That virtual meeting that could have been an email? It should have been a Slack Huddle or a clip.
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Slack, an already integral part of the modern workforce, is redefining the norm of remote and hybrid work yet again with its new collaboration tools – huddles and clips. With the help of AWS machine learning (ML), the company has reinvented collaboration across time zones in an increasingly isolating hybrid workplace. In just a few short months, Slack has leveraged ML to innovate, improve products, and speed time to market on the cloud.
Creating a digital HQ in a hybrid world
Slack’s mission is to foster inclusivity, connection, and flexibility online—and it’s using machine learning to do it. Slack’s journey with AWS started in 2020, when the company started using the Amazon Chime SDK, AWS’s communication service that helps users chat, communicate, and conduct business calls.
If you ask Dolapo Falola, Slack’s Director of Engineering, working across time zones in distributed silos isn’t easy. “People working in a hybrid environment creates a host of productivity challenges. You’re in these back-to-back video calls and it’s just exhausting.”
For Falola, there are a lot of things we took for granted in the office, including: “the context of understanding who people are, who works together based on where they sit, and when people are free to chat. How can we find neutral, organic ways to replicate that connection without all-day video meetings?”
As offices continue to reopen in 2022, 51% of employees will be connected in a hybrid environment, with people working from home at least once a week. “That’s why company leaders have been rethinking how teams can communicate outside of video meetings,” says Falola. “We’re all about creating a digital HQ that feels human in a hybrid world.”
Seeing an opportunity to reinvent AI-driven ways to connect communities online, Slack partnered with AWS to recreate in-person collaboration touchpoints on the cloud. Powered by AWS’s powerful data and ML services, Slack engineers have developed tools that allow us to hop in and out of standups, collaborate in conference rooms, and even casually chat with coworkers face-to-face.
Modernizing workforce collaboration with machine learning
Partnering with AWS’s cloud-based ML services quickly minimized Slack’s involvement with daily IT management—leaving much needed time to focus on pushing more innovative products to market.
From AI-powered transcription services to near real-time video processing capabilities, ML is woven throughout the user experience of Slack’s flagship products. A new Slack Huddles feature facilitates lightweight audio calls that colleagues can jump in and out of, and an AI-powered speech transcription service offers fast and accurate live captioning. “Since you can screen share from anywhere in the world, you have the same shared context and can easily collaborate in real-time,” Falola says.
Slack’s newest clips feature allows users to “share their work asynchronously through voice or video recordings,” says Falola. Slack users can send short audio and video messages on the app to address a key pain point of hybrid work: too many meetings across time zones.
Clips can easily be shared in channels through DMs, and Amazon Transcribe takes voice and video data to create a transcript that’s easily searchable by keywords. For Falola, the accessibility of the new transcription service stands out. “We wanted folks to be able to follow along live if they needed to with captions, and quickly find these clips later on in the search bar with a single keyword.”
One of the AWS services that powers Slack Huddles, Amazon Transcribe, facilitates language detection capabilities, which is essential for teams working across time zones and countries. “People will set their Slack language to English, but will communicate with their coworkers in German,” says Falola. “Working with AWS allowed us to automatically detect languages more easily than ever.” Another AWS service, Amazon Chime SDK, enables Slack Huddles to minimize background noise, a crucial feature for those who take their work beyond the quiet walls of the traditional office.
These are just a few of the ways that Slack is using machine learning to reinvent digital collaboration—and each of these experiences is made possible by the company’s investment in innovative product development on the cloud.
Key takeaways for business leaders
Innovating at the speed and scale of the cloud gives you a competitive edge and allows you to serve your customers like never before. By following Slack’s lead, there are several things you can do to maximize the opportunity machine learning presents to your business.
- Evaluate time to market capabilities. Traditional IT software requires weeks or months of lead time when businesses seek to add more capacity. For Slack, AWS’s responsiveness was key to rolling out their products quickly. “We had a really tight timeline because we wanted to get this out. As we worked with AWS, we had improvements on the product that we were able to accomplish really quickly.” If your organization is developing new offerings, leverage a cloud provider that can react to new capacity in seconds—not weeks.
- Monitor performance. Be sure to pay close attention to analytics and KPIs, which in Slack’s case were response time metrics. For Falola, an agile and responsive ML platform was key to Slack’s success. “We take a good look at video send times, and how long after you hit the button are the transcripts available. By targeting the standard creator stumbling blocks like what breaks connection or increases response time, you can improve the serenity of the system on the cloud.”
- Prioritize ease of integration. Ease of integration is essential when rolling out new products. “Consider if the cloud software integrates nicely into your current technology stack,” advises Falola. “How does it fit into what’s already working?” This was especially true about Slack’s new clips offering where users can record audio and video messages within existing Slack channels to cut down meeting times. While initial prototypes included a stories-like interface, the feature has evolved to a searchable video format that better aligns with how daily users communicate on Slack.
- Keep customers at the forefront of innovation. Everything at Slack starts with truly understanding its customers’ needs and closely monitoring the changing work environment around the customers. Simply solving the problems that customers vocally report is not going to be enough if you truly want to stay ahead of the pack. What is needed is anticipating ways of making customers’ lives better in ways they haven’t thought about yet.
Slack has come a long way in reinventing digital collaboration, but it’s constantly innovating the future of work. Powered by AWS services and capabilities that support speed of innovation and agility, the company is currently developing the next generation of voice and video tools to provide even better outcomes for millions of daily users.
By taking a page from Slack’s playbook, you can reinvent collaboration at your organization by building your digital HQ—and pave your own path towards innovation.
