Архив рубрики: Startups

SponsorUnited secures $35M investment to build out its database of brand sponsorships

Sponsorships are a multibillion-dollar industry. But data on sponsorships, like who’s sponsoring who, can be tough to come by because of the various forms they take — and channels on which those sponsorships take place (think not only websites and social media posts but also physical signage and even sports team jerseys). For both brands and the recipients of sponsorships, the lack of data presents a challenge. Brands don’t always know how much to charge sponsors, while sponsors aren’t consistently aware of sponsorship deals currently in place.
Frustrated by the sponsorship space’s opaqueness, Bob Lynch, the former VP of corporate partnerships for the Miami Dolphins, in 2017 founded SponsorUnited, a software-as-a-service platform that provides analytics data on the sponsorship industry. SponsorUnited claims to track over a million sponsorships across 250,000 brands, including every U.S.-based major league sports team.
“When I joined the Miami Dolphins after a decade in media, I immediately realized there was significant complexity and a lack of transparency and standardization within sponsorships, making it hard for brands and teams to optimally partner,” Lynch told TechCrunch in an email interview. “Noticing a similar trend in the NBA and arena events while with the Brooklyn Nets, I realized that if you could democratize access to previously inaccessible sponsorship deal data that the entire industry would want access to it.”
Lynch says that SponsorUnited is serving roughly 2,900 brands and properties, including Fortune 500 firms, talent and brand agencies and media companies — and investors seem pleased with the growth so far. SponsorUnited today closed a $35 million Series A funding round led by Spectrum Equity at a postmoney valuation “north of” $100 million. Paired with previous investments from Milwaukee Bucks owner Marc Lasry and San Diego Padres co-owner Ron Fowler, the infusion brings the startup’s total raised to $38.6 million.
“Up to this point, SponsorUnited had raised minimal capital, preferring to stay lean while building our data capture infrastructure and platform,” Lynch said. “But as we’ve gained critical mass beyond properties (e.g., teams and events) with brands, media, agencies and international expansion, we saw an opportunity to further accelerate growth by automating and scaling valuable data.”
Lynch describes SponsorUnited as “the Bloomberg terminal of marketing partnerships.” It’s essentially a search layer on top of a database of sports, esports, music, entertainment and media sponsorship deals, brands and properties. SponsorUnited acquires all the data directly without tapping into third-party sources, and it serves it in a way that allows companies to combine it with other data around sponsorship, including internal spend, return on investment and engagement.
A cursory Google search reveals several companies attempting to solve the same problem as SponsorUnited. There’s GlobalData, the sports-focused SportBusiness and SponsorPitch, to name a few. When asked about these rivals and others, Lynch pointed out that SponsorUnited tracks more categories of sponsorships than most and has invested heavily in its tech stack, which uses both automated and manual methods to compile sponsorship data.
“We have cultivated, refreshed, and expanded a vast repository of information — over five million data points on more than 500 asset types,” Lynch said. “We continue to invest in technology to scale and replicate the processes by which sponsorship data is tracked.”
So what’s next for SponsorUnited? Lynch says he’s tracking trends like sponsorships in the metaverse (to the extent they’re a thing), college athlete deals enabled by last year’s Supreme Court decision, and TikTok’s growing reach with younger audiences. The pandemic was and continues to be a boon for SponsorUnited, he says, as marketing organizations seek to track how deals shift from live events to digital.
In potentially good news for SponsorUnited, a 2021 survey from Caravel Marketing found that 52% of corporations planned to increase their budgets for sports team sponsorships in 2022, with only 16% projecting a decrease in spending. Lynch makes the case that these spenders will be inclined to subscribe to SponsorUnited’s services even if the economy ultimately takes a dip; when budgets tighten, it becomes imperative to discover the right partnerships and “optimize” current sponsorships, he asserts.
“The complexity and number of marketing assets and platforms being bought and sold in this industry is rising at an exponential pace,” Lynch said. “Our data provides valuable insights not only to IT but across the C-suite — chief marketing officers, chief revenue officers, chief customer officers and others.”
Stamford, Connecticut–based SponsorUnited — which isn’t revealing revenue figures — expects to have 100 employees by the end of the year, Lynch added.
