, adopting a multicloud approach may lead to higher spending. A long-term value vs cost perspective will help enterprises realize higher benefits.
Essential Strategies to Overcome IoT Automation Testing Challenges
IoT application testing is an essential part of smart device development. Just like any other system, the IoT systems have to work seamlessly well in the desired environment during their deployment. Hence, it demands rigorous testing as they are often deployed in heterogenous application platforms with various infrastructural dependencies. The devices are also mostly located far from any
Centralized servers were established as the be all and end all of computing until it started to change as this form of computing is costly, hard to scale and resource intensive. Cloud computing emerged as the most flexible model of computing that could cater to a wider range of networking requirements. But computing needs have grown to the peripherals of the network with devices called as edge
Driving Smart Farming with Advanced AI, IoT, and Data Solutions
At the core of the advanced AI, IoT, big data and analytics-based solutions for smart farming is the collection and analysis of data for generating real-time relevant insights at scale and speed, leading to phenomenally higher yield and better utilization of resources.
Boosted by the growing adoption of advanced technologies, sensors, and the Internet of Things (IoT), could servitization become the default business model for smart manufacturers?
Most organizations spend thousands of hours creating QA tests for applications, meticulously breaking down the application and debugging it from release to release. This enormous amount of time spent in manual testing produces very little outcome as it slows down development and affects productivity. Automating the testing by injecting test automation scripts into every stage of the test cycle