European regulation is turning ESG (environmental, social, and governance) reporting from a nice-to-have to a must. This creates new tailwinds for startups such as Paris-based Apiday, whose platform targets private equity funds and blue-chip companies needing to track and pilot sustainability practices.
Asset management firms have been a key target for Apiday, especially European ones. Because of the Sustainable Finance Disclosure Regulation (SFDR), it is not just impact funds that keep close tabs on sustainability metrics: All sorts of firms are now paying attention to ESG reporting.
This creates a different environment from when Apiday was founded in 2021 and as ESG continues to face backlash. CEO Édouard Audi engaged with Elon Musk’s criticism of ESG ratings and agrees that these have limits. But his focus with Apiday is on using ESG for value creation and not merely compliance.
The company just raised €10 million in a Series A funding round, which will help Apiday accelerate its growth in a space that includes well-funded competitors such as AlphaSense, Dataminr and Sesamm, as well as FactSet-owned Truvalue Labs.
Like these players, Apiday leverages AI to save time for its customers. But like legacy consultants, it also offers human expertise. It’s the combination of both that gives it an edge over competitors old and new, Audi told TechCrunch in an interview.
Another differentiator is its expansion plan. With clients in 23 countries and 60% of its sales generated outside of France, it plans to double down on Europe and open offices in Germany and the U.K. Since it also aims to improve its offer overall, it expects its team to grow from 40 to 70 employees over the next 12 months.
Audi also hopes that Apiday’s latest funding round will boost the company’s standing among asset management firms.
Image Credits: Apiday
Before co-founding Apiday with former investor Charles Moury, Audi co-founded ride-hailing company LeCab, and this journey inspired him to go into the ESG space. Compared to competitors, LeCab was doing better in some ESG-related respects, Audi said, but that wasn’t properly taken into account in its sale due to a lack of metrics on these topics.
Again, the way that investors engage with ESG now is not the same as it was back then, and on the corporate side, ESG reporting is about to get another boost from the Corporate Sustainability Reporting Directive (CSRD). “The importance of ESG data will increase dramatically over the next few years,” said Stanislas Lot, the partner who led the round at Daphni.
Image Credits: Apiday
Data is only the basis, though. What’s more important is what can be done with it. Apiday, for instance, assists its customers with developing roadmaps, including some 350 actions they can take to improve their ESG practices after becoming compliant. Funds have already reached that phase, but Apiday expects corporates to follow, and it will be interesting to see how quickly they do.
Its Series A backers include AENU, Daphni, Galion.exe and SWEN Capital, as well as existing investors Speedinvest and Revent.
European regulation is turning ESG (environmental, social, and governance) reporting from a nice-to-have to a must. This creates new tailwinds for startups such as Paris-based Apiday, whose platform targets private equity funds and blue-chip companies needing to track and pilot sustainability practices.
Asset management firms have been a key target for Apiday, especially European ones. Because of the Sustainable Finance Disclosure Regulation (SFDR), it is not just impact funds that keep close tabs on sustainability metrics: All sorts of firms are now paying attention to ESG reporting.
This creates a different environment from when Apiday was founded in 2021 and as ESG continues to face backlash. CEO Édouard Audi engaged with Elon Musk’s criticism of ESG ratings and agrees that these have limits. But his focus with Apiday is on using ESG for value creation and not merely compliance.
The company just raised €10 million in a Series A funding round, which will help Apiday accelerate its growth in a space that includes well-funded competitors such as AlphaSense, Dataminr and Sesamm, as well as FactSet-owned Truvalue Labs.
Like these players, Apiday leverages AI to save time for its customers. But like legacy consultants, it also offers human expertise. It’s the combination of both that gives it an edge over competitors old and new, Audi told TechCrunch in an interview.
Another differentiator is its expansion plan. With clients in 23 countries and 60% of its sales generated outside of France, it plans to double down on Europe and open offices in Germany and the U.K. Since it also aims to improve its offer overall, it expects its team to grow from 40 to 70 employees over the next 12 months.
