A few weeks ago I was genuinely thunderstruck. My co-editor at P&G Signal (thanks Stan!) introduced me to a new company – one that promised to give consumers control over their personal data in new and innovative ways. At first I was skeptical – I’d seen quite a few “personal data lockers” come and go over the past decade or so. I even invested in one way back in 2012. Alas, that didn’t work out.
For as long as I can remember, I’ve been writing – over and over and over – about how the Internet’s central problem is the lack of leverage that consumers have over the data they co-create with the hundreds of apps, sites, and platforms they use. But data lockers never got any traction – most were confusing to install and run, and they all suffered from a lack of tangible consumer benefits. Sure, having a copy of all my personal data sounds great, but in the end, what can it do for me? Up till now, the answer was not much.
It was with all those caveats – and honestly pretty low expectations – that I took a meeting with Sumit Agarwal and his team at Palo Alto, CA-based Gather, an early stage startup still in its first year of operation. Fifteen minutes later I was hooked – here was a company that was addressing the “what can my data do for me” problem by building out a generative AI agent that just might spark the kind of personal data revolution I’ve been writing about for more than a decade. And this was no fly-by-night startup – the company’s founders, team, and investors are all deeply experienced in AI, Internet security, scaled engineering, product design, marketing, and much more.
Before diving in, a caveat: Gather is still at a very early stage, as is the overheated AI ecosystem in which Gather’s products will eventually live. Agarwal told me he’s not even sure if his company will be called Gather by the time its first product becomes available later this year. In addition, the company faces fearsome obstacles to success – including entrenched platform players like Google, Amazon, and Apple, whose business interests do not align with the concept of a newly empowered consumer base. While I usually like to write about companies and products that readers can use immediately, I’m breaking that rule for Gather. No matter the business you’re in, it will pay to understand the shift in consumer behavior that tools like Gather could unlock. And as I said before, this company is the first I’ve seen that has assembled the team, vision, and execution chops to pull it off.
Timing Is Everything
With startups, timing is everything. There’s only so much you can control – what you make, how you spend your investors’ money, the people you hire. But nearly everything else is driven by externalities you must navigate. Is the technology ecosystem capable of supporting your vision, or is your product ahead of its time? Netflix, for instance, had to wait until broadband was pervasive enough to launch its streaming service. Are consumers ready for your idea, or is it out of sync with their expectations? Uber and Airbnb faced this challenge in their early years. Will huge competitors copy your idea, or change their policies and make it impossible for you to thrive? Ask Yelp how it feels about Google’s review summaries, or ask Epic Games about Apple’s 30 percent tax in the app store.
Gather faces all these timing challenges and more, but the company does have one huge tailwind: AI is hot, and investors can’t get enough of it. This past month alone, VCs poured more than $11 billion into AI startups, up 86 percent from a year ago. But while AI funding tipped into a frenzy with OpenAI’s launch of ChatGPT last November, Gather managed to raise an impressive seed round five months earlier, in June of 2022. Agarwal and several of his co-founders were already seasoned operators with a billion-dollar exit in the Internet security sector (Shape Security, sold to F5 three years ago). Gather’s $9 million round was led by general partners at respected firms Bain, Floodgate, and Wing Ventures, with participation from experienced Valley angels like Gokul Rajaram – an investor and director at The Trade Desk, Pinterest, and Coinbase, among many others – and Vivek Sharma, the co-founder and CEO of Movable Ink.
“I’ve known Sumit for about 15 years,” said Gaurav Garg, founder of Wing Venture Capital and early investor and board member at Gather. “He has a deep background in consumer and enterprise products used by hundreds of millions of people, as well as exposure to government policy, across technology areas including security, identity, privacy, and e-commerce.” Garg also noted that Sumit has the attributes of a great founder – drive, persuasiveness, perspective, and a learning mindset – crucial when you’re looking to reimagine something as big as how consumers will interact with AI and the Internet.
“The team are all exceptional founders,” added Bain Capital Venture’s Ajay Agarwal, who’s known and worked with several of the Gather team over the past 25 years. He added a key observation: The tech ecosystem is at an inflection point – mainstream devices like phones and computers can now power distributed platforms like Gather, large language models have evolved to conversational levels, and there’s even just the right amount of government regulation to create conditions for a sea change in how consumers control their data. We’ll get into all of that, but first, the product.
First, Gather The Data
Gather acts as your trusted and secure agent, logging into various data-hoarding services like Google (think Maps, Search, Mail, Android Play, YouTube), Amazon, Uber, Strava, and many more. At your direction, Gather then downloads copies of your data from each service to your local device – a right codified into law by the 2018 European General Data Protection Regulation (GDPR) and adopted, in broad strokes, by several states in the US – California chief among them. Till Gather came along, no one had built a service that automates what is otherwise a tedious and frankly pretty pointless process – almost no one actually downloads copies of their data from online services, because, as we’ve already established, there was simply no use case for doing so.
