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What’s the next big thing in enterprise automation? If you ask the tech giants, it’s agents — driven by generative AI.
There’s no universally accepted definition of agent, but these days the term is used to describe generative AI-powered tools that can perform complex tasks through human-like interactions across software and web platforms.
For example, an agent could create an itinerary by filling in a customer’s info on airlines’ and hotel chains’ websites. Or an agent could order the least expensive ride-hailing service to a location by automatically comparing prices across apps.
Vendors sense opportunity. ChatGPT maker OpenAI is reportedly deep into developing AI agent systems. And Google demoed a slew of agent-like products at its annual Cloud Next conference in early April.
“Companies should start preparing for wide-scale adoption of autonomous agents today,” analysts at Boston Consulting Group wrote recently in a report — citing experts who estimate that autonomous agents will go mainstream in three to five years.
So where does that leave RPA?
Robotic process automation (RPA) came into vogue over a decade ago as enterprises turned to the tech to bolster their digital transformation efforts while reducing costs. Like an agent, RPA drives workflow automation. But it’s a much more rigid form, based on “if-then” preset rules for processes that can be broken down into strictly defined, discretized steps.
“RPA can mimic human actions, such as clicking, typing or copying and pasting, to perform tasks faster and more accurately than humans,” Saikat Ray, VP analyst at Gartner, explained to TechCrunch in an interview. “However, RPA bots have limitations when it comes to handling complex, creative or dynamic tasks that require natural language processing or reasoning skills.”
This rigidity makes RPA expensive to build — and considerably limits its applicability.
A 2022 survey from Robocorp, an RPA vendor, finds that of the organizations that say they’ve adopted RPA, 69% experience broken automation workflows at least once a week — many of which take hours to fix. Entire businesses have been made out of helping enterprises manage their RPA installations and prevent them from breaking.
RPA vendors aren’t naive. They’re well aware of the challenges — and believe that generative AI could solve many of them without hastening their platforms’ demise. In RPA vendors’ minds, RPA and generative AI-powered agents can peacefully co-exist — and perhaps one day even grow to complement each other.
UiPath, one of the larger players in the RPA market with an estimated 10,000+ customers, including Uber, Xerox and CrowdStrike, recently announced new generative AI features focused on document and message processing, as well as taking automated actions to deliver what UiPath CEO Bob Enslin calls “one-click digital transformation.”
“These features provide customers generative AI models that are trained for their specific tasks,” Enslin told TechCrunch. “Our generative AI powers workloads such as text completion for emails, categorization, image detection, language translation, the ability to filter out personally identifiable information [and] quickly answering any people-topic-related questions based off of knowledge from internal data.”
One of UiPath’s more recent explorations in the generative AI domain is Clipboard AI, which combines UiPath’s platform with third-party models from OpenAI, Google and others to — as Enslin puts it — “bring the power of automation to anyone that has to copy/paste.” Clipboard AI lets users highlight data from a form, and — leveraging generative AI to figure out the right places for the copied data to go — point it to another form, app, spreadsheet or database.
Image Credits: UiPath
“UiPath sees the need to bring action and AI together; this is where value is created,” Enslin said. “We believe the best performance will come from those that combine generative AI and human judgment — what we call human-in-the-loop — across end-to-end processes.”
Automation Anywhere, UiPath’s main rival, is also attempting to fold generative AI into its RPA technologies.
Last year, Automation Anywhere launched generative AI-powered tools to create workflows from natural language, summarize content, extract data from documents and — perhaps most significantly — adapt to changes in apps that would normally cause an RPA automation to fail.
“[Our generative AI models are] developed on top of [open] large language models and trained with anonymized metadata from more than 150 million automation processes across thousands of enterprise applications,” Peter White, SVP of enterprise AI and automation at Automation Anywhere, told TechCrunch. “We continue to build custom machine learning models for specific tasks within our platform and are also now building customized models on top of foundational generative AI models using our automation datasets.”