SponsorUnited secures $35M investment to build out its database of brand sponsorships by Kyle Wiggers originally published on TechCrunch
SponsorUnited secures $35M investment to build out its database of brand sponsorships

Meet Unstable Diffusion, the group trying to monetize AI porn generators

When Stable Diffusion, the text-to-image AI developed by startup Stability AI, was open sourced earlier this year, it didn’t take long for the internet to wield it for porn-creating purposes. Communities across Reddit and 4chan tapped the AI system to generate realistic and anime-style images of nude characters, mostly women, as well as non-consensual fake nude imagery of celebrities.
But while Reddit quickly shut down many of the subreddits dedicated to AI porn, and communities like NewGrounds, which allows some forms of adult art, banned AI-generated artwork altogether, new forums emerged to fill the gap.
By far the largest is Unstable Diffusion, whose operators are building a business around AI systems tailored to generate high-quality porn. The server’s Patreon — started to keep the server running as well as fund general development — is currently raking in over $2,500 a month from several hundred donors.
“In just two months, our team expanded to over 13 people as well as many consultants and volunteer community moderators,” Arman Chaudhry, one of the members of the Unstable Diffusion admin team, told TechCrunch in a conversation via Discord. “We see the opportunity to make innovations in usability, user experience and expressive power to create tools that professional artists and businesses can benefit from.”
Unsurprisingly, some AI ethicists are as worried as Chaudhry is optimistic. While the use of AI to create porn isn’t new  — TechCrunch covered an AI-porn-generating app just a few months ago — Unstable Diffusion’s models are capable of generating higher-fidelity examples than most. The generated porn could have negative consequences particularly for marginalized groups, the ethicists say, including the artists and adult actors who make a living creating porn to fulfill customers’ fantasies.
A censored image from Unstable Diffusion’s Discord server. Image Credits: Unstable Diffusion
“The risks include placing even more unreasonable expectations on women’s bodies and sexual behavior, violating women’s privacy and copyrights by feeding sexual content they created to train the algorithm without consent and putting women in the porn industry out of a job,” Ravit Dotan, VP of responsible AI at Mission Control, told TechCrunch. “One aspect that I’m particularly worried about is the disparate impact AI-generated porn has on women. For example, a previous AI-based app that can ‘undress’ people works only on women.”
Humble beginnings
Unstable Diffusion got its start in August — around the same time that the Stable Diffusion model was released. Initially a subreddit, it eventually migrated to Discord, where it now has roughly 50,000 members.
“Basically, we’re here to provide support for people interested in making NSFW,” one of the Discord server admins, who goes by the name AshleyEvelyn, wrote in an announcement post from August. “Because the only community currently working on this is 4chan, we hope to provide a more reasonable community which can actually work with the wider AI community.”
Early on, Unstable Diffusion served as a place simply for sharing AI-generated porn — and methods to bypass the content filters of various image-generating apps. Soon, though, several of the server’s admins began exploring ways to build their own AI systems for porn generation on top of existing open source tools.
Stable Diffusion lent itself to their efforts. The model wasn’t built to generate porn per se, but Stability AI doesn’t explicitly prohibit developers from customizing Stable Diffusion to create porn so long as the porn doesn’t violate laws or clearly harm others. Even then, the company has adopted a laissez-faire approach to governance, placing the onus on the AI community to use Stable Diffusion responsibly.
Stability AI didn’t respond to a request for comment.
The Unstable Diffusion admins released a Discord bot to start. Powered by the vanilla Stable Diffusion, it let users generate porn by typing text prompts. But the results weren’t perfect: the nude figures the bot generated often had misplaced limbs and distorted genitalia.
Image Credits: Unstable Diffusion
The reason why was that the out-of-the-box Stable Diffusion hadn’t been exposed to enough examples of porn to “know” how to produce the desired results. Stable Diffusion, like all text-to-image AI systems, was trained on a dataset of billions of captioned images to learn the associations between written concepts and images, like how the word “bird” can refer not only to bluebirds but parakeets and bald eagles in addition to more abstract notions. While many of the images come from copyrighted sources, like Flickr and ArtStation, companies such as Stability AI argue their systems are covered by fair use — a precedent that’s soon to be tested in court.
Only a small percentage of Stable Diffusion’s dataset — about 2.9% — contains NSFW material, giving the model little to go on when it comes to explicit content. So the Unstable Diffusion admins recruited volunteers — mostly members of the Discord server — to create porn datasets for fine-tuning Stable Diffusion, the way you would give it more pictures of couches and chairs if you wanted to make a furniture generation AI.
