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Permira is taking Squarespace private in $6.6 billion deal | TechCrunch


Squarespace, a platform used by SMEs and individuals for building websites, blogs, and online stores, is going private in an all-cash deal that values the company on equity basis at $6.6 billion, or a $6.9 billion enterprise valuation. The acquiring company is U.K.-based private equity firm Permira. This is a breaking story, refresh for updates.

© 2024 TechCrunch. All rights reserved. For personal use only.


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Robotic Automations

Gratitude Plus makes social networking positive, private and personal | TechCrunch


Private social networking is making a comeback. Gratitude Plus, a startup that aims to shift social media in a more positive direction, is expanding its wellness-focused, personal reflections journal to include support for families who want to stay in touch even when physically distant.  The startup, whose name reflects its core offering of a gratitude […]

© 2024 TechCrunch. All rights reserved. For personal use only.


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Robotic Automations

NASA orders studies from private space companies on Mars mission support roles | TechCrunch


Mars exploration has been always been the exclusive purview of national space agencies, but NASA is trying to change that, awarding a dozen research tasks to private companies as a prelude to commercial support for future missions to the Red Planet.

It’s the second time in a month that the agency has shown its desire for commercial support in Mars missions, having more or less scrapped the original Mars Sample Return mission in favor of a to-be-determined alternative likely by private space companies.

A total of nine companies were selected to perform twelve “concept studies” on how they could provide Mars-related services, from payload delivery to planetary imaging to communications relays. While each award is relatively small — between $200,000 and $300,000 — these studies are an important first step for NASA to better understand the costs, risks, and feasibility of commercial technologies.

The companies selected are: Lockheed Martin, Impulse Space, and Firefly Aerospace for small payload delivery and hosting services; United Launch Alliance, Blue Origin, and Astrobotic for large payload delivery and hosting services; Albedo, Redwire Space, and Astrobotic for Mars surface-imaging services; and SpaceX, Lockheed Martin, and Blue Origin for next-gen relay series.

Nearly all the selected proposals would adapt existing projects focused on the moon and Earth, NASA said in a statement. The twelve-week studies will conclude in August, and there’s no guarantee that they would lead to future requests for proposals or contracts. That said, it’s similarly unlikely that future contracts would appear without a study having previously been done by a company vying for it.

The companies were sourced from a request for proposals put out by NASA’s Jet Propulsion Laboratory earlier this year. According to that solicitation, the idea is to develop a new paradigm for Mars exploration, one that delivers “more frequent lower cost missions” via partnerships between government and industry.

The plan is similar to the agency’s Commercial Lunar Payload Services program, which provides large contracts to private companies to deliver payloads to the moon. And like CLPS, which helped bankroll the first successful private lunar lander (among others), these latest awards also show that the agency is increasingly comfortable working with smaller, earlier-stage startups working on unproven tech.


Software Development in Sri Lanka

Robotic Automations

Thoma Bravo to take UK cybersecurity company Darktrace private in $5B deal | TechCrunch


Darktrace is set to go private in a deal that values the U.K.-based cybersecurity giant at around $5 billion.

A newly-formed entity called Luke Bidco Ltd, formed by private equity giant Thoma Bravo, has tabled an all-cash bid of £6.20 ($7.75) per share, which represents a 44% premium on its average price for the three-month period ending April 25. However, this premium drops to just 20 percent when juxtaposed against Darktrace’s closing price yesterday, as the company’s shares had risen 20% to £5.18 in the past month.

Founded out of Cambridge, U.K., in 2013, Darktrace is best known for AI-enabled threat detection smarts, using machine learning to identify abnormal network activity and attempts at ransomware attacks, insider attacks, data breaches, and more. The company claims big-name customers including Allianz, Airbus, and the City of Las Vegas.

After raising some $230 million in VC funding and hitting a private valuation of $1.65 billion, Darktrace went public on the London Stock Exchange in April, 2021, with an opening-day valuation of $2.4 billion. Its shares hit an all-time high later that year of £9.45, and plummeted to an all-time low of £2.29 last February. But they had been steadily rising since the turn of the year, and hadn’t fallen below £4 since the beginning of March.

