Product Engineering

Unlock the power of AI to net visual bugs

Accelerate visual testing using AI and achieve better accuracy at lower operational costs

According to Browser stack, 67% of businesses conduct visual testing manually to detect and fix visual bugs.

However, manual testing to detect visual bugs has posed several challenges that affect productivity, such as:

  • Testing multiple aspects – Every single component in a UI requires thorough testing
  • Frequent UI changes lead to a redundant and prolonged testing process
  • Inconsistency in UI across platforms – Different UIs across different digital channels, such as browsers (both mobile and web versions), mobile apps, and operating systems (Android & IOS), make it difficult to conduct thorough testing

To overcome the aforementioned challenges, service providers must use AI to automate the process of visual testing to detect bugs quickly and efficiently, improve accuracy and reduce operational costs.


Fig: AI-driven test automation for visual testing

Implementing AI-driven test automation can accelerate testing with better accuracy, enhanced test coverage, and lower operational costs.

Product Engineering

Create product differentiation and supercharge revenue growth

The key ingredients connected platforms and software products (CPS) firms must consider to stay ahead of the curve

Explore new opportunities enabled by emerging Cloud, Data, Artificial Intelligence, and Network technologies!

In an industry driven by constant change and innovations, connected platforms and software product (CPS) firms have created tremendous value. Its innovations fuel the digital world, connecting people, things, devices, and networks.

CPS firms need to overcome 4 significant challenges to maintain their competitive edge:

  • Improving the innovation speed – bringing innovative and differentiated products and features faster to the market. 
  • Analyzing large amounts of siloed data sets to understand customer preferences and behaviors, develop customer-centric products, and continually improve customer experience.
  • Increasing the efficiency of product development and engineering processes while keeping costs under control.
  • Gaining access to new markets, extending the reach, and accelerating revenue.

From this industry viewpoint, we share the key ingredients that can help Connected Platforms and Software (CPS) product firms to overcome the above challenges and create product differentiation.

Products on the cloud can scale much faster, reach global customers, and deliver a significantly higher quality of service at lower costs

Product Engineering

Move to technology-driven smart policing

Leverage predictive analytics to reduce crimes and burglaries by 30%

Today, the crime rates in most parts of the world are high, despite taking necessary measures. Reports by FBI reveals, “3.9% increase in the estimated number of violent crimes and a 2.6% decrease in the estimated number of property crimes when compared to 2014.” Due to this, the police forces globally are under tremendous pressure to leverage technologies such as predictive analytics, to draw insights from the vast complex data for fighting the crimes. It not only helps in preventing robberies and burglaries but also aids in better utilization of the limited police resources.

Fig. Predicting crime by applying analytics on data feeds from various sources

As per studies conducted by the University of California, crime in any area follows the same pattern as the earthquake aftershocks. It is difficult to predict an earthquake, but once it happens, the following ones are quite easy to predict. The same is applicable when it comes to crimes in any geographical area. Combinational analysis of the past crime data and other influencing parameters help in predicting the location, time, and category of crime.

With the increasing crime rates, globally the police forces are under tremendous pressure to leverage technologies such as predictive analytics to draw insights from the vast complex data for fighting crimes.

Product Engineering

Deliver high-quality entertainment services at high speed and with flawless quality

Automate the end-to-end compatibility testing and rollout steps to deliver a seamless viewing experience across multiple digital platforms and form factors

A series of technological advancements has completely changed the way people consume video content. Compared to earlier days, when a television set was the primary source to consume videos, today’s consumers have many other options – smart TV, streaming box/stick, gaming consoles, DVR, set-top box, tablet, computer, mobile, etc. A recent ComScore OTT state report clearly shows the growing penetration of different digital devices among U.S households.

To deliver a seamless viewing experience, service providers need to ensure video compatibility across a broad range of device types, operating systems, browsers, and network types.

The end-users now have the flexibility to watch their preferred videos on any digital platform of their choice without being much concerned about the supporting operating systems, browsers, and network connectivity.

But if we look from the lens of service providers, delivering video service faster and with high quality has become much more complicated. It requires them to ensure feature compatibility with a broad range of device types with different operating systems, browsers, and network connectivity. This requires a humongous amount of testing in the background. And as digital-savvy users expect feature updates at lightning speed, service providers cannot afford to spend much time testing and rolling out services.

This mandates service providers to technically upgrade their way of working, the testing process, and existing release platforms.

Product Engineering

Use AI to Bolster your Network Capacity Planning decisions

The Content Delivery Network (CDN) market is poised to explode as content consumption gains more momentum. This calls for an efficiency-focused approach towards CDN capacity planning.

As per a Cisco report, the annual global IP traffic has already crossed the zettabyte (ZB) threshold. To cope with the increased content consumption by users, more supply chains should be established along with a reliable and scalable infrastructure. This puts a lot more pressure on the Content Delivery Networks (CDNs), which forms a well-established global backbone for content delivery.

For service providers, it becomes vital to take an efficiency-focused approach towards CDN capacity planning. This means satisfying the future capacity requirements without increasing the total cost of ownership.

The legacy manual way of capacity planning uses basic statistical tools to collect data and set a static threshold on capacity requirements. Such manual planning typically does not analyze the network in a holistic manner and produces a final proposal with a “one rule fits all” approach. However, this approach is inefficient in today’s scenario where consumer behavior changes very dynamically. Manual planning is also prone to human error, so the outcome might deviate from time to time, wasting a substantial number of resources and time. The service providers often run out of capacity due to increased data consumption and changes in the consumption patterns, which are not identified correctly during capacity planning.

To satisfy the customer demands in a timely fashion, it is necessary to have a modern capacity planning strategy.

Network planners need to confront these challenges before it impacts the customer experience. Leveraging Artificial Intelligence (AI) can significantly improve network capacity planning, thereby improving the end-user experience and reducing the total cost of ownership.

Product Engineering

Speed-up entertainment services rollout

Implementing an effective CI/CD setup to deliver high-value media services with agility

Online video consumption has been increasing tremendously with a rapid change in consumer expectations to have a seamless viewing experience across various digital devices. To capture this growing demand, it is critical for DSPs to deliver fast-track rollout of NextGen media services.

However, DSPs are facing major challenges in orchestrating and managing rollouts of innovative features, converged live TV and curated media services within a short span of time. This complexity further increases when DSPs need to cater to multiple geographies.

Unlike OTT players, DSPs have been limited with extremely long development and rollout timelines for new services and offerings. Primarily because of the enormous amount of vendor-specific hardware and software applications that do not support rapid changes.

An effective continuous integration and continuous deployment (CI/CD) approach enable DSPs to achieve same innovative services and delivery agility that OTT providers are offering to stay competitive. This insight talks about different enablers that will help DSPs in adopting an effective CI/CD setup for faster rollout of NextGen media services. Implementing these enablers would further ensure high-quality, right first time and consistent right delivery of media services across multiple geographies and drastically cut down on the product’s time to market.

Implementing CI/CD architecture accelerates media service rollouts by 60% providing enhanced content and features to the customers.