Audi also hopes that Apiday’s latest funding round will boost the company’s standing among asset management firms.
Image Credits: Apiday
Before co-founding Apiday with former investor Charles Moury, Audi co-founded ride-hailing company LeCab, and this journey inspired him to go into the ESG space. Compared to competitors, LeCab was doing better in some ESG-related respects, Audi said, but that wasn’t properly taken into account in its sale due to a lack of metrics on these topics.
Again, the way that investors engage with ESG now is not the same as it was back then, and on the corporate side, ESG reporting is about to get another boost from the Corporate Sustainability Reporting Directive (CSRD). “The importance of ESG data will increase dramatically over the next few years,” said Stanislas Lot, the partner who led the round at Daphni.
Image Credits: Apiday
Data is only the basis, though. What’s more important is what can be done with it. Apiday, for instance, assists its customers with developing roadmaps, including some 350 actions they can take to improve their ESG practices after becoming compliant. Funds have already reached that phase, but Apiday expects corporates to follow, and it will be interesting to see how quickly they do.
Its Series A backers include AENU, Daphni, Galion.exe and SWEN Capital, as well as existing investors Speedinvest and Revent.
European regulation is turning ESG reporting from a nice-to-have to a must. This creates new tailwinds for startups such as Paris-based Apiday, whose platform targets private equity funds and blue-chip companies needing to track and pilot sustainability practices.
Asset management firms have been a key target for Apiday, especially European ones. Because of the Sustainable Finance Disclosure Regulation (SFDR), it is not just impact funds that keep close tabs on sustainability metrics: All sorts of firms are now paying attention to ESG reporting.
This creates a different environment from when Apiday was founded in 2021, but also one in which ESG backlash has appeared. CEO Édouard Audi Audi himself engaged with Elon Musk’s criticism of ESG ratings, and agrees that these have limits. But his focus with Apiday is on using ESG for value creation and not merely compliance.
The company just raised €10 million in a Series A funding round, which will help Apiday accelerate its growth in a space that includes well-funded competitors such as AlphaSense, Dataminr and Sesamm, as well as FactSet-owned Truvalue Labs.
Like these players, Apiday leverages AI to save time for its customers. But like legacy consultants, it also offers human expertise. It’s the combination of both that gives it an edge over competitors old and new, CEO Édouard Audi told TechCrunch in an interview.
Another differentiator is its expansion plan. With clients in 23 countries and 60% of its sales generated outside of France, it plans to double down on Europe and open offices in Germany and the U.K. Since it also aims to improve its offer overall, it expects its team to grow from 40 to 70 employees over the next 12 months.
Audi also hopes that Apiday’s latest funding round will boost the company’s standing among asset management firms.
Image Credits: Apiday
Before co-founding Apiday with former investor Charles Moury, Audi co-founded ride-hailing company LeCab, and this journey inspired him to go into the ESG space. Compared to competitors, LeCab was doing better in some ESG-related respects, Audi said, but that wasn’t properly taken into account in its sale due to a lack of metrics on these topics.
Again, the way that investors engage with ESG now is not the same as it was back then; and on the corporate side, ESG reporting is about to get another boost from the Corporate Sustainability Reporting Directive (CSRD). “The importance of ESG data will increase dramatically over the next few years,” said Stanislas Lot, the partner who led the round at Daphni.
Image Credits: Apiday
Data is only the basis, though. What’s more important is what can be done with it. Apiday, for instance, assists its customers with developing roadmaps including some 350 actions they can take to improve their ESG practices after becoming compliant. Funds have already reached that phase, but Apiday expects corporates to follow, and it will be interesting to see how quickly they do.
Its Series A backers include AENU, Daphni, Galion.exe and SWEN Capital, as well as existing investors Speedinvest and Revent.