The full valuation based on Thoma Bravo’s offer amounts to $5.3 billion (£4.25 billion) on what is known as a full-diluted basis, which takes into account all convertible securities and is designed to give a more comprehensive view of a company’s valuation. However, the enterprise value in this instance is approximately $4.9 billion (£4 billion), which includes additional considerations such as debt and cash positions.

Take-private

There has been a swathe of “take-private” deals of late, with Vista Equity this month announcing plans to acquire revenue optimization platform Model N in $1.25 billion deal — its fifth take-private deal in 18 months. And last month, Thoma Bravo revealed it was taking critical event management software company Everbridge private in $1.8 billion transaction.

In an investor relations’ document published today, Thoma Bravo said that iDarktrace represented an “attractive opportunity to increase its exposure” to the fast-growing cybersecurity market.

“Darktrace is at the very cutting edge of cybersecurity technology, and we have long been admirers of its platform and capability in artificial intelligence,” Thoma Bravo partner Andrew Almeida said. “The pace of innovation in cybersecurity is accelerating in response to cyber threats that are simultaneously complex, global and sophisticated.”

Separately, Darktrace said it had previously rebuffed approaches from Thoma Bravo on the grounds that the offers were too low — something that the duo have now clearly resolved with the amended bid.

“The proposed offer represents an attractive premium and an opportunity for shareholders to receive the certainty of a cash consideration at a fair value for their shares,” Darktrace chair Gordon Hurst said. “The proposed acquisition will provide Darktrace access to a strong financial partner in Thoma Bravo, with deep software sector expertise, who can enhance the company’s position as a best-in-class cyber AI business headquartered in the U.K.”

The deal is of course still subject to shareholder approval, but the companies said that they expect to complete the transaction by the end of 2024.


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Robotic Automations

Learn how to master cap table management with Fidelity Private Shares | TechCrunch


Are you gearing up to secure funding for your startup or maybe you’ve raised a little bit already? If so, ensuring your cap table and data room are pristine could be the difference between a smooth, swift raise and a drawn-out, costly process. At TechCrunch Early Stage 2024, join Fidelity Private Shares’ session, “Preparing to Raise: Cap Table Best Practices to Help You Close Fast” to gain invaluable insights from industry experts. This session promises to equip founders with the essential knowledge needed to navigate the fundraising landscape efficiently.

Attendees of this session will walk away with actionable guidance from three experts representing the legal, investor, and founder perspectives. Whether you’re a first-time founder or a seasoned entrepreneur, mastering cap table management is essential for a successful fundraising journey. Don’t miss this opportunity to learn from the best and streamline your path to funding success at TechCrunch Early Stage 2024.

Meet the speakers

Kristen Craft, vice president and business partner manager at Fidelity Private Shares, brings a wealth of experience from both sides of the startup equation. With her background as a founder and startup operator, Kristen understands the challenges firsthand. At Fidelity, she spearheads initiatives to support founders and investors with equity management tools, fundraising strategy, and go-to-market best practices.

Laura Stoffel, partner at Gunderson Dettmer, adds legal expertise to the discussion. As a seasoned attorney specializing in the innovation economy, Laura guides entrepreneurs through the complexities of forming and structuring businesses, securing financing, and executing M&A transactions. Her deep understanding of governance and venture financing matters makes her an invaluable resource for startups at every stage of growth.

Melissa Withers, founder and managing partner of RevUp Capital, rounds out the panel with her unique perspective on early-stage investing. A trailblazer in the field, Melissa pioneered revenue-based funding with RevUp, offering startups an alternative to traditional equity models. With a commitment to supporting diverse founders and fostering innovation, Melissa’s approach to investing is reshaping the landscape of startup finance.

What are you waiting for? Book your passes now before prices go up at the door.


Software Development in Sri Lanka

Robotic Automations

Vista Equity to take revenue optimization platform Model N private in $1.25B deal | TechCrunch


Model N, a platform used by companies such as Johnson & Johnson, AstraZeneca, and AMD to automate decisions related to pricing, incentives, and compliance, is going private in a $1.25 billion deal with private equity firm Vista Equity Partners. The acquisition underscores how PE firms continue to scoop up tech companies that have struggled to perform well in public markets in the last couple of years.