Much of the work is ongoing, but Chaudhry tells me that some of it has already come to fruition, including a technique to “repair” distorted faces and arms in AI-generated nudes. “We are recording and addressing challenges that all AI systems run into, namely collecting a diverse dataset that is high in image quality, captioned richly with text, covering the gamut of preferences of our users,” he added.
The custom models power the aforementioned Discord bot and Unstable Diffusion’s work-in-progress, not-yet-public web app, which the admins say will eventually allow people to follow AI-generated porn from specific users.
Growing community
Today, the Unstable Diffusion server hosts AI-generated porn in a range of different art styles, sexual preferences and kinks. There’s a “men-only” channel, a softcore and “safe for work” stream, channels for hentai and furry artwork, a BDSM and “kinky things” subgroup — and even a channel reserved expressly for “nonhuman” nudes. Users in these channels can invoke the bot to generate art that fits the theme, which they can then submit to a “starboard” if they’re especially pleased with the results.
Unstable Diffusion claims to have generated over 4,375,000 images to date. On a semiregular basis, the group hosts competitions that challenge members to recreate images using the bot, the results of which are used in turn to improve Unstable Diffusion’s models.
Image Credits: Unstable Diffusion
As it grows, Unstable Diffusion aspires to be an “ethical” community for AI-generated porn — i.e. one that prohibits content like child pornography, deepfakes and excessive gore. Users of the Discord server must abide by the terms of service and submit to moderation of the images that they generate; Chaudhry claims the server employs a filter to block images containing people in its “named persons” database and has a full-time moderation team.
“We strictly allow only fictional and law-abiding generations, for both SFW and NSFW on our Discord server,” he said. “For professional tools and business applications, we will revisit and work with partners on the moderation and filtration rules that best align with their needs and commitments.”
But one imagines Unstable Diffusion’s systems will become tougher to monitor as they’re made more widely available. Chaudhry didn’t lay out plans for moderating content from the web app or Unstable Diffusion’s forthcoming subscription-based Discord bot, which third-party Discord server owners will be able to deploy within their own communities.
“We need to … think about how safety controls might be subverted when you have an API-mediated version of the system that carries controls preventing misuse,” Abhishek Gupta, the founder and principal researcher at the Montreal AI Ethics Institute, told TechCrunch via email. “Servers like Unstable Diffusion become hotbeds for accumulating a lot of problematic content in a single place, showing both the capabilities of AI systems to generate this type of content and connecting malicious users with each other to further their ‘skills’ in the generation of such content .. At the same time, they also exacerbate the burden placed on content moderation teams, who have to face trauma as they review and remove offensive content.”
A separate but related issue pertains to the artists whose artwork was used to train Unstable Diffusion’s models. As evidenced recently by the artist community’s reaction to DeviantArt’s AI image generator, DreamUp, which was trained on art uploaded to DeviantArt without creators’ knowledge, many artists take issue with AI systems that mimic their styles without giving proper credit or compensation.
Character designers like Hollie Mengert and Greg Rutkowski, whose classical painting styles and fantasy landscapes have become one of the most commonly used prompts in Stable Diffusion, have decried what they see as poor AI imitations that are nevertheless tied to their names. They’ve also expressed concerns that AI-generated art imitating their styles will crowd out their original works, harming their income as people start using AI-generated images for commercial purposes. (Unstable Diffusion grants users full ownership of — and permission to sell — the images they generate.)
Gupta raises another possibility: artists who’d never want their work associated with porn might become collateral damage as users realize certain artists’ names yield better results in Unstable Diffusion prompts — e.g., “nude women in the style of [artist name]”.
Image Credits: Unstable Diffusion
Chaudhry says that Unstable Diffusion is looking at ways to make its models “be more equitable toward the artistic community” and “give back [to] and empower artists.” But he didn’t outline specific steps, like licensing artwork or allowing artists to preclude their work from training datasets.
Artist impact
Of course, there’s a fertile market for adult artists who draw, paint and photograph suggestive works for a living. But if anyone can generate exactly the images they want to see with an AI, what will happen to human artists?
