Why JIFFY.ai is a Leader in the Zinnov Zones “Breakout Zone”

JIFFY.ai—a company that officially launched less than a year ago—is already a top-scoring disruptor in the Hyper Intelligent Automation (HIA) Breakout Zone, according to global management consulting and strategic advisory firm, Zinnov.

Zinnov regularly performs a comprehensive assessment of Hyper Intelligent Automation platforms as part of Zinnov Zones, an industry-leading annual rating of global technology service providers of cutting-edge technologies. For its 2021 report, Zinnov evaluated over 70 companies, including JIFFY.ai.

Zinnov closely examined JIFFY.ai technology for its technical prowess and scalability across multiple categories, including HIA, Use Case Discovery, Intelligent Document Processing, IT Automation, Intelligent Virtual Agent, F&A Automation, Customer Success Automation, and Talent Management Automation.

JIFFY.ai came out top-ranked in the Breakout Zone because our AI and ML-based platforms bring high-performance automation solutions to companies worldwide.

JIFFY.ai has come far in a short amount of time because we were founded to do things differently. We’re a newcomer in the marketplace, driven to disrupt the terrain of business automation with new ideas.

How HyperApps Leapfrog Other Automation Tech

The JIFFY.ai HyperApp approach leapfrogs past automation solutions such as RPA and SaaS-based point solutions for Business Process Management. (For a detailed rundown on how HyperApps excel in areas where RPA, SaaS-based point solutions, and hyperautomation don’t—read our post, From RPA to Hyperautomation to HyperApps: Level Up Automation Deployments in 2021.)

Zinnov looked at us closely and put JIFFY.ai at the top of its Breakout Zone because our unique approach allows businesses to combine the simplicity of low code with the power of intelligent automation, and the cost convenience of SaaS. Our HyperApps encapsulate all the various capabilities required to achieve successful business process automation—including designing, building, deploying, monitoring, and analyzing.

Our Invoice Processing HyperApp, for example, eliminates the roadblocks to maintaining frictionless cash flow by minimizing the risks and costs associated with inefficient processes. This HyperApp meets the complex technical and business requirements for seamless invoice processing—and then puts it in an easy-to-use, self-service application for business users, with no development team required.

Because our platform makes automation app development easier, we help businesses to avoid a common pitfall: With only technical users and data science professionals involved in automation development and deployment, there is a risk that real business requirements will get overlooked. HyperApps help to demystify the automation of complex business processes, simplifying deployment for business and technical users alike.

Most businesses silo their employees, which allows them to use and develop their specific expertise for the business’s success. This division is especially evident in software and technology areas: One employee may conceive a new idea but must rely on yet another employee to implement it due to a lack of specialized expertise.

While there’s nothing inherently wrong with this breakdown, it can lead to frustration for the idea’s creator. Creators of new ideas must spend a great deal of time and effort translating their thoughts to another group. Some things may get lost in translation, and often, this uphill climb means new concepts don’t come to fruition because the idea is too hard to enact, or too expensive, or too time-consuming.

With JIFFY.ai technology, it’s different: Ideas can be put into development more efficiently. Innovative power is easier to enact. Ideas come to fruition, and innovation moves forward.

When businesses use HyperApps developed on a single platform—rather than stitching together multiple technologies and vendors on their own—they’re able to structure their automation with reusable building blocks. These extensible and scalable building blocks allow them to stay on track through inevitable changes, such as workforce restructuring or application and process changes.

JIFFY.ai is proud to be a leader in the Zinnov Zones Breakout Zone. But we’re just getting started. Society is heading into the Great Reset, and process automation and reliance on digital channels will be a crucial ingredient to our recovery. JIFFY.ai HyperApps technologies will enable predictable wins in the short term, low effort overheads and greater democratization in the mid-term, and radical advantages in the long term. It’s time to disrupt business automation with HyperApps.

Celebrating the big and little things that make JIFFY.ai a great workplace

JIFFY.ai named Great Place to Work (mid-size comapny)

Great people make great workplaces, and great workplaces make amazing products.

December is typically a reflective time of year for most people and this year is – by far – no exception. Indeed, the pandemic and our response to it gives us further reasons to reflect, offer thanks, and look forward with hope.

This year, JIFFY.ai announced our Series A funding, received incredibly positive client reviews, and most importantly, managed to create real success stories for several clients reeling from the pandemic’s impact. 

As I write this article, we’re also very excited to be finishing off the year on such a positive note because our workplace has been voted as one of the best, most trustworthy workplaces in the Great Place to Work Survey 2020

Every year, more than 10,000 organizations from over 60 countries partner with Great Place to Work® Institute for assessment, benchmarking and planning actions to strengthen their workplace culture. Great Place to Work® Institute’s methodology is recognized as rigorous and objective and is considered as the gold standard for defining great workplaces across business, academia and government organizations.

