[Exclusive Interview] This Startup Is Empowering Businesses With Enterprise AI Solution: How It Works?
Recently we interacted with Sagar Mahurkar, Director of Technology, Findability Sciences, and asked him about his company’s vision, and their future plans.
Here are the highlights from the interview:
- Kindly brief us about the company, its specialization, and the services that your company offers.
Leading enterprise AI company Findability Sciences assists enterprises worldwide in realizing the full potential of data. We help customers from all sectors and regions ramp up the data-to-AI transformation journey and develop their IP and data science skills while strategically executing to yield real financial ROI. As we help businesses across the globe address their most complex and pressing business challenges, we empower them by leveraging the power of data, cognitive computing, and AI. Simply put, we help traditional businesses through digital transformation by transforming them into data superpowers.
Our broad range of services spans various sectors, including manufacturing, retail, media, and communications. Findability Sciences has five main product lines. Findability, Findability, and AI. ERP-Max and the recently introduced Findability.Accelerate, a solution that gives businesses the foundation and resources they need to become “AI-ready” and move quickly and effectively toward implementing enterprise AI. Additionally, Findability.AI, our multi-award-winning proprietary platform, integrates machine learning, computer vision, and natural language processing to assist businesses in enhancing their AI readiness. - How are Big Data and AI evolving today in the industry? What are the most important trends that you see emerging across the globe?
For enterprises aiming to create highly successful and economical businesses, AI has become an essential tool. Today, companies may use a wide range of plug-and-play AI solutions, and it is evident that there is an insatiable need to find new data sources to support them in achieving their core business goals. Data is the next big thing for firms using AI, becoming a significant differentiation. Organizations driven by data have a 19 times higher probability of success, according to data and analytics research (powered by AI). - Emerging technologies power intelligent digital processes, enabling machines to aid humans in their work. According to a PwC report, artificial intelligence may have a $15 trillion impact on the world economy by 2030. There aren’t many technologies with this kind of potential. Some of the significant and emerging trends that are being seen worldwide are:
- Businesses in industries including manufacturing, banking, and financial services will continue to use AI in innovative ways to improve their performance and operations.
- “Big data” is simply insufficient today. Businesses must adopt the idea of “wide data” to deliver relevant insights and valuable analytics for the best decision-making. Wide data concentrates on value, while big data concentrates on the so-called “three V’s” — volume, velocity, and value
- Wide Data is the process of gathering information from all sources within the system while obtaining information from beyond the company’s firewalls, such as news releases, financial data, socioeconomic data, traffic data, and meteorological data, to fully realize its potential
- The influence of AI will be at least as great as how the internet altered every aspect of business interactions
- What is Information Architecture? Could you please elaborate on why it is important for AI implementation?
Start-ups and major corporations alike are familiar with the artificial intelligence (AI) ‘s buzz due to its increased visibility. However, the need for other components, such as high-quality data inputs, applied engineering principles, and, most importantly, Information Architecture, plays a crucial part in the foundation upon which artificial intelligence systems can be constructed. Unstructured information architecture can also be successful when applied to ML and artificial intelligence, which can comprehend and interpret algorithms. However, that is not the case; before these systems start to work their magic, curated tech talent is needed. As a result, any business must be ready to use information architecture effectively to benefit from artificial intelligence capabilities.
We have recently introduced Findability.Accelerate, a solution that provides the necessary tools and framework to equip enterprises to become ‘AI-ready’ and expedite their AI journey. Findability.Accelerate brings information architecture to enterprises powered by solutions built on partner products and tech talent to get optimal business outcomes and return on investment. This three-pronged approach works towards expedient and efficient enterprise AI implementation. - How important is having the right tech talent? What defines a perfect team in a company that provides AI solutions?
The search for the right tech talent is becoming more and more complex. Discovering great talent doesn’t help if they don’t want to work for you, and employing them doesn’t matter if they quit the position soon. Businesses must invest concurrently throughout the “recruit to retire” life cycle. The first step in achieving this is creating a digital talent engine, a dedicated team overseeing every aspect of the employee experience, from recruitment and onboarding to creating new career paths and ongoing skill development.
Why would technology’s most prominent talent want to work with you? While compensation is crucial, the best applicants also care about using cutting-edge technology, developing their skills, becoming a part of a culture that appreciates technology, connecting with a meaningful cause, and, most importantly, working on challenging and inspiring problems.
Today, it isn’t easy to see a company prosper without a solid tech talent foundation. Companies cannot expect to realize digital promises’ benefits unless they embrace that overwhelming fact and make a concerted effort to hire the best tech talent.
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