You know that mildly jarring experience whenever that well-known celebrity shows up in an entirely different context — e.g. a musician making a horror flick cameo; an NFL player rearing their head in a comedy series; or a Hollywood movie icon selling mobile phone plans on TV? Well, it’s starting to feel like that with Spotify’s foray into the enterprise and developer tooling space — nothing wrong with it per se, but it makes you flinch just a little due to its divergence from the norm.
What we’re talking about is Backstage, a platform and framework Spotify introduced internally in 2016 to bring order to its developer infrastructure. Backstage powers customizable “developer portals” that combine tooling, apps, data, services, APIs and documents in a single interface. Want to monitor Kubernetes, check your CI/CD status or track security incidents? Backstage to the rescue.
Lots of companies construct their own internal systems to help developers work more efficiently. And lots of companies release such systems to the public via an open source license to spur wider adoption, as Spotify did with Backstage in 2020. But it’s highly unusual for a consumer technology company to actively monetize this side of its business, which Spotify has been doing since 2022.
Now, Spotify is leaning even further into this play with the launch of a new suite of products and services designed to make Backstage the de facto developer portal platform for the software development industry.
Spotify’s grand plan to monetize developers via its open source Backstage project
Modular
Backstage is built on a modular, plug-in based architecture that allows engineers to layer-up their developer portal to meet their own needs. There is already a thriving marketplace for Backstage plug-ins, some developed by Spotify itself and some by the wider community, including developers from Red Hat and Amazon Web Services (AWS) — AWS, for example, has developed a plug-in to make data from Amazon Elastic Container Service (ECS) available in Backstage.
Since late 2022, Spotify has been selling a handful of premium plug-ins as a subscription, such as Backstage Insights, which serves up data related to Backstage usage across an organization, including which plugins they’re engaging with most.
The open source Backstage project has been adopted internally by some of the world’s most well-known companies, including LinkedIn, Twilio, American Airlines, Unity, Splunk, Ikea, HP and more than 3,000 organizations. But as with just about any open source project, the main issue with Backstage is the complexity involved in getting set up — lots of integrations, configurations and figuring out how it all glues together.
Thus, Spotify is now introducing an out-the-box version of the open source project called Spotify Portal, available in beta from today, which is pitched as a “full-featured, low-/no-code internal developer portal (IDP)” built atop Backstage.
Spotify Portal. Image Credits: Spotify
Spotify Portal ships with quick-start tools for connecting all their internal services and libraries, replete with setup wizard for installing Portal and connecting it with a company’s GitHub and cloud provider.
“When you set up your IDP, typically you need to ingest a lot of software into that, because the point of the IDP is to capture your full software catalogue and map that to the user base, and there’s potentially a lot of integrations involved in,” Tyson Singer, Spotify’s head of technology and platforms, explained to TechCrunch. “And so with Spotify Portal for Backstage, we’ve basically given folks a no-code way to do that.”
On the surface, this seems like some sort of SaaS play, similar to how a commercial company might offer a fully managed, hosted version of a popular open source product. But that isn’t quite what’s happening here — there is no hosted element to this, though that might change in the future. It’s what Singer calls “Backstage in a box,” one which is deployed within the customer’s own ecosystem either on-premises, or in their own cloud.
“It’s the customer who manages it,” Singer said. “What’s important from our perspective is that we’ve really focused on both reducing the startup time and the maintenance time. So that means not only is the setup and the onboarding ‘no-code,’ it’s also the maintenance where we’re reducing code. That really makes it quite easy to manage in your own particular context.”
However, in a follow-up question, a Spotify spokesperson clarified that Spotify Portal for Backstage is its “first step towards a managed product,” which means that it more than likely will be offered more like a SaaS service in the future. “We’ve seen a growing appetite for a more managed product that would allow us to share our expertise more directly with companies, and we want to be able to offer more in support of that need,” the spokesperson said. “Portal is our first step on that journey, but in the future, we’re going to expand our offerings as managed.”