It’s not an imminent threat, necessarily. As adult art communities grapple with the implications of text-to-image generators, Simply finding a platform to publish AI-generated porn beyond the Unstable Diffusion Discord might prove to be a challenge. The furry art community FurAffinity decided to ban AI-generated art altogether, as did Newgrounds, which hosts mature art behind a content filter.
When reached for comment, one of the larger adult content hosts, OnlyFans, left open the possibility that AI art might be allowed on its platform in some form. While it has a strict policy against deepfakes, OnlyFans says that it permits content — including AI-generated content, presumably — as long as the person featured in the content is a verified OnlyFans creator.
Of course, the hosting question might be moot if the quality isn’t up to snuff.
“AI generated art to me, right now, is not very good,” said Milo Wissig, a trans painter who has experimented with how AIs depict erotic art of non-binary and trans people. “For the most part, it seems like it works best as a tool for an artist to work off of… but a lot of people can’t tell the difference and want something fast and cheap.”
For artists working in kink, it’s especially obvious to see where AI falls flat. In the case of bondage, in which tying ropes and knots is a form of art (and safety mechanism) in itself, it’s hard for the AI to replicate something so intricate.
“For kinks, it would be difficult to get an AI to make a specific kind of image that people would want,” Wissig told TechCrunch. “I’m sure it’s very difficult to get the AI to make the ropes make any sense at all.”
The source material behind these AIs can also amplify biases that already exist in traditional erotica – in other words, straight sex between white people is the norm.
“You get images that are pulled from mainstream porn,” said Wissig. “You get the whitest, most hetero stuff that the machine can think up, unless you specify not to do that.”
Image Credits: Milo Wissig
These racial biases have been extensively documented across applications of machine learning, from facial recognition to photo editing.
When it comes to porn, the consequences may not be as stark – yet there is still a special horror to watching as an AI twists and augments ordinary people until they become racialized, gendered caricatures. Even AI models like DALLE-2, which went viral when its mini version was released to the public, have been criticized for disproportionately generating art in European styles.
Last year, Wissig tried using VQGAN to generate images of “sexy queer trans people,” he wrote in an Instagram post. “I had to phrase my terms carefully just to get faces on some of them,” he added.
In the Unstable Diffusion Discord, there is little evidence to support that the AI can adequately represent genderqueer and transgender people. In a channel called “genderqueer-only,” nearly all of the generated images depict traditionally feminine women with penises.
Branching out
Unstable Diffusion isn’t strictly focusing on in-house projects. Technically a part of Equilibrium AI, a company founded by Chaudhry, the group is funding other efforts to create porn-generating AI systems including Waifu Diffusion, a model fine-tuned on anime images.
Chaudhry sees Unstable Diffusion evolving into an organization to support broader AI-powered content generation, sponsoring dev groups and providing tools and resources to help teams build their own systems. He claims that Equilibrium AI secured a spot in a startup accelerator program from an unnamed “large cloud compute provider” that comes with a “five-figure” grant in cloud hardware and compute, which Unstable Diffusion will use to expand its model training infrastructure.
In addition to the grant, Unstable Diffusion will launch a Kickstarter campaign and seek venture funding, Chaudhry says. “We plan to create our own models and fine-tune and combine them for specialized use cases which we shall spin off into new brands and products,” he added.
The group has its work cut out for it. Of all the challenges Unstable Diffusion faces, moderation is perhaps the most immediate — and consequential. Recent history is filled with examples of spectacular failures at adult content moderation. In 2020, MindGeek, Pornhub’s parent company, lost the support of major payment processors after the site site was found to be circulating child porn and sex-trafficking videos.
Will Unstable Diffusion suffer the same fate? It’s not yet clear. But with at least one senator calling on companies to implement stricter content filtering in their AI systems, the group doesn’t appear to be on the steadiest ground.
Meet Unstable Diffusion, the group trying to monetize AI porn generators by Kyle Wiggers originally published on TechCrunch
Meet Unstable Diffusion, the group trying to monetize AI porn generators

Elon guts Twitter, Google shutters Hangouts, and the tech layoffs continue

Hey, all — welcome back to Week in Review, the newsletter where we sum up the most read TechCrunch stories from the past week. And oof, what a week it was.