Specifically, the metrics around the pride we take in what we do and the camaraderie we share are truly heartening. The free-flowing conversations, the honesty, the friendships we build at work – whether online or in person – these are the things that truly matter to us. While it is often hard to quantify great culture, we’re pleased to report that we’re building a true family here at JIFFY.ai.

From the days of our company’s inception, our leadership team has made building a people-driven culture a key tenet of what drives us. And in the year of the pandemic that forced us to connect remotely and often figure things out over a video call, a culture of putting people first has only gotten stronger. 

Being nimble on our virtual toes has been an unprecedented challenge, but when it comes to service, every team member has found it in themselves to rise to the occasion and do what would have once seemed impossible. These attributes are reflected in our high ranking in the Trust Index score, and we couldn’t be happier!

To many more years of changing the world of intelligent automation and remembering to do it with a smile! The JIFFY.ai team wishes you a safe and happy festive season ahead.

Gratitude for Momentum at JIFFY.ai

While 2020 has been challenging on so many fronts, I wanted to take a pause to express gratitude and excitement for some of the great successes JIFFY.ai has achieved. Our company has had a transformative year. We proudly announced our Series A funding and launched our few brand this summer. And we are aggressively working on the next spectacular chapter of our growth story.

Since our funding announcement in June, we have been investing in our growth exactly as we outlined. One of the critical investments is in our leadership team. Over the last couple of months, we have added two savvy leaders who will strengthen our ability to build trust in the marketplace and accelerate innovation for our clients across the globe.

Algernon Callier (Al) – Head of Business Development 

Al is an experienced leader, communicator, and builder across multiple business segments, with a focus on Digital Transformation, Innovation & Technology Strategy, and Brand Development. He is a founding partner of Reaction Global, a new Venture Capital organization founded by Stanford executive alumni and a named co-inventor on patents achieved for Facial Recognition technology. Al has been recognized as a winning honoree of the Digital Edge 50 Award from IDG’s CIO organization, among other towering achievements.

Mahesh Vaidya – Head of Strategic Development and Partnerships

Mahesh is a Wharton alumnus and a seasoned executive, having worked with innovative companies across sectors and investing successfully across multiple geographies and through economic cycles. He is a former General Partner of Epsilon Venture Partners, a VC and growth equity fund focused on technology opportunities in digital infrastructure across South and SE Asia. He had led investments in and served on the Board of companies such as policybazaar.com and Imanis Data. His stint with Intel Capital was successful in making it a top-quartile VC in India.

I am so pleased to have these exceptional leaders join us as our company continues to grow. The future is bright for a new era of intelligent automation, and JIFFY.ai is proud to be at the forefront.

Procurement in the Post-pandemic World

How to build efficiency using intelligent automation

When we think of Robotic Process Automation (RPA) in procurement, we know that adoption is already on the rise. Many businesses are using RPA in their value chain, and for those that aren’t yet, it is a factor of ‘when’ and not ‘if’ they will use RPA at some point in time.

In a domain as complex as procurement, RPA ensures that most tasks and processes are automated at a fraction of the cost of adding headcount/resources or deploying new teams. The benefit in addition to using a computational system is also being able to work around-the-clock (thanks to RPA), which  significantly reduces dependencies on human resources.

The true value of RPA is being able to repeat complex tasks and follow decision trees effectively. But with machine learning, cognitive processing, and natural language processing gaining traction and advancing at an accelerated pace, it is only natural to integrate this with RPA to deliver a more effective solution across the value chain.

Enter intelligent automation.

Now let’s dive deeper into why machine learning, cognitive processing, natural language processing, analytics and RPA must go hand-in-hand, and how learning algorithms coupled with RPA’s execution capabilities are the future of full automation.

What is cognitive procurement?

In the field of supply chain automation, cognitive procurement refers to the process of using automation with machine learning, analytics, and other cutting-edge technologies to help automate further, faster, and more efficiently.

Procurement as a process is characterized by large amounts of unstructured data, which may be impossible to process using traditional systems.

Apart from solving the problem of unstructured data handling, cognitive procurement also helps:

  • Transform all existing purchase and transfer order systems, sometimes entirely
  • Transform supplier onboarding and the associated processes with automation
  • Forecast prices and inventory needs, create reports with usable data and power better decision-making
  • Conduct risk assessment to prepare for known threats to the value chain

The best part? A cognitive procurement solution can also connect to external sources of data and tie these parameters into the recommendations it makes. RPA alone may not be able to do so, but when supported with the right data and learning systems, the possibilities are nearly endless in the space of procurement.

