All the "stuff" | Conversational AI | Thought leadership
01 October 2020
Over the last several years, there’s been a lot of talk about AI chatbots, voice assistants, automation and the future of work. Many companies have been founded and hundreds of press releases have been written about robots taking over and replacing human work – you get the idea. Yet, despite that, the way we work hasn’t changed for many of us, other than we have more software than ever at our disposal, making it increasingly more challenging to do our work productively.
As we build Charli, we’re driven by both our experience and our goal of creating not just another bot or productivity tool that ends up on a growing list of software users have to interact with daily. We want to make our users’ lives easier by truly eliminating productivity killers and streamlining workflows so people can get back to doing the things that add value (like talking to customers or spending more time with family). After all, Charli is designed for busy knowledge workers, business owners, consultants and freelancers, making time-consuming tasks like expense tracking, time management and document filing easy.
We’ve developed Charli in a way that meets that goal, which – in our opinion – sets it apart from all other productivity tools. Here’s why Charli is different:
1. Traditional SaaS tools put the burden on the user – Charli reverses that
How many apps do you have on your phone? How many SaaS tools do you use for work every day? Chances are the number runs into the dozens. The problem is that each app requires an onboarding process, a learning curve and time spent integrating it with other tools. Some can get very complex.
Charli reverses the burden. In fact, Charli is designed to take care of time-consuming administrative tasks through natural language instructions. Charli learns about the user – their needs, habits and preferences – and automates the tedious behind-the-scenes processes. That means users don’t need to set up complex workflows, rules or IFTTT logic. They simply need to ask Charli to do something (“Charli, record this expense” or “Charli, save the information on this business card”) and Charli will take care of the rest.
2. Users communicate with Charli through conversational chat
Put simply: truly conversational apps are hard to create. They’re leading edge and involve complex AI technology. Yet, conversation is the most effective way for humans to communicate with machines. Conversational tools reduce the learning curve, are usually simplistic to use and let the user “fire-and-move-on” with their day.
Conversational communication is at Charli’s core. Charli enables users to interact with it quickly, efficiently and on their own terms – using a conversational back-and-forth delivered through multiple channels. While the technology was not easy to develop, it makes Charli truly user-centric.
3. Charli learns context
There are so many things that humans do and say every day that we take for granted. These simple things give us an understanding of the context and underlying reason behind actions we take, or even requests we make of people. Understanding context is not natural for machines and it’s extremely difficult even in the world of AI to create this level of contextual “smarts”. In the case of Charli, it’s important to understand what and why you’re asking for something. When interacting, are you asking for something new, or did you just answer a previous question Charli asked? Did you ask Charli to do something in relation to a meeting you are currently attending, or does this request need to be flagged as a priority?
Over the past year and a half, we’ve worked incredibly hard to design Charli to be able to learn and understand context. And, in the cases where Charli doesn’t fully understand the context, we’ve built in the smarts for Charli to clarify and learn for next time. That means Charli can quickly and easily interact conversationally with users. Plus, it means that it’s general enough to scale, but also specific enough to solve our target users’ problems.
4. Charli is seamlessly multichannel
In our day-to-day experiences, we’re constantly switching between channels – from text, to email, to Slack, and then back to text, and over to email. We expect that we’ll be able to communicate with others using the channels we want, when we want.
We put this same expectation on Charli and, as a result, built it to be multichannel. That means users can communicate with Charli in the most natural way possible and with the tools they use to do their work. They can send Charli an email asking to file an invoice, then switch to text to ask Charli to schedule a meeting, and then head to the app to scan a business card for Charli to put in their CRM and to create a follow-up reminder. We use multiple methods of communication in our everyday lives and we want to make sure Charli does the same.
5. “Teach don’t code” means Charli is inherently built to scale
Most apps now are low code, but rarely are they no code. Many require some level of technical understanding to set up, customize and automate. Charli changes this by being no code – really and truly. That means rather than having to mess around in the backend or set up IFTTT rules, users simply send Charli natural language instructions and let it take care of the rest. If Charli needs to confirm an instruction or ask a question, it will send the user a message in plain language. Charli learns through teaching, interaction and experience – not through code.
Curious to learn more? Reach out to me for more information, or visit http://resources.charli.ai/ to join our beta program waitlist.