Ray notes it’s important to be cognizant of generative AI’s limitations — namely biases and hallucinations — as it powers a growing number of RPA capabilities. But, risks aside, he believes generative AI stands to add value to RPA by transforming the way these platforms work and “creating new possibilities for automation.”
“Generative AI is a powerful technology that can enhance the capabilities of RPA platforms enabling them to understand and generate natural language, automate content creation, improve decision-making and even generate code,” Ray said. “By integrating generative AI models, RPA platforms can offer more value to their customers, increase their productivity and efficiency and expand their use cases and applications.”
Craig Le Clair, principal analyst at Forrester, sees RPA platforms as being ripe for expansion to support autonomous agents and generative AI as their use cases grow. In fact, he anticipates RPA platforms morphing into all-around toolsets for automation — toolsets that help deploy RPA in addition to related generative AI technologies.
“RPA platforms have the architecture to manage thousands of task automations and this bodes well for central management of AI agents,” he said. “Thousands of companies are well established with RPA platforms and will be open to using them for generative AI-infused agents. RPA has grown in part thanks to its ability to integrate easily with existing work patterns, through UI integration, and this will remain valuable for more intelligent agents going forward.”
UiPath is already beginning to take steps in this direction with a new capability, Context Grounding, that entered preview earlier in the month. As Enslin explained it to me, Context Grounding is designed to improve the accuracy of generative AI models — both first- and third-party — by converting business data those models might draw on into an “optimized” format that’s easier to index and search.
“Context Grounding extracts information from company-specific datasets, like a knowledge base or internal policies and procedures, to create more accurate and insightful responses,” Enslin said.
If there’s anything holding RPA vendors back, it’s the ever-present temptation to lock customers in, Le Clair said. He stressed the need for platforms to “remain agnostic” and offer tools that can be configured to work with a range of current — and future — enterprise systems and workflows.
To that, Enslin pledged that UiPath will remain “open, flexible and responsible.”
“The future of AI will require a combination of specialized AI with generative AI,” he continued. “We want customers to be able to confidently use all kinds of AI.”
White didn’t commit to neutrality exactly. But he emphasized that Automation Anywhere’s roadmap is being heavily shaped by customer feedback.
“What we hear from every customer, across every industry, is that their ability to incorporate automation in many more use cases has increased exponentially with generative AI,” he said. “With generative AI infused into intelligent automation technologies like RPA, we see the potential for organizations to reduce operating costs and increase productivity. Companies who fail to adopt these technologies will struggle to compete against others who embrace generative AI and automation.”
A new social media app called Indaband lets musicians and vocalists collaborate with others and make music with people all over the world. The app is designed to make people who usually play an instrument on their own feel like they’re part of a worldwide band (get it, Indaband?). Record a video of yourself playing an instrument and others can stitch in videos of themselves playing their own instruments on top of your original recording.
All you need to get started on Indaband is a pair of headphones and a smartphone to record yourself. You can choose to upload prerecorded files as new tracks or open the app’s recording booth to record your tracks on top of someone else’s. You can record and mix unlimited video tracks in different sessions using the app’s multitrack video studio and share them with your community. Indaband notifies you when someone collaborates with one of your tracks, so you can see how they added their own take on your content.
The app is the brainchild of CEO Daniel Murta, CTO Andrews Medina, Head of Engineering Helielson Santos and Design Leader Emerson Farias. The co-founders came up with the idea for the app when they were working at a legal technology company called Jusbrasil, which Murta co-founded.
Image Credits: Indaband
They all used to get together to play music during happy hours after work, and once the pandemic hit, they came up with the idea for Indaband so they could still play music together while in quarantine. The group then spent their weekends working on Indaband and eventually ended up leaving Jusbrasil to focus on Indaband full-time.
“Music creation is very hard and involves complex software. So, the whole idea was to redesign this process from scratch and make it simple and out of your smartphone,” Murta told TechCrunch. “The idea was that we would unlock musical expression to a different level to make it simple to collaborate and co-create music.”
Indaband helps users discover songs and jam sessions with daily curated playlists that dive into different genres, like rock, jazz, hip-hop and EDM. Users can like and comment on videos and repost them to their followers.