In addition, Spotify is adding various enterprise support and services to the mix, which it says it has already been providing since last summer but hasn’t disclosed this until now. This includes one-on-one tech support from dedicated Backstage personnel at Spotify, and includes service-level agreements (SLAs), security reviews and incident notifications. And for those wanting to get up-and-running with Backstage in the first instance, Spotify is also offering consulting services.
Spooling up
In essence, Spotify is now catering to three broad category of users: the core open source project for those with the resources and technical nous to self-deploy everything; the “hybrid adopters,” which is what Spotify calls those that have some of the necessary skills but need some support along the way; and the businesses that need something a bit more oven-baked — which is where Spotify Portal enters the fray.
Similar to the pricing structure for its existing plugin subscriptions, which are charged based on “individual customer parameters” such as usage and capacity, the new Portal and enterprise services don’t come with up-front costs.
“For pricing, we are referring customers back to our sales organization,” Singer said. “It’s custom pricing.”
Given this transition to an enterprise-focused developer tools company, Spotify is also having to staff-up accordingly, though Singer wouldn’t share how many people it would be hiring or allocating to these new support roles.
“We are changing how we go forward with both our sales organization and support,” Singer said. “So we’re shifting more focus towards how can we support customers in their initial journey and then also, once they’ve got it set up, their ongoing journey because we do want to be able to support them to get to value as quickly as possible.”
All this, it seems, is just the tip of the iceberg as far as Spotify’s developer tooling shift is concerned. The company is adding new features to some of its existing premium plug-ins, and it’s adding more plug-ins to the mix, too. One of these is the “data experience” plug-in, which makes it easier to add individual data entities to a software catalog — this includes built-in “ingestors” to scoop metadata from external data platforms, and make this available across Backstage.
Last year, Spotify also teased a totally separate product for software development teams called Confidence, which is like an A/B experimentation platform based on one of its own internal tools. For now, that remains a beta product, but Singer says that it’s “all systems go” as it readies things for prime-time in the future.
“We are super happy with the feedback that we’ve been getting from our [Confidence] beta customers so far,” Singer said. “We built out an experimentation platform that is broad and deep, covering a tremendous amount of use cases covering everything from your typical A/B testing on a user surface, to being able to do that across all of our ML [machine learning] use cases. And I think that really sets it aside, as more and more companies are using ML in the same sorts of ways that we are to optimize things.“
Google’s gunning for OpenAI’s Sora with Veo, an AI model that can create 1080p video clips around a minute long given a text prompt.
Unveiled on Tuesday at Google’s I/O 2024 developer conference, Veo can capture different visual and cinematic styles, including shots of landscapes and time lapses, and make edits and adjustments to already generated footage.
“We’re exploring features like storyboarding and generating longer scenes to see what Veo can do,” Demis Hassabis, head of Google’s AI R&D lab DeepMind, told reporters during a virtual roundtable. “We’ve made incredible progress on video.”
Image Credits: Google
Veo builds on Google’s preliminary commercial work in video generation, previewed in April, which tapped the company’s Imagen 2 family of image-generating models to create looping video clips.
But unlike the Imagen 2-based tool, which could only create low-resolution, few-seconds-long videos, Veo appears to be competitive with today’s leading video generation models — not only Sora, but models from startups like Pika, Runway and Irreverent Labs.
In a briefing, Douglas Eck, who leads research efforts at DeepMind in generative media, showed me some cherry-picked examples of what Veo can do. One in particular — an aerial view of a bustling beach — demonstrated Veo’s strengths over rival video models, he said.
“The detail of all the swimmers on the beach has proven to be hard for both image and video generation models — having that many moving characters,” he said. “If you look closely, the surf looks pretty good. And the sense of the prompt word ‘bustling,’ I would argue, is captured with all the people — the lively beachfront filled with sunbathers.”