But once you have a critical mass of that data, and it’s organized in a way where questions can be asked of it, a whole new world opens up. Gather added me to a pre-release version of its platform, and it was magical to watch the service engage with Amazon, Uber, Google, Twitter, Venmo, Strava, and many others. Within minutes, copies of my data were presented and organized in my Gather app. And that’s when things start to get interesting. As Gather marketing lead Niki Aggarwal pointed out, now that I had the data in my control, I could start to ask it questions. What kind of bias, if any, might be evident in the stories I was reading from Google News? How much did I spend on Amazon each month, and would I have saved money if I had bought those same items at Walmart? Was there an optimal time of day to get a personal best when riding on Strava?
Of course, this is only the tip of the proverbial iceberg when it comes to what’s possible with data sets like these. Sure, it’s cool to have a copy on my own device, in my control. But the real fun will start when you add a personalized AI agent capable of instantaneously answering those initial questions, as well as conjuring up ones you’ve not thought to ask. Even more exciting, imagine that same agent as a trusted confidant, leveraging your data as it interacts with the rest of the online world. Now that’s a consumer benefit – a personal agent that knows my preferences and can, say, plan a complicated business trip, or negotiate for the best price for an item I want to buy online. The time savings alone make the idea compelling. I’ve come to call such agents “genies” – because they work only for you, and they can produce all kinds of magic (and as a bonus, they aren’t limited to three wishes!).
Where Genies Play
Gather hasn’t released its “genie” yet, but it’s working on it. Codenamed “Sidekick,” the product will consist of several elements. First is your personal datastore, which lives on your own device and remains under your control at all times. Second is the Sidekick agent, which Agarwal describes as “an AI product that proactively and intuitively helps you.” He continues: “We are trying to get away from ‘blinking cursor in an empty text box’ and get to ‘intelligent character that thinks about your needs, intuits your desires, [and] acts on your behalf.'” Gather’s third element is a platform that manages how outside organizations interact and create value with your data.
Agarwal offers an example of how Sidekick might work: “You visit Amazon Music, and there’s an offer for six months of free service if you upload your Spotify play history. Your Gather Sidekick allows you to upload with a single click. Your data moves to an external service (Amazon Music) and you get value. You can think of the same example in many contexts – food/dieting, fitness, other entertainment apps, medical apps, etc. The concept is simply that a specific – and sometimes complex – “slice” of your data needs to move somewhere in order for you to receive some value (economic or otherwise).” (This example calls to mind my 2018 piece, in which I imagined how Walmart might compete with Amazon online by leveraging a consumer’s Amazon purchase history.)
Agarwal’s second example envisions an instance where you don’t necessarily trust the service that wants to leverage your data. Imagine, for example, that a third-party developer has created “the ultimate music recommendation app.” It sounds appealing, but you’re wary of uploading your Spotify or Apple Music data to a service that has yet to prove it’s trustworthy. In this case, Gather becomes a secure platform that runs on your device. “With Gather,” Agarwal explains, “that recommendation app can run locally in your environment. This is a win for you because you have no data sharing concerns, so you can comfortably let the app engage with your data to get the very best recommendations. The Gather platform keeps your data local but publishes the schema so developers know how to interact with the platform – without seeing your data.”
I think of Gather’s platform as like Apple’s app store or Google Play, but with one critical difference: The power to decide who gets access to the platform resides not with a massive corporation, but with you, the consumer. This seemingly small distinction is in fact a massive shift in power, agency, and value from the centralized model of Web 2 toward a decentralized vision more aligned with the original architecture of the Internet – pushing intelligence and control to the edge of the network.
The Iceberg Metaphor
Over the course of many emails, calls and Zoom meetings with Agarwal and his co-founders Sudhir Kandula and Mengmeng Chen, both colleagues with Agarwal at Shape Security, we touched on topics as varied as security and privacy, Internet history, and information theory. Gather emerged from its founders’ dissatisfaction with what author and Internet OG Cory Doctorow calls the Internet’s “ensh*ttification.” As large companies have consolidated control of our online lives, our experiences have begun to degrade. This is why so many technology observers are excited by Microsoft’s integration of ChatGPT into its Bing search service. Google search is so clogged up with low-quality results and ads, Microsoft’s “conversational search” promises a better, clutter-free user experience. But Agarwal sees many more use cases beyond search – and to understand how it might work, it’s worth a dive into what he calls “the iceberg metaphor,” a visualization of how humans might best communicate with infinitely capable AIs.