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most read
Mass layoffs at Twitter: It was Elon’s first full week as the boss of Twitter post-$44 billion acquisition. Sweeping layoffs were said to be on the way — and, well, they’ve begun. After a painfully impersonal heads-up email went out Thursday evening, entire teams are waking up to find their access suddenly revoked. With reports suggesting layoffs could impact up to half the company, Twitter employees have reportedly taken to referring to the whole thing as “the snap” (à la Thanos). A class action lawsuit has already been filed alleging that Twitter isn’t following the proper legal processes here.
Layoffs everywhere: Meanwhile, news of tech industry layoffs continues to pour in. Lyft let go of 13% of its workforce, Stripe cut 14%, Opendoor reduced its workforce by 18%, Chime parted ways with 12%, and more. Meanwhile, both Apple and Amazon have reportedly gone into hiring freezes.
Google kills Hangouts: We knew it was coming, but this week Google put the final nail in Hangouts’ coffin, shutting down the chat-focused web app (the Hangouts Android/iOS apps were shuttered last year) in favor of Google Chat. Of course, given Google’s history with chat apps, I expect at least two more to be launched and/or shuttered by the time I finish this newsletter.
Falcon Heavy returns to space: This week SpaceX launched its Falcon Heavy rocket for the first time since 2019, finally moving forward on a mission that had been delayed (“due to payload readiness issues”) since late 2020.
Amazon expands its Music service: “The company said it will now offer Prime subscribers a full music catalog with 100 million songs, instead of the previously more limited selection of just 2 million songs,” writes Sarah, “and will make most of the top podcasts on its service available without ads.”
audio roundup
Whats up in TC podcast land this week? Here’s some of the highlights:
The Equity crew chatted about the ever-evolving role of the venture capitalist, and our friend Melia Russell from Business Insider stopped by to fill us in on her recent story about how “investors are rewriting the playbooks when it comes to maternity leave policies at their firms.”
Amanda joined Darrell on the TC Podcast to discuss Elon’s “questionable plans” to change up how identity verification works on Twitter
The Chain Reaction team dive into the growing list of troubles that have developed for Bitcoin miners in the last few months.
techcrunch+
Not a part of TechCrunch+ yet? Here’s what TC+ members were reading most behind the paywall:
Pilot’s CEO tears down their $60 million Series C deck: Published in early 2021, this one blew up for some reason this week! Just a few weeks after raising a big Series C, Pilot CEO Waseem Daher sat down with Lucas Matney to break down what worked about their pitch deck.
The most common pitch deck mistakes: Speaking of pitch decks, TC’s resident pitch expert, Haje Jan Kamps, has a list of the mistakes he’s tired of seeing in decks, having reviewed thousands of them.
Elon guts Twitter, Google shutters Hangouts, and the tech layoffs continue by Greg Kumparak originally published on TechCrunch
Elon guts Twitter, Google shutters Hangouts, and the tech layoffs continue

Nigerian data and intelligence company Stears raises $3.3M, backed by Mac VC and Serena Ventures

While studying at the London School of Economics and the University of Oxford, a group of graduates noticed how difficult it was to get data and information on Africa’s largest economy and their home country, Nigeria. Each had different yet complementary skills — Michael Famoroti, an economist; Bode Ogunlana, a software engineer; Abdul Abdulrahim, a data scientist; and Preston Ideh, a corporate lawyer — and in 2017, they launched a media startup to address the dearth of information and data-driven insights in the West African country. 
Five years on, this startup, Stears, is announcing a $3.3 million seed round led by MaC Venture Capital. Serena Ventures, Omidyar Group’s Luminate Fund, Melo 7 Tech Partners and Cascador (Empowering Economic Growth Foundation) participated. This news is coming two years after Stears raised $650,000 in pre-seed funding. Last month, it was one of the 60 startups to get accepted into the Google for Startups Black Founders Fund 2022 cohort, which included some non-dilutive funding.
Stears started as a media publication focused on financial news and insights in Nigeria. Its flagship subscription insights product, Stears Premium, contains content ranging from news and opinion pieces to investigative pieces and deep dives, educating the general public on issues around business and finance, economy, government and policy in Nigeria. The $100-a-year product witnessed significant usage among consumers, particularly employees working in various finance-related institutions across the country. And because these institutions have more spending power, Stears subsequently tailored the product to businesses who wanted to subscribe on behalf of their teams. Some of its subscribers include financial institutions like Sterling Bank, and fintechs like Sparkle, PiggyVest and Paystack. The company says its userbase has grown mainly organically at around 6.5% month-on-month, doubling its total number of users over the last year. 
