Tag: Artificial Intelligence

Enterprises have been using Machines to improve efficiency and productivity for long, though it may be advance machinery or shifting to robotics or cobots to further improvement, the need to increase efficiency is consistent. Machine Learning is the next thing which is helping enterprises to use the machines to improve and work more efficiently.

Customer Support is undoubtedly one of the biggest cost centers in modern-day operations, for big or medium scale businesses.

And Customer Support is also considered as one of the most complex parts as well.
Well does it really need to be one? the straight answer is ‘No“

Machine Learning is already set to bring in a major role in resolving challenges in a customer support function.

What is Machine Learning (ML)

ML is one of the parts of artificial intelligence (AI), it is a set of techniques that provides systems or computers an ability to automatically learn without being actually programmed. It can read the data whether it may be structured or unstructured and discover insights.

How does it help in Customer Support

When it comes to Customer support ML provides a higher level of convenience to the customers and efficiency to the support staff.
CS means a lot of data, of which the major part is an unstructured one. This data that is gathered through everyday conversion and communication which contains deep insights, ML when used intelligently can be helpful in understanding the customers, their thinking, wishes and so on.

How is Machine Learning used in the CS environment?

Here are quick top picks

Understanding the Intent

Most of the time your agent does not know why is customer contacting you or where probably he is asking for help.

Machine Learning can help CS agents predict the same. Machine learning collects data about a customer’s previous browsing, geo-events, contact pattern, and other online behaviors. That allows agents to plan and prioritize the customers need. In a way your agent provides personalized services to the connecting customer, assuring elevated user experience.

Timesaving – a win-win situation

Well, what is mostly observed by the researchers, people prefer getting in touch with customer support is through chat or messaging app option. that’s where chatbot comes in the picture.

While, chatbots are something that is equally disliked by people, when used intelligently it can have a greater impact. for instance, if a chatbot can extract what exactly the customer is looking from the text types, further tag it correctly, to direct it right customer support specialist, can bring in a win-win situation for both.

it saves time for the customer, saves time for an agent, reaches the right SME and improves the overall experience

Predictive Service

With IoT, companies are now able to practically track their devices even while the customer is using it. For example, a Smart Machine connected to the internet can send back a signal to the manufacturer when a fault or unusual operation takes place. The manufacturer can get back to owning the company to inform arising issues with the required solution.

Virtual Assistance

Virtual assistance is helping customers during their journey, providing insights to customers as well as feeding the analytic program at the back-end for future reference.

ML can help a enterprises to virtually assist the customer right from buying stage to finding out resolution when he is facing any issue. ML can also help in pushing a product which customer has checked or liked based on his online behavior, it can trigger alerts or updates to the customers.

While these are only a few things listed here, there is a long list where ML can help in optimizing Customer support.
To list a few – customer data capture, classification, proactive emailing, perform root-cause analysis of repetitive instances, reduce interaction time.
Crafsol with its ML and AI services has strong experience of building custom solutions for enterprises.

Get in touch to know more how we can help you in your fasten your customer support services.

https://www.zendesk.com/blog/machine-learning-used-customer-service/
https://freshdesk.com/customer-support/machine-learning-optimizing-customer-support-blog/
https://www.forbes.com/sites/forbestechcouncil/2019/04/24/using-machine-learning-to-improve-customer-service/#298ccf985892
https://www.cognizant.com/perspectives/how-machine-learning-can-optimize-customer-support

Industry 4.0 has brought lot of change in many sectors like transportation and logistics, manufacturing, aviation, and oil and gas production. New waive that is coming up is Pharma 4.0 i.e. Implementation of Industry 4.0 in pharmaceuticals

Understanding Pharma 4.0

Similar to Industry 4.0, Pharma 4.0 refers inter-connectivity, automation, integration of AI and ML to make it possible to gather and analyze data across machines, enabling faster, more flexible, and more efficient processes to produce higher-quality goods at reduced costs.

Why to move towards pharma 4.0

Remaining competitive, ensuring to keep market place in tact is pushing pharma manufacturers to improve productivity ensure better control on monitoring. harma 4.0 technology allows for continuous, real-time monitoring of manufacturing processes so any drift away from specified parameters can be predicted and rectified before it turns into a deviation, avoiding the associated down time and loss of product.

Wining over existing control strategies

Pharma industry always had automated process control right from beginning of 90s. But this relatively old system which only alerts when already damage is done. Pharma 4.0 on other hand is proactive in nature. By using sensors and using continuous monitoring techniques, integrated with AI and analytics provides predictive analysis and a world of other business insights that are currently unavailable because they’re buried in unstructured, dispersed, incomplete data.

Role of Big Data

Big data analytics draws data from sources that have traditionally been disconnected from one another, and looks for relationships and trends that were previously undetectable. For example, data from the online inspection system described above can be combined with that from equipment maintenance and engineering systems to streamline maintenance schedules; combining production data with that from sales and dispatch systems can streamline production planning.