Indaband plans on launching a new feature called “Circles” that Murta compares to clubs on Strava. Circles will allow users to build their own communities on the app and possibly even hold live events. Indaband may also develop a Patreon-like feature within Circles that would allow established creators to offer paid content. For instance, an established musician could offer virtual lessons on an instrument that they have mastered.
Image Credits: Indaband
While Indaband’s early adopters are skilled musicians who are comfortable sharing their music and recording themselves, Indaband eventually plans to target musicians and singers who are just starting out.
“We want to be known as a place where the musical community flourishes,” Murta said. “There is no place for musical communities right now. So the idea is to be known for that, and our strategy is to make it easy to create, and allow everyone to join the creation process.”
Indaband raised $7 million in seed funding in late 2021. The funding round included several angel investors, including Instagram co-founder Mike Krieger and former Megadeth guitar player Kiko Loureiro. The round also included funding from several Latin American VC firms, including Monashees, Astella and Upload Ventures.
If you’ve been feeling lonely over the past few years, you’re not alone. According to a 2023 report from the U.S. surgeon general, about half of U.S. adults reported feeling lonely, even before the COVID-19 pandemic. The report warns that loneliness and isolation can lead to physical consequences, such as a 29% increased risk of heart disease and a 32% increased risk of stroke.
A new app called Buffet is aiming to address the loneliness epidemic by helping users meet new people by quickly matching them with a person and a place to meet up (think Tinder + OpenTable). The app is designed to remove the barriers and hassles that come with meeting new people and then trying to find a place to hang out. Buffet aims to help users meet likeminded individuals, whether they’re looking for a new friend, romantic partner or gym buddy.
At launch, Buffet is available in Los Angeles, with expansions planned for additional cities later this year, starting with New York City.
The app is the brainchild of Buffet CEO Rich Hacking and COO Sean Emery. The pair worked as financial analysts before starting Buffet and came up with the idea for the app while they were on a business trip in Dubai.
“We started throwing this idea around, and thought, hey, there’s something there,” Hacking told TechCrunch. “We saw the loneliness epidemic and saw that the market was in need of something new. The massive incumbents have lacked innovation in the last decade. There was an obvious key opportunity for disruption. So we put one foot in front of the other and started building Buffet.”
To get started with Buffet, users enter five of their interests, such as motorcycles, horseback riding or reading. The app then asks a series of five questions to get a better understanding of their personality and what kinds of places and people they would be interested in.
Image Credits: Buffet
Buffet’s algorithm then pairs users. If interested, they can send an invite to the person they’re matched with; the matched pair can then message each other via the app to decide on a time and date to meet. Buffet is designed to allow people to do most of the talking and getting-to-know-each-other in-person. Buffet encourages people to go beyond a chatbox and digital communication and actually meet up in the real world.
If there’s a match with someone, but the app-suggested meeting place isn’t a good match, users can choose from a list of other places that might be more interesting. And if users aren’t interested in their match partners, they can refresh and get matched with someone else.
Buffet’s target demographic is people who have been affected by the loneliness epidemic the most: 18- to 25-year-olds. The app also wants to target young professionals in the late to early 30s. Hacking believes that if Buffet can win over the average 25-year-old female professional, it can win over anyone.
“The app will be free to use for the foreseeable future,” Hacking said. “We want to win over users. We want to build trust and right now, when you read the market, people are frustrated with all of the paywalls.”
In terms of the app’s business model, Buffet will leverage advertising. The company plans to build up an in-app community forum where local businesses would be able to advertise directly to users and promote happy hours and other discounts.
The app is currently only available on iOS, but the company plans to launch an Android app in the future.
If you think that choosing a nail polish color or which ingredients go into your face cream can’t have anything to do with blockchain, think again.
Kiki World, a beauty startup launched last year, wants consumers to co-create products and co-own the company with the help of web3 technology.