“We have a strong understanding of the kind of information people need. So our focus is on standardizing information dissemination and building with the customer in mind,” Ideh told TechCrunch in an interview. “An essential part of our business model is pushing out high-value subscription data products, for instance, proprietary forecast models. Conversely, the low-value end will be news, so customers’ willingness to spend changes as they go along the spectrum.” 
The iteration of Stears Premium, alongside the introduction of other products Stears Pro and Stears Advisory, has seen Stears morph into a data and intelligence company. Macro trends and topics like GDP and inflation drive content on Stears Premium. Stears Pro, on the other hand, provides more bespoke content around specific issues such as market entry, country analysis and digital economy for international organizations such as the United Nations Development Programme, the Foreign Commonwealth and Development Office and the knowledge workers—people need a great deal of data for their work, which may include roles such as analysts, portfolio managers, researchers and economists—that work in them. 
But in a bid to support its transition from an insights company to a data company and buoyed by this new investment, Stears is planning a strategy modification for the Pro product. According to the company’s COO and data scientist Abdulrahim, the data outfit is working with international development institutions and financial institutions to produce proprietary and exclusive datasets that don’t exist anywhere else. Therefore, instead of reporting insights from the data it sources, Stears wants to collate data, engage in deep data analytics and present it to its business customers in various formats. 
“An essential part of our business model is pushing out high-value subscription data products. And as we advance, we’ll do less custom work for this set of customers and focus more on overall data around the same sector,” added Ideh, on the direction Stears is taking with its Pro product. “So the difference in output is such that in the past, we put out reports, but in the future, we’re probably going to put out data feeds. So less text-heavy way of publishing and more of forecast and prediction around sectors that matter to knowledge workers and their organizations.”
Stears Advisory — the product where Stears wears its consultancy hat and takes on third-party projects around its core coverage — is taking a rear seat as the company intends to double down on Pro and Premium. CEO Ideh explained that while the Advisory product, which he likens to a research and development (R&D) arm sponsored by different partners, allows Stears to experiment with data collection and analysis and provides the bedrock to carve out further insights, it’s not scalable and lacks the sort of recurring revenue that venture-backed businesses need.  
Image Credits: Stears
So far, the company’s strategy seems to be paying off. Enterprise customers now contribute over 75% of revenues generated, up from 45% in 2021. It also expects revenues to double from last year as half-year revenues for 2022 have already surpassed full-year revenues for 2021. This is compared to the 80% revenue growth between FY 2021 and FY 2020.
As a data and intelligence company, Stears finds itself in a sweet spot where it is incentivized to pursue political projects that would draw attention if it were a media or tech company. In 2019, the company embarked on one such project as it developed Nigeria’s first real-time election database. Over 2 million Nigerians used it to monitor the general elections. Ideh said his company intends to relaunch the election data site, this time with more datasets and functionalities, in anticipation of Nigeria’s 2023 elections.
“Bloomberg, at its core, is a data company; we love how they approach elections and our approach in 2019 was driven by them,” said Ideh, who has always been vocal about Stears building the Bloomberg of Africa. “This is a big open data effort for us and we are also excited about polling because it is a very important form of data verification currently missing in Nigeria. And so over the election period, we will run and push out statistically representative polls on Nigeria, using strong data mindsets, to get a sense of public opinion issues and achieve more robust results.”
According to Ideh, the seed investment will take Stears from a v2.0, a Nigerian insight company, to a v3.0, a data company focused on Africa. The company plans to use the investment to enhance its data collection and analytics capabilities, hire data scientists, data analysts and sector analysts, and expand to east Africa through Kenya, southern Africa through the eponymous country and north Africa through Egypt. 
“Africa is home to the first humans and is now the next frontier for business,” said Marlon Nichols, co-founder and managing general partner at lead investor MaC Venture Capital on the investment. “Many multinational corporations and governments understand this to be a reality. They also appreciate that several African countries are subject to unique business processes and are primarily cash-based economies, which results in understated GDP, among other things. Stears is uniquely positioned to provide the proprietary and accurate data needed to unlock trade and deeper business relationships with African countries and companies.”