Image Credits: Google
Veo was trained on lots of footage. That’s generally how it works with generative AI models: Fed example after example of some form of data, the models pick up on patterns in the data that enable them to generate new data — videos, in Veo’s case.
Where did the footage to train Veo come from? Eck wouldn’t say precisely, but he did admit that some might’ve been sourced from Google’s own YouTube.
“Google models may be trained on some YouTube content, but always in accordance with our agreement with YouTube creators,” he said.
The “agreement” part may technically be true. But it’s also true that, considering YouTube’s network effects, creators don’t have much choice but to play by Google’s rules if they hope to reach the widest possible audience.
Image Credits: Google
Reporting by The New York Times in April revealed that Google broadened its terms of service last year in part to allow the company to tap more data to train its AI models. Under the old ToS, it wasn’t clear whether Google could use YouTube data to build products beyond the video platform. Not so under the new terms, which loosen the reins considerably.
Google’s far from the only tech giant leveraging vast amounts of user data to train in-house models. (See: Meta.) But what’s sure to disappoint some creators is Eck’s insistence that Google’s setting the “gold standard,” here, ethics-wise.
“The solution to this [training data] challenge will be found with getting all of the stakeholders together to figure out what are the next steps,” he said. “Until we make those steps with the stakeholders — we’re talking about the film industry, the music industry, artists themselves — we won’t move fast.”
Yet Google’s already made Veo available to select creators, including Donald Glover (AKA Childish Gambino) and his creative agency Gilga. (Like OpenAI with Sora, Google’s positioning Veo as a tool for creatives.)
Eck noted that Google provides tools to allow webmasters to prevent the company’s bots from scraping training data from their websites. But the settings don’t apply to YouTube. And Google, unlike some of its rivals, doesn’t offer a mechanism to let creators remove their work from its training data sets post-scraping.
I asked Eck about regurgitation, as well, which in the generative AI context refers to when a model generates a mirror copy of a training example. Tools like Midjourney have been found to spit out exact stills from movies including “Dune,” “Avengers” and “Star Wars” provided a time stamp — laying a potential legal minefield for users. OpenAI has reportedly gone so far as to block trademarks and creators’ names in prompts for Sora to try to deflect copyright challenges.
So what steps did Google take to mitigate the risk of regurgitation with Veo? Eck didn’t have an answer, short of saying the research team implemented filters for violent and explicit content (so no porn) and is using DeepMind’s SynthID tech to mark videos from Veo as AI-generated.
Image Credits: Google
“We’re going to make a point of — for something as big as the Veo model — to gradually release it to a small set of stakeholders that we can work with very closely to understand the implications of the model, and only then fan out to a larger group,” he said.
Eck did have more to share on the model’s technical details.
Eck described Veo as “quite controllable” in the sense that the model understands camera movements and VFX reasonably well from prompts (think descriptors like “pan,” “zoom” and “explosion”). And, like Sora, Veo has somewhat of a grasp on physics — things like fluid dynamics and gravity — which contribute to the realism of the videos it generates.
Veo also supports masked editing for changes to specific areas of a video and can generate videos from a still image, a la generative models like Stability AI’s Stable Video. Perhaps most intriguing, given a sequence of prompts that together tell a story, Veo can generate longer videos — videos beyond a minute in length.
Image Credits: Google
That’s not to suggest Veo’s perfect. Reflecting the limitations of today’s generative AI, objects in Veo’s videos disappear and reappear without much explanation or consistency. And Veo gets its physics wrong often — for example, cars will inexplicably, impossibly reverse on a dime.
That’s why Veo will remain behind a waitlist on Google Labs, the company’s portal for experimental tech, for the foreseeable future, inside a new front end for generative AI video creation and editing called VideoFX. As it improves, Google aims to bring some of the model’s capabilities to YouTube Shorts and other products.
“This is very much a work in progress, very much experimental … there’s much more left undone than done here,” Eck said. “But I think this is sort of the raw materials for doing something really great in the filmmaking space.”
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