On Tuesday, LA-based Kiki announced that it raised a $7 million seed round from the Andreessen Horowitz crypto fund and The Estée Lauder Companies’ New Incubation Ventures, along with other backers such as Orange DAO and 2 Punks Capital.
Kiki co-founder Jana Bobosikova said she believes that being a loyal user of a brand in the Web 2.0 world can be a net negative experience. “You probably have watched a lot of creators on TikTok recommend it to you. You probably recommended it to all your friends. And what do you get for that? Just more retargeted ads,” she said.
Kiki is flipping that model by allowing its community members to vote on the features they want before the beauty products are made. As a reward, voters earn points toward free products and receive digital tokens in the company.
“It’s a dynamic that the internet and your bathroom have not seen yet,” Bobosikova said. (She may be right about the bathroom, though of course, the internet has seen plenty of customers vote on products and earn digital tokens for their participation.)
Since it’s not uncommon for cosmetics companies to find themselves with large piles of inventory they can’t sell, another benefit of Kiki’s on-demand approach is that it uses less capital and resources.
Although members’ product votes are recorded on Ethereum, Bobosikova said some participants don’t need to know they are taking action on blockchain. Users can sign in with an email, and voila, Kiki has created an on-chain account that will store the members’ votes into perpetuity.
a16z decided to back Kiki after the startup completed its 10-week crypto startup accelerator program. “Jana is a force of nature. She was one of the things that most drew us to the company,” said Arianna Simpson, a general partner at the firm. “She has incredible expertise in the beauty space, but also a unique understanding of web3, which is not always something we see if we have a founder coming out of a more traditional industry.”
Prior to founding Kiki, the Czech-born Bobosikova was the CEO of Epic Future Labs, a product development and brand innovations agency.
Simpson noted that Kiki is not the firm’s only bet on a company that rewards customers using blockchain technology. Last year, a16z led a $24 million Series A of Blackbird Labs, a hospitality tech company that developed a loyalty program that incentivizes guests to dine in independent restaurants.
For now, Kiki has launched five product collections, including a nail polish pen, for which consumers can choose the next color Kiki will manufacture.
But, as Simpson pointed out, Kiki has plans to eventually expand beyond the world of beauty.
How long will it be until it’s possible to vote on jeans styles or purse sizes? Perhaps a while.
“We have faced insane challenges on the physical side of things,” Bobosikova said, adding that some products take much longer to manufacture than others. “The power of asking people what they want and giving it to them, it’s very, very simple. It’s just very hard to do.”
Every year, Time Magazine issues a list of the 200 best inventions of the past 12 months. Frankly, I don’t know how the editors do it. The dirty secret of this job is that true, game-changing inventions rarely cross your desk. In fact, you’re extraordinarily lucky if you average one a year.
Oculus’ Rift prototype felt like just such a device when it first crossed my radar more than a decade ago. More than anything, the system resembled a hastily duct-taped ski mask. It was a remarkable presentation, in hindsight — an all-too-rare glimpse into a plucky entrepreneurial tech spirit. It evokes a flood of romanticized images of Homebrew Computer Club nerds soldering together circuit boards in South Bay garages.
A decade has now passed since Meta (née Facebook) announced plans to acquire the startup for $2 billion. A decade after the deal was announced, it’s safe to say that the VR headset hasn’t changed the world we live in. But there’s always that little-discussed middle ground between transforming the human condition and just being an abject dumpster fire of failure. So, where, as of April 2024, does the Facebook/Oculus deal rank?
“Immersive gaming will be the first, and Oculus already has big plans here that won’t be changing and we hope to accelerate,” Mark Zuckerberg wrote at the time. “After games, we’re going to make Oculus a platform for many other experiences. Imagine enjoying a court side seat at a game, studying in a classroom of students and teachers all over the world or consulting with a doctor face-to-face — just by putting on goggles in your home.”
Image Credits: David Fitzgerald/Sportsfile / Getty Images
Facebook’s founder referred to the Oculus Rift as a “new communication platform,” comparing it to computers, the internet and smartphones before it. He suggested that the “dream of science fiction” was now a reality — one that Facebook had suddenly cornered. It’s hard to overstate how transformative Zuckerberg believed the technology to be. It was, after all, the gateway to the metaverse.