As we know, 90 percent of an iceberg is underwater. At its tip – the 10 percent – is human interaction with AI – the prompts we type, or soon, the words we utter. That interaction is limited by our ability to speak or type – which compared to machines, is very low bandwidth, about 50 words per minute. But human speech is richly nuanced, and informed by executive function – this is where decision making occurs.
It’s in the 90 percent underwater where AI can excel. Machines can speak to other machines at mind bending speeds – one AI genie speaking to countless others, negotiating information demands, price comparisons, complex, multi-step transactions like scheduling a meeting or building a travel itinerary. “Underneath the water the GPT is listening, watching, reading, and comprehending on your behalf,” Agarwal says. “It’s unconstrained by our puny 50 word-per-minute input.”
The key to the iceberg model is that ten percent – no substantive decisions are taken, no meaningful action, until the human in charge says so. Good genies will surface questions and clarifications at the speed of human language, then dive back below the surface to negotiate next steps in the underwater world of machine-to-machine communication.
Will Tech Giants Let It Happen? The Plaid Example.
For Gather to scale, it needs hundreds of thousands, if not millions, of people to engage with its platform. Agarwal is reserved when pressed on the use cases that might drive that engagement, but it’s not hard to imagine any number of “killer apps” that could get the startup to its first million users. But as challenging as scaling an initial user base may be, Gather faces an even larger threat: The data use policies of big platforms like Amazon and Google. Regulations like GDPR guarantee a user’s right to access and download their own data, but most big tech platforms have “terms of service” policies that prohibit automated retrieval of user data. These policies are ostensibly in place to counter malicious actors who are spoofing real user’s accounts, but they could also be employed to stymie Gather’s work on behalf of its user base.
This is where the Gather team’s experience at Shape Security comes into play. Shape’s core business was to help large financial institutions fight automated attacks against the banking industry’s consumer portals. Agarwal and his colleagues spent years understanding and perfecting defenses against sophisticated “attack vectors” in a sector where the stakes are high – people do not like to lose their money. For much of their time at Shape, one of their most vexing opponents was a company called Plaid – then a startup, but now a $15 billion industry leader that offers consumers a platform to retrieve, manage, and gain value from their personal financial data across a majority of banking institutions online. If you’ve ever used RobinHood, or moved money from your bank to Venmo, you’ve used Plaid. Like Gather, Plaid works as an agent on behalf of its individual customers. For years big banks fought against the idea of their own consumers taking control of their data, and Shape Security was one of their most potent weapons. While Shape was able to win at the tactical level – stopping Plaid from accessing data on behalf of clients like Capital One – Plaid managed to win the overall war, because its ardent users pressured their financial institutions (and regulators) to allow them access to their own data.
The Plaid example can’t but be front and center in the Gather team’s minds as they embark on the next phase of their journey. Agarwal, a former Network Warfare Officer with the United States Air Force, often uses military terminology when describing the state of consumer data rights. “In the military there’s a term called preparing the battlefield – months and months of preparatory work before you commit,” Agarwal says. “As soon as we finished up at our acquirer, we started brainstorming about how to protect more users in more profound ways.” The idea for Gather, he said, hit him “like a lightning bolt” and work on Gather began almost immediately afterward.
What’s In It For Brands?
Agarwal is committed to making Gather free for its users, a tactic that will certainly help the company garner its initial user base. Once a critical mass of consumers are on the platform, he envisions charging enterprises API fees when they reach out to consumers and request consumer data, with the consumer’s permission, of course. As Agarwal imagines it, brands might want to offer promotions much like the example he mentioned above – where Amazon Music offers six months free in exchange for a user’s Spotify data. Walmart might do the same in a bid to lure away Amazon customers. But the examples can get even more granular – McDonald’s might offer otherwise hard to reach consumers in a certain zip code free delivery via DoorDash, or a company like P&G might pilot a Pampers subscription service based on a user’s past purchase data. The possibilities are infinite – if Gather gets to scale.
Should he succeed, Agarwal and team are hoping to jumpstart an entirely new value equation for consumer-driven data, one that just might force all businesses to abandon today’s dominant model of hoarding data and steering consumers into a limited set of choices. “Today, our data is so siloed, but it’s so valuable,” Agarwal told me. “We can change the power balance from the platform back to the user.”
Long time readers know how I feel about Agarwal’s sentiment – I believe unleashing the consumer data economy could drive a huge increase in economic innovation and flourishing. I suspect this won’t be the last time I write about Gather, and certainly not the last time I write about the sea change it hopes to spark. In the meantime, Agarwal will be presenting his vision for Gather at P&G Signal this coming July 12th. You can find a registration link for the event here.