Nigerian data and intelligence company Stears raises $3.3M, backed by Mac VC and Serena Ventures by Tage Kene-Okafor originally published on TechCrunch
Nigerian data and intelligence company Stears raises $3.3M, backed by Mac VC and Serena Ventures

Regie secures $10M to generate marketing copy using AI

Regie.ai, a startup using OpenAI’s GPT-3 text-generating system to create sales and marketing content for brands, today announced that it raised $10 million in Series A funding led by Scale Venture Partners with participation from Foundation Capital, South Park Commons, Day One Ventures and prominent angel investors. The fresh investment comes as VCs see a growing opportunity in AI-powered, copy-generating adtech companies, whose tech promises to save time while potentially increasing personalization.
Regie was founded in 2020 by Matt Millen and Srinath Sridhar. Previously a software engineer at Google and Meta, Sridhar is a data scientist by trade, having developed enterprise-scale AI systems that detect duplicate images and rank search results. Millen was formerly a VP at T-Mobile, leading the national sales teams (e.g., strategic accounts and public sector).
With Regie, Sridhar says he and Millen aimed to create a way for companies to communicate with their customers via channels like email, social media, text, podcasts, online advertising and more. Because companies have so many platforms and mediums at their disposal to speak with customers, he notes, it can be a challenge for content marketers to produce continuously compelling content to reach their customers.
“The way content is getting generated has fundamentally changed,” Sridhar told TechCrunch in an email interview. “Marketers and copywriters working in the enterprise … increasingly [need] to produce and manage content and content workflows at scale.”
Regie uses GPT-3 to power its service — the same GPT-3 that can generate poetry, prose and academic papers. But it’s a “flavor” of GPT-3 fine-tuned on a training data set of roughly 20,000 sales sequences (the series of steps to convert prospects into paying customers) and nearly 100 million sales emails. Also in the mix are custom language systems built by Regie to reflect brands and their messaging, designed to be integrated with existing sale platforms like Outreach, HubSpot, and Salesloft.
Image Credits: Regie
Lest the systems spew problematic language, Regie says that every system goes through “human curation” and vetting before being released. The startup also claims to train the systems on “inclusive” language and test them for biases, like bias against certain demographic groups.
Customers can use Regie to generate original, optimized-for-search-engines content or create custom sales sequences. The platform also offers blog- and social-media-post-authoring tools for personalizing messages, as well as a Chrome extension that analyzes the “quality” of emails that customers send — and optionally rewrites the text.
“Generative AI is completely disrupting the way content is created today. The biggest competitors of Regie would be the large content authoring and management platforms that will be completely redesigned AI first going forward,” Sridhar said confidently. “For example, Adobe’s suite of products including Acrobat, Illustrator, Photoshop, now Figma as well as Adobe Experience Cloud will start to get outdated as Regie continues to build on an intelligent content creation and management platform for the enterprise.”
More immediately, Regie competes with vendors like Jasper, Phrasee, Copysmith and Copy.ai — all of which tap AI to generate bespoke marketing copy. But Sridhar argues that Regie is a more vertical platform that caters to go-to-market teams in the enterprise while combining text, images and workflows into a single glass pane.
“Generative AI is such a paradigm shift that not only productivity and top-line of companies will go up as a result, but the bottom line will also go down simultaneously. There are very few products that can improve both sides of that financial equation,” Sridhar continued. “So if a company wants to reduce costs because they want to assimilate sales tools, or reduce outsourced writing while simultaneously increasing revenue, Regie can do that. If you are an outsourced marketing agency looking to retain more customers and efficiently generate content at scale, Regie can definitely do that for agencies as well.”
The company currently has more than 70 software-as-a-service customers on annual contracts, including AT&T, Sophos, Okta and Crunchbase. Sridhar didn’t reveal revenue but said that he expects the 25-person company to grow “meaningfully” this year.
“This is a revolutionary new field. And as always, adoption will require educating the users,” Sridhar said. “It is clear to us as practitioners that the world has changed. But it will take time for others to get their hands dirty and convince themselves that this is happening — and that it is a very positive development. So we have to be patient in educating the industry. We also have to show that content quality isn’t compromised and that it can perform better and be maintained more consistently with the strategic application of AI.”
To date, Regie has raised $14.8 million.
Regie secures $10M to generate marketing copy using AI by Kyle Wiggers originally published on TechCrunch
Regie secures $10M to generate marketing copy using AI