Should anyone doubt the company’s commitment to the concept, in late 2021, it rebranded itself as “Meta,” killing off the Oculus brand the same afternoon. Surely social media platforms wouldn’t dominate online discourse forever. They would eventually give way to something wholly new. Except that despite that $500 billion rebrand, Zuckerberg and company never did a particularly good job of defining the metaverse. They simply insisted that it was an exciting thing that you should be excited about.
Image Credits: Facebook
I suspect that were you to perform a blind poll, the majority of people who are familiar with the term meta would describe something like Second Life, the virtual world that to be on its fifth or sixth life by now. Mark Zuckerberg is probably as guilty as any single person for perpetuating that perception, happily working his hardest to make the company’s Horizon Worlds platform synonymous with conceptions of the metaverse. Remember what a big deal it was when its avatars finally got legs?
So where are we now? It’s complicated, obviously. From a purely financial standpoint (the only language shareholders speak), things are bleak. Between the end of 2020 and the first quarter of 2024, the company’s metaverse division lost $42 billion. That’s roughly 21x the price it paid for Oculus, not adjusting for inflation. That’s a little over one-fourth a Zuckerberg (not adjusted for inflation — i.e., BJJ-related bulking).
Why is Meta hemorrhaging that much money? The simple and cynical answer is, because it can. The corporation made $134 billion in revenue and $39.1 billion in net income last year. That’s not to say that having a division that’s $42 billion in the red over four years doesn’t impact its bottom line, of course. But Facebook believes it’s playing the long game here.
Image Credits: Brian Heater
It’s widely believed that Meta sells its Quest headsets at a loss. This is despite the fact that the company has easily the best manufacturing scale in the industry. It doesn’t take an MBA to understand that this is a terrible short-term strategy, but again, Meta believes it’s playing the long game. The end game is getting enough of these devices into people’s hands to reach a critical mass of adoption, word of mouth and developer content. If you can’t do that while turning a profit, well, you gotta spend money to make money, right?
It continues to be a massive bet. How long the company is willing to play the long game here, however, largely comes down to how much patience Meta’s shareholders have. If it can truly saturate the market and corner content, it will be better positioned to capitalize on mixed reality’s hypothetical exponential growth.
It has already edged the competition out of the market and generally sucked the air out of the room. As an HTC Vive exec told me back in February at MWC, “I think Meta has adjusted the market perception of what this technology should cost.” Other companies can’t compete on price and content in the customer space, so the savviest of the bunch have moved over to enterprise, where clients have much deeper pockets.
If you judge the company’s journey in terms how much of the VR headset market it controls, it’s been a wild and unprecedented success. According to IDC, Meta had a 50.2% share as of Q2 2023. Of course, we’re not talking about smartphone figures here. As of early 2023, Meta was estimated to have sold 20 million headsets. At the end of the year, the Quest 2 was still outselling the Quest 3. One part of the Meta thesis has absolutely played out: People are looking for an inexpensive on-ramp to the technology.
Image Credits: Brian Heater
When Apple announced the Vision Pro at WWDC 2024, I received a flood of unsolicited comments from VR headset manufacturers all stating they saw the iPhone maker’s headset as validation for the space. You can cynically (and correctly) point out that everyone says some version of that when Apple enters their vertical, and many of them don’t make it out the other side in one piece.
But I concur that Apple throwing its hat in the ring after decades of failed VR attempts does constitute validation. That’s absolutely the case for Meta. Zuckerberg happily used the opportunity to point out that his headsets were (1) significantly less expensive and (2) didn’t require an external battery. Meta also had a large head start in terms of VR-specific content. Naturally, Zuckerberg also insisted that his product was vastly superior in spite of the significantly lower price point.
“It seems like there are a lot of people who just assumed that Vision Pro would be higher quality because it’s Apple and it costs $3,000 more,” he noted in February, “but honestly, I’m pretty surprised that Quest is so much better for the vast majority of things that people use these headsets for, with that price differential.”