Intelligent RPA and its role in cognitive procurement

Cognitive procurement is often referred to as the final frontier in the procurement process. However, wisdom and experience show us that most of the quantum of human knowledge is actually ahead of us. In the era of information, we need a system that can handle three aspects of any complex task:

  • Research and data processing: This is where analytics come into the picture.
  • Learning from past data to make accurate predictions for the future: Machine Learning works on the principle that when an artificially intelligent system is given enough data to work with, it can make decisions that are as good as, or better than, their human counterpart.
  • Execution: Any plan is only as good as its implementation, and the sheer volume of work and number of branches in the process. Post-machine learning interventions need RPA to help in seamless execution.

As a final product, businesses with a vast and demanding procurement function can expect to achieve efficiency in analyzing their data, manage their supply risk, procure and pause material based on real-time needs, plan logistics for better efficiency and optimized costs, evaluate their suppliers based on their monthly, quarterly or annual performance across as many parameters as needed, and provide 24X7 support throughout.

Why should you implement an intelligent RPA solution in procurement?

According to a KPMG research report, “Delivering value in procurement with Robotic Process Automation,” implementing intelligent RPA can deliver over 50% savings in procurement costs, increase Return on Investment (ROI) by 5X, and reduce the number of strategic suppliers needed by nearly 50%.

How should businesses decide where and how to implement RPA in their procurement process?

Start by reviewing existing procurement processes to identify areas where the scope for automation is high. These tasks often represent repetitive actions that offer less value per extra time unit spent.

However, for an RPA system to work, the process needs to have a clear workflow and lead to non-ambiguous outcomes. Technical specifications include processes that run in relatively stable environments, and cases where manual intervention to solve for an impasse can be kept low.

Next, identify these processes based on how much business impact using automation could create, and how much effort might be necessary to implement RPA in this process. With these features in mind, the tasks can be classified into low-impact, low-effort-to-implement processes which make for good early adoption and trial cases, and high-impact, high-effort-to-implement processes which can effectively transform the business.

As a process laden with numbers and data, procurement presents the best use-case for implementing RPA in tandem with data analytics and machine learning. Companies that have already done so report unprecedented results across crucial parameters. One of the barriers for RPA implementation is worry around the cost-to-benefit ratio, which these numbers quickly disprove. The next barrier is a fear of ‘machines taking over the world’, which in cases as complex as a global supply chain – may be a good thing, as the pandemic’s disruption to this key process has shown.

The human capital that has been freed from the clutches of repetitive tasks and handling data too complex to process, can now be used in functions needing more human intervention and creativity. This leaves the machines to do what they do best – repeat every process error-free, follow the rules and use data effectively.

The Evolution of Automation: From Mundane tasks to Enhancing Human Innovation

With COVID-19 causing risks to human health and disruption to our way of life in general, especially the way we work, companies have been forced to pursue alternate ways of making progress. Many of them are striving to use intelligent automation and AI to innovate their way forward while working safely from home.

This shift does not mean that we do not value human work, or the role people play in the enterprise. Think about the agricultural revolution. In the 18th century, people transitioned from hard laboring stationary farming to original inventions that altered the farming process. The new patterns of crop rotation and livestock utilization paved the way for better crop yields and the ability to support more animals. It was an opportunity to produce more, not a judgment of the reduced value of human work.

These agricultural changes impacted societies as there was a decline in both the intensity of the work and the number of farming laborers needed. Nevertheless, the positive effects of this disruption gave life to new technologies and opportunities as people migrated to the city to work in industrial jobs. As humans, it’s in our nature to innovate and create new solutions that become paramount to organizations and the people that work within them. We believe that as intelligent automation, Artificial Intelligence, and Machine Learning continue to evolve, we have an opportunity to harness this energy of innovation in a whole new way.

Our mission is to enable organizations to cross the human machine divide that has existed since the introduction of machines and enable them to co-exist seamlessly. We aim to reduce the friction between the two in a natural, human-friendly way. Eliminating the need for expensive translation mechanisms in the form of data entry, data synchronization and mundane activities allows organizations to become extremely efficient and resilient. Enabling innovation within the enterprise using natural language instructions, we bring out the innovator in the everyday business user. By letting the machines understand human language to achieve automation we drive speed in business transformation previously not possible. This is the core of our perspective on automation.

For too long, enterprises have placed contradictory expectations on their most talented thought leaders and employees. We have expected people to be innovative while also weighing them down with administrative tasks. Research shows “task switching” disrupts flow of thought and creativity. Ultimately, we launched JIFFY.ai to reduce this phenomenon and to allow creativity to flourish and innovation to be unleashed in its most uninterrupted form. Our relentless commitment is to see a change in how organizations redesign their work, supporting them through the power that automation and AI offers to maximize strength, resiliency and scale.

