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Pypestream Executive Interview

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Sheri Greenhaus, Managing Partner of CrmXchange, had a chance to discuss Pypestream with Richard Smullen, CEO Pypestream, Inc.  

Pypestream, a revolutionary platform, aims to transform customer-business interactions by eliminating the need for middlemen. Through automation, visualization tools, and AI, Pypestream offers a self-service model that allows users to perform tasks seamlessly. With real-time language translation, proactive troubleshooting, and access to customer records, Pypestream enhances the customer experience. The platform's unique Pype interface combines app-like functionalities with chat, setting it apart from other providers. Pypestream's analytics-driven approach ensures continuous improvement and enables organizations to automate various aspects of their operations. With partnerships and successful implementations, Pypestream has proven its capabilities in major enterprises.

Could you provide us with an overview of Pypestream?

Absolutely. We've been in operation for a few years now, with our headquarters based in New York. Our main objective from the beginning was to eliminate the need for a middleman in customer-business interactions. We wanted to revolutionize the way these interactions take place.

The idea came to me around nine years ago, during the time when Uber was gaining significant traction. At that time, in order to book a car, you would have to make a phone call to speak with someone who would then contact the driver. They would send you a form to fill out via email, asking for your credit card details. You would then receive a call back with the driver's details and the estimated arrival time. Travis Kalanick and his team at Uber figured out how to automate this process and make it entirely digital.

Considering the advancements in technology, it's highly likely that all businesses will eventually adopt self-service models and interact with customers similarly to how Uber does. However, for this vision to become a reality, three key elements needed to come together and work seamlessly.

Firstly, automation had to reach a level of excellence. It's now clear that most tasks can be automated without requiring human intervention. If processes aren't automated, businesses are essentially wasting money, and human resources are better utilized elsewhere.

The second element was the advancement of visualization tools and mobility. Users needed the ability to engage with systems and platforms from anywhere using their mobile devices. Swiping, typing, and pin-dropping functionalities had to be highly intuitive and efficient.

Lastly, artificial intelligence (AI) needed to be capable of understanding human behavior better than call center agents. This was the missing piece of the puzzle. If AI could replace agents and interact with humans while taking context into account and analyzing an unlimited amount of data points, it would significantly enhance the customer experience while reducing the need for human agents.

Until about six months ago, AI had not reached the necessary level of accuracy and understanding. The chatbot experience often resulted in confusion, leading to escalation to human agents. However, we anticipated the development of large language models and generative AI tools about 18 months ago, preparing our platform for their integration. This allowed us to deliver what we call the "call center of the future," where users can perform tasks and interact digitally without the need for extensive training on software tools.

We have been aggressively rolling out this approach and have already partnered with major companies such as MAX, Sling TV, HBO, T-Mobile, and the Department of Veterans Affairs. Procter & Gamble is using our platform across eight of their brands, with global implementation on the rise.

Our proposition is worth taking seriously because it represents the next generation beyond the failed chatbot era. Users can chat within the interface, swipe, pin-drop, and our system can proactively anticipate their needs. This level of seamless interaction is unmatched.

What sets Pypestream apart from other providers who claim to offer similar capabilities?

The main distinction is that we can prove our capabilities by showing real solutions in action. You can visit companies like MAX or Clear at the airport, and you will be using Pypestream. When you ask other vendors to demonstrate a real solution, most of them disappear or show you a chat window with a human on the other end. We can actually let you experience our platform and run through various use cases, which immediately highlights the difference and effectiveness of our approach. We believe in showing rather than just telling. Additionally, we can back our claims with partnerships and case studies.

We wouldn't be able to talk about our success with partners and clients if it couldn't be validated. With thousands of chatbot vendors in the market, our goal was to create an experience that is unlike any other. We have developed something called the Pype, which combines the functionalities of an app and a chat interface into one hybrid experience. It's part of our unique pattern, and when users see it, they realize it's a lot more functional and innovative. We often hear that they have never seen anything quite like it.

It sounds like Pypestream has the potential to automate various aspects of businesses. Could you elaborate on how automation spreads throughout an organization once the initial problem is sorted out?

Absolutely. Once we address the initial problem, our automation capabilities can be extended to various other areas of the business. We can automate nearly anything within an organization. This is one of the remarkable aspects of Pypestream. Once we're integrated, we continuously improve the business through automation, extending its benefits beyond the initial use case.

Can Pypestream's tools detect someone's emotions in a panic situation?

Detecting emotions would require access to data that indicates a panic situation. The key question is whether there is good access to that data in the given moment. Pypestream analyzes real-time data, such as location, history, and text construction, to infer the emotions of a user. Although it's not yet 100% accurate, it's well on its way to becoming highly reliable.

If I provide my identity, can Pypestream retrieve my record from the customer relationship management (CRM) system and understand why I may be contacting them?

Retrieving customer records from the CRM system is a fundamental capability of Pypestream. We examine historical interactions, remedies provided, and re-contact history. We analyze whether the customer's inquiry is related to a previous remedy and determine if the resolution was successful. Our goal is to minimize frustration and provide proactive solutions. Moreover, in real-time, we can identify issues like buffering for a streaming provider. Before the customer even contacts the provider, they receive a text message from Sling TV notifying them of the buffering issue and offering troubleshooting options. This proactive approach adds significant value for our customers.

It seems like Pypestream's capabilities are vast. Where should organizations start when considering Pypestream?

This is a common challenge for executives right now. We typically begin by analyzing the contact center and understanding the volume and the use cases driving that volume. We examine the speed at which we can connect the use cases to backend systems. We prioritize the automation of use cases that can be done quickly and will immediately impact business operations by saving costs and reducing the need for human agents. We analyze which use cases can be automated and how fast we can develop them. Once we identify the top use cases, we build them out and put them into action. Our process involves a deep dive into the analysis, which we offer to our customers free of charge. We want to ensure that our automation delivers real impact and aligns with the goals of our customers.

Is Pypestream available in multiple languages, or is it primarily in English?

Pypestream is deeply integrated with AWS, which provides us with essential core tools. One of those tools is Amazon Translate. Through our integration with Amazon, including services like Alexa and Amazon Prime, we have access to an extraordinary translation service within AWS. At the moment, we support approximately 100 languages at a high level of proficiency.

When someone is texting, does Pypestream translate the messages in real-time and store them in a database?

Yes, Pypestream detects the language of the user's browser and translates messages in real-time accordingly. Whether it's proactive outreach or responses within the platform, Pypestream leverages real-time translation capabilities to provide a seamless multilingual experience.

The capabilities of Pypestream seem limitless. Is there anything else you believe our audience should know about your platform?

Analytics play a crucial role in Pypestream. Our platform is built on a robust analytics layer, which means that every user movement within our micro apps is analyzed in real-time. We have an extensive library of micro apps that we can customize for our customers, and we also build new ones as needed. Once the platform is up and running, continuous tweaking, fixing, updating, and refining occur to optimize the user experience. We offer complete visibility into the effectiveness of the platform, leaving no room for guesswork.

I want to emphasize that we only charge our customers if we successfully prevent the call from reaching a human agent. Our partnership model is performance-based, and our pricing reflects a small percentage of the cost of a traditional call center interaction. The rest, about 90%, becomes pure profit for our customers. We work closely with each company to define specific goals, and the impact on their business can be substantial, leading to improved shareholder perception and even influencing share prices.