The coronavirus pandemic may dramatically shift the way we live and work. Its difficult to imagine and recreate that normal what we were used to pre COVID-19. People have lost their jobs and as a result there is a significant rise in the various types of insurance claims.
It only means the insurance companies will struggle to keep up with significant increase in calls to their call centers.
With the growing demand of customers seeking attention,Insurance companies like many others cannot scale their human resources capabilities on demand to answer every single call. And perhaps the economics of scale does not allow that as well. Companies will have to rethink the way a customer are served yet by fulfilling the objective of their own existence.It is highly unlikely that companies can still cram agents into tightly packed call centers. Rather they will have to find ways on how, customers can be engaged in self-service digital experiences and be connected.
Pypestream is conversational AI built for scale. Built to usher the customer-centric philosophy enterprise into the digital age with “always-on” automation. No more big call centers, no more single-task chatbots, no more embarrassing NPS scores and no more cobbling together technologies from multiple vendors. This could be a high time to elevate your customer experience with a full-stack platform, military-grade security, and the only patented B2C messaging carrier purpose-built to handle any volume.
The recent measures to support the economy during the COVID-19 pandemic, such as default and treasury lines, have resulted in an abnormal flow of orders to the banking sector, which is having significant difficulties in operationalizing the response to its customers in a timely manner. The speed of response to these credit lines is of critical importance for the operations of many companies, so delays in the response may result in uncertainties and instability.
Through its network of reference partners, DocDigitizer is installing integrated document validation and remote signature solutions in record time, via AI/ Machine Learning. This enables financial entities to accept bank service subscriptions completely remotely and in line with the directives and requirements of Banco de Portugal, while also enabling banks to reduce order processing time to 60 minutes without occupying their back office. In addition to the national market, this solution is also being adopted by several leading financial entities in Europe, leading to exponential growth in the use of DocDigitizer.
In another context companies are used to creating, acquiring, and accumulating terabytes of unstructured knowledge. And these are often the most important data assets the company owns. Yet what happens to all that knowledge overtime? After 90 days most of these asset will never be used again. Which means a lack of accountability exists in the company’s culture at the same time a need for serious thought was not realized. Then again the argument could be that all these data needs to be stored and processed. Which is a good argument on its own. However, in order to do that financial burden could be heavy and perhaps unsustainable on a long run.
Lucy reads , watches , listen and learn all the data you share with her. She finds answers and insights across all your files such as powerpoints , keynotes , pdf , images , word documents, videos, audio and more.
Lucy is trained in natural language processing with ability to produce exact results in its original form instead of list of search results. Lucy is an answer engine that gets smarter overtime with the ability to remember all the assets that was tagged. Transforming terabytes of valuable enterprise knowledge into instantly searchable answers.
Ability for the machine to understand the physical environment is opening a lot of opportunity across multiple industries. For example understanding what is happening with your stock. Even if means vending machines across the globe. Computer vision and all these new abilities today are driven by new technology called deep learning. In the past the engineer would design and code the model to computer vision. But deep learning is a different paradigm, it’s the machine that codes the computer vision models.
The fact that it’s a different paradigm it creates two huge challenges for companies who wants to do this. It’s a different process as its not an engineering process rather a scientific process. And to work on the scientific process requires special resource or talents called research scientists and they are very expensive and hard to find.
The second challenge is that you need tools for any processes. In fact with companies such as Google, Facebook, Microsoft more than 90% of their investment for deep learning and computer vision goes first to building tools before they build actual products.
Allegro AI is a pioneer in deep learning and machine learning software tools. With Allegro AI’s suite of enterprise and open source solutions, businesses are able to bring to market and manage higher quality products, faster and more cost effectively. Whether you are an expert or new to the field, you can use Allegro Trains to manage and track your experiments and collaborate with your colleagues. Leverage ML-Ops and distributed training with no heavy lifting required from DevOps. Scale up your workflows and move to deployment leveraging powerful data management and pipeline building features; enhanced security, managed services & support plus other enterprise features.
In an interview with Pramod Dhakal Nir Bar Lev Co Founder At Allegro AI shares a deep insights on how his company is helping the startups as well as large enterprises.
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Fashion retailers across the globe are struggling to survive. On the store sales are non-existent due to the closure of all the physical store. For some business owners they must work extra to keep up with the unproportionally lack of human resources to support the whole value chain. Again for some they need to rethink and question about their own involvement in fashion industry.
As the world approaches a new normal with much slower pace. The downfall of fashion industry will continue.
To keep this industry alive, disruptive new innovations are required that can redefine the whole clothing manufacturing ecosystem. The large workforce who are currently unemployed can be reengaged while keeping the mother nature healthy.
Savitude builds retail profits by solving fit for diverse customer populations. Savitude transforms retail using AI hyper-personalization to build intelligent assortments serving all shapes and proportions increasing conversions 11%; classifies clothing assortments directly from e-Commerce images, creating accessorized outfits automatically so shoppers can instantly find their best choices.They use artificial intelligence to design collections and capsules in fashion.
- Their technology combines predictive modeling with machine learning to help retailers increase sales through better fit, product-market match and reduced returns.
- Their latest feature helps designers efficiently create new designs from existing product so that unsold inventory can efficiently be updated and turned into sellable product.
- There is an underlying sustainability play at the core of what they do.
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Digital transformation offers a lot of promises however, its up to the decision makers and leaders to take necessary steps to keep their businesses afloat. For customers they need better services delivered as efficiently as possible. And thus we have seen how artificial Intelligence can support digital transformation. Offcourse its a matter of seeing where AI can be used to the advantage and offer better services. Its the businesses who must constantly redefine their existence by seriously discovering ways in which they can deliver service to their customers.