How will this transform to a waive

Although pharma is very precautious industry, which requires tighter control and is coupled with very strong statutory norms. However, still Governments, regulators are taking every possible step help enterprises to move towards Pharma 4.0 soon Pharma 4.0 is be waive in itself

Crafsol with its leaders, who have strong understanding of pharmaceutical industry, is ready and keen to help companies to start Pharma 4.0, get in touch with our team now.

Choosing right IoT Platform can be a challenging task, coupled with confusion due to thousands options available. Choosing the right IoT platform isn’t as easy as it seems at first. There are numerous categories of IoT systems to consider, all of which offer more or less advanced options depending on your needs.
In this blog we are trying to guide to choosing the best IoT platform for your needs.

Factors to consider

While selecting an IoT platform, one has to consider some factors, These factors will help you narrow down applicable platform, like:

1. Reason of implementing IoT
2. What will be your scability needs
3. What kind of support you need
4. Does platform that you are selecting adheres to good security parameters

Keep in mind, platform that you are selecting is going to be huge investment and you need to be extra sure before doing it. While above factors help you narrow down the selection process, There are 3 – 4 aspects you need to consider or evaluate before choosing the platform

ROI

While implementing any new tool in the business ecosystem, first point that come in mind is end result and ROI. In this aspect one needs to ensure proper road map is created, even before the platform is selected. Performance metrics are well defined and attributed to respective KPI in the implementation process

Application Industry

Probably even more important point than ROI which needs attention is ‘Application‘ Requirements will drastically change based on application industry. Just to take example medical field will require 100% reliability considering the criticality attached to it. Offshoring will require consistent operations and global connectivity. considering similar requirement for your application than selecting a platform makes real sense.

Security

One needs to take security very seriously while Implementing IoT
IoT devices have become a massive and popular target for cyber attack and during migration when data is in in-transit mode it is even more vulnerable. Unsecured IoT can lead to major risks such as financial losses, info leaks, reputation losses

Bandwidth and Cost

Well, while implementing we may not find this important, however it is very critical aspect when it comes to operational success later on. For ex. Some businesses need lot of data transmission where as some would need lot of storage. Bandwidth will also important with respect of getting desired result of the IoT. One needs to consider current requirement, growth expectancy and capability for Platform to support both.

Data Delivery

if your desired platform is just going to deliver data from a single or two sources, than its point which needs your attention. Consider a situation where your delivery source had a crash, like power outage, connectivity errors or any other case, your system will be unable to work or work in negative manner. Select a platform which offer multiple delivery methods like cloud, on-premise or edge.

Choosing an IoT platform is not easy, but taking the time to research and compare different services could be a game-changer. Crafsol has inherited capability to understand your business action as per define road map and KPI

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Industry 4.0 and allied technologies are already driving a huge change when it comes to Manufacturing. Although technologies in manufacturing are advancing at very fast pace industry 4.0 is already to set to take it to the next level.

Industry 4.0 has already benefiting manufacturers by increased visibility into operations, substantial cost savings, faster production times and the ability to provide excellent customer support.
As Competition is growing, The only way manufacturers can stay ahead of competitors and win market share is getting best out of technologies. Those companies who want excel and not just survive are on set to ripe best out Industry 4.0

In this month’s Newsletter we take a look at 5 trends that drive manufacturing in 2020

Digital Twins

Although digital Twin technologies have been around 2003, real utilization is up when IoT came into the picture. Digital twins are virtual replicas of physical devices that data scientists and IT pros can use to run simulations before actual devices are built and deployed. They are also changing how technologies such as IoT, AI and analytics are optimized.

IoT

Manufacturers are already leveraging the benefits of IoT by connecting their existing manufacturing infrastructure to internet using unique devices. In 2020 more and more companies even from SME’s will invest in IoT to leverage more informed decisions to achieve increased efficiency, improved safety, meeting compliance requirements, and product innovation.

Increased use of Cobots

Markets have welcomed Cobots positively and some research show that by 2025 investment in cobots will be 12 billion USD. Cobots create opportunities for manufacturers to improve their production lines, increasing productivity while keeping employees safe. Cobots are compact and affordable and easy to use.

AR & VR

Assistive technologies, such as augmented reality (AR) and virtual reality (VR), will continue to create mutually beneficial partnerships between man and machine that positively impact manufacturers. These technologies help businesses work more effectively while also making them more efficient. Helping in several ways like product design, production line development, driving OEE improvements, technical and engineering support, training, team collaboration, inventory management, and more.

Smart Factories

Businesses, to stay competitive, are striving hard to make their production lines more efficient, effective and utilize the resources to fullest all this to achieve better productivity.

The smart factory represents a leap forward from more traditional automation to a fully connected and flexible system—one that can use a constant stream of data from connected operations and production systems to learn and adapt to new demands.

While above is just a quick list of trends that will be seen in next year, it does show the opportunities that exist in 2020 and beyond for manufacturing companies with a forward-thinking and innovative outlook.

Want to know more about how Crafsol can help you?
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