Sorry, Zuck, the Vision Pro is the more impressive piece of technology. Whether it’s $3,000 more impressive is a different conversation. What I can tell you right now is that the pricing gulf puts these products into different categories. Apple is targeting business customers at that price point, while Meta is far more committed to democratizing access by — again — losing money on a per-unit basis.
It’s still early days for Vision Pro — and, really, mixed reality in general. If it ever does truly become ubiquitous, it will be the result of countless hard-fought battles. As we mark a decade since the Oculus acquisition, I find myself returning to the above Zuckerberg comment: “Imagine enjoying a courtside seat at a game, studying in a classroom of students and teachers all over the world or consulting with a doctor face-to-face — just by putting on goggles in your home.”
Re-reading this from the vantage point of 2024, it strikes me that he was right about the content, but not necessarily the delivery mechanism. The past four years have dramatically impacted how we interact with each other, the world and day-to-day activities. The pandemic de-stigmatized so many virtual activities. But for the time being, no headsets are required.
As AI proliferates and things on the internet are easier to manipulate, there’s a need more than ever to make sure data and brands are verifiable, said Scott Dykstra, CTO and co-founder of Space and Time, on TechCrunch’s Chain Reaction podcast.
“Not to get too cryptographically religious here, but we saw that during the FTX collapse,” Dykstra said. “We had an organization that had some brand trust, like I had my personal life savings in FTX. I trusted them as a brand.”
But the now-defunct crypto exchange FTX was manipulating its books internally and misleading investors. Dykstra sees that as akin to making a query to a database for financial records, but manipulating it inside their own database.
And this transcends beyond FTX, into other industries, too. “There’s an incentive for financial institutions to want to manipulate their records … so we see it all the time and it becomes more problematic,” Dykstra said.
But what is the best solution to this? Dykstra thinks the answer is through verification of data and zero-knowledge proofs (ZK proofs), which are cryptographic actions used to prove something about a piece of information — without revealing the origin data itself.
“It has a lot to do with whether there’s an incentive for bad actors to want to manipulate things,” Dykstra said. Anytime there’s a higher incentive, where people would want to manipulate data, prices, the books, finances or more, ZK proofs can be used to verify and retrieve the data.
At a high level, ZK proofs work by having two parties, the prover and the verifier, that confirm a statement is true without conveying any information more than whether it’s correct. For example, if I wanted to know whether someone’s credit score was above 700, if there’s one in place, a ZK proof — prover — can confirm that to the verifier, without actually disclosing the exact number.
Space and Time aims to be that verifiable computing layer for web3 by indexing data both off-chain and on-chain, but Dykstra sees it expanding beyond the industry and into others. As it stands, the startup has indexed from major blockchains like Ethereum, Bitcoin, Polygon, Sui, Avalanche, Sei and Aptos and is adding support for more chains to power the future of AI and blockchain technology.
Dykstra’s most recent concern is that AI data isn’t really verifiable. “I’m pretty concerned that we’re not really efficiently ever going to be able to verify that an LLM was executed correctly.”
There are teams today that are working on solving that issue by building ZK proofs for machine learning or large language models (LLMs), but it can take years to try and create that, Dykstra said. This means that the model operator can tamper with the system or LLM to do things that are problematic.
There needs to be a “decentralized, but globally, always available database” that can be created through blockchains, Dykstra said. “Everyone needs to access it, it can’t be a monopoly.”
For example, in a hypothetical scenario, Dykstra said OpenAI itself can’t be the proprietor of a database of a journal, for which journalists are creating content. Instead, it has to be something that’s owned by the community and operated by the community in a way that’s readily available and uncensorable. “It has to be decentralized, it’s going to have to be on-chain, there’s no way around it,” Dykstra said.
This story was inspired by an episode of TechCrunch’s podcast Chain Reaction. Subscribe to Chain Reaction on Apple Podcasts, Spotify or your favorite pod platform to hear more stories and tips from the entrepreneurs building today’s most innovative companies.
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