Historically, automation was seen as a point solution for mundane actions. You gave it a specific function or set of functions, and it performed. Now, technology allows us to elevate and redefine the process and achieve progress through automation. This change is necessary in the ever-evolving landscape in which we live.

How Businesses Can Shift into Life Beyond COVID19

As we navigate a time different from the one we would have liked or wanted, we’re bringing to you a series of blogs, writeups, and LinkedIn resources that we call New Now. In today’s New Now blog, we talk about how businesses can begin to recover and mitigate some of the significant disruption with help from automation.

One McKinsey & Company report suggested, well before the pandemic, that over 30% of manual jobs currently could be automated by 2030. The same report also says that this change could actually bring in more jobs into the economy and that people would need to skill themselves accordingly.

But automation isn’t just a good-to-have feature anymore. For their own well-being and those of the people around them, companies and individuals alike will actively look to automate as many processes as possible, thus reducing the need for manual intervention and the close calls that might involve.

We also need to bear in mind that as all-consuming as it seems right now, the pandemic in its current state will change and subside. What this radical shift really does for businesses is it helps them see what costs they can cut, and where they can better utilize their workforces.

For the fiscal quarters that follow, many industries will continue to focus only on the costs they can cut. Three main solutions can help, and the use of technology and automation can make these processes faster and easier.

1.Analytics for real-time information: Everyone in the retail industry is feeling the heat, but the fashion and apparel industry is feeling it the most. In the business of clothing manufacturing, what is essentially a nice-to-have product in a thriving economy likely will not be purchased in current circumstances. The industry is looking at steep reductions in demand, as well as a restricted ability to predict future trends.

The only fallback, then, is real-time analysis. Fashion and apparel retailers have a tremendous opportunity here – to use real-time analytics and data to predict what they should stock up on, and how much. This could be a big welcome breath for brands that continue to struggle with too much inventory and a severely fragmented supply chain.

Another example is the airline industry. Using real-time data on infection rates and noticing which sectors open up first, they can plan their flight rosters and figure out which staff they need to bring back, and in what time frame. By linking powerful analytics with automated flight rosterscomplex, data-driven decisions that now need to be made can be made that much faster.

2.Preserving brand value and customer satisfaction: Much has been said about marketing in the current scenario. For some time now, most businesses have been riding the wave of a thriving economy. For about a year, though, we have heard predictions of a possible recession but certainly not on the scale we see now.

Companies around the globe have to rethink not just what they say, but how well they can walk the talk. Consumers of both B2B and B2C brands are navigating some very sensitive times and simply do not take kindly to an undelivered or under-delivered promise.

The next logical step for brands is ensuring that they can deliver on all the promises they make. We are heading into a territory where every individual is trying to find a new job or hold onto the one they have, and to save money while they can. Something as simple as getting a timely refund can put everyone at ease.

Serving multiple stakeholders in a shorter time window can be achieved using intelligent automation. For instance, Jiffy.ai has been able to help clients in the airline space accomplish improved turnaround times of 300% on ticket cancellations and refunds, while also significantly reducing errors.

Suggested Reading: How Jiffy.ai helped a leading airline company save 2000+person hours and process 90,000 transactions in a week

3.Preparing for the future: Companies today face a twofold challenge – delivering on an authentic customer experience and managing their cash flows to ride out the storm, and regroup for the next phase.

Generating demand is crucial for the cash registers to start ringing again. Unfortunately, demand forecasting will be a real struggle for many industries in the post-pandemic world. Consumer habits have changed, in some cases forcibly, and  wallets have tightened in a tough economy.

AI solutions can problem-solve in real-time when demand forecasting may seem like a mirage. Inventory management can be integrated with AI, helping retailers sync demand and inventory better. AI can also hook new and returning customers with a personalized experience along with identifying gaps in the offerings. This would certainly help businesses bounce back faster.

Looking ahead and planning for the future

Here are some other ways to optimize costs while also maintaining efficiency:

  • Adapt to the new virtual culture such that all non-operations staff continue to work remotely, ensuring their continued safety and well-being
  • Use automated cleaning and QC tools for spaces where people are needed physically
  • Automate complex processes using intelligent automation to help cut costs and improve efficiency

The fact remains that people need to buy things and consume services. The growth will first be visible across essential and semi-essential commodities. Several businesses will have to display tremendous resilience as the demand curve slowly rises. Investing in intelligent automation now can create a path to more efficient processes being run at lower costs, setting the tone for overcoming the current challenges and a viable recovery.