Vista Equity is doling out $30 per share in the all-cash transaction, representing a 12% premium on Friday’s closing price, and 16% on its 30-day average.

This is Vista Equity’s fifth such acquisition in the past 18 months, following Avalara ($8.4 billion); KnowBe4 ($4.6 billion); Duck Creek Technologies ($2.6 billion); and EngageSmart ($4 billion).

Founded in 1999, Model N’s software integrates with various data sources and internal systems to help companies analyze trends, pricing efficacy, market demand, and more. The platform is typically used in industries such as pharmaceuticals and life sciences, where there may be complex pricing structures, and where regulatory or market changes can impact business.

The San Mateo-headquartered company went public on the New York Stock Exchange (NYSE) in 2013, and it has generally performed well in the intervening years — particularly since around 2019, when its market cap steadily started to increase, hitting an all-time high of $1.6 billion last year. However, its valuation has generally hovered below the $1 billion market for the past six months, sparking Vista Equity Partners into action today.

Vista said that it expects the transaction to close in the middle of 2024, though it is of course subject to the usual conditions, including shareholder approval.


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Robotic Automations

'Reverse' searches: The sneaky ways that police tap tech companies for your private data | TechCrunch


U.S. police departments are increasingly relying on a controversial surveillance practice to demand large amounts of users’ data from tech companies, with the aim of identifying criminal suspects.

So-called “reverse” searches allow law enforcement and federal agencies to force big tech companies, like Google, to turn over information from their vast stores of user data. These orders are not unique to Google — any company with access to user data can be compelled to turn it over — but the search giant has become one of the biggest recipients of police demands for access to its databases of users’ information.

For example, authorities can demand that a tech company turn over information about every person who was in a particular place at a certain time based on their phone’s location, or who searched for a specific keyword or query. Thanks to a recently disclosed court order, authorities have shown they are able to scoop up identifiable information on everyone who watched certain YouTube videos.

Reverse searches effectively cast a digital dragnet over a tech company’s store of user data to catch the information that police are looking for.

Civil liberties advocates have argued that these kinds of court-approved orders are overbroad and unconstitutional, as they can also compel companies to turn over information on entirely innocent people with no connection to the alleged crime. Critics fear that these court orders can allow police to prosecute people based on where they go or whatever they search the internet for.

So far, not even the courts can agree on whether these orders are constitutional, setting up a likely legal challenge before the U.S. Supreme Court.

In the meantime, federal investigators are already pushing this controversial legal practice further. In one recent case, prosecutors demanded that Google turn over information on everyone who accessed certain YouTube videos in an effort to track down a suspected money launderer.

A recently unsealed search application filed in a Kentucky federal court last year revealed that prosecutors wanted Google to “provide records and information associated with Google accounts or IP addresses accessing YouTube videos for a one week period, between January 1, 2023, and January 8, 2023.”

The search application said that as part of an undercover transaction, the suspected money launderer shared a YouTube link with investigators, and investigators sent back two more YouTube links. The three videos — which TechCrunch has seen and have nothing to do with money laundering — collectively racked up about 27,000 views at the time of the search application. Still, prosecutors sought an order compelling Google to share information about every person who watched those three YouTube videos during that week, likely in a bid to narrow down the list of individuals to their top suspect, who prosecutors presumed had visited some or all of the three videos.

This particular court order was easier for law enforcement to obtain than a traditional search warrant because it sought access to connection logs about who accessed the videos, rather than the higher-standard search warrant that courts can use to demand that tech companies turn over the contents of someone’s private messages.

The Kentucky federal court approved the search order under seal, blocking its public release for a year. Google was barred from disclosing the demand until last month when the court’s order expired. Forbes first reported on the existence of the court order.

It’s not known if Google complied with the order, and a Google spokesperson declined to say either way when asked by TechCrunch.

Riana Pfefferkorn, a research scholar at the Stanford Internet Observatory, said this was a “perfect example” why civil liberties advocates have long criticized this type of court order for its ability to grant police access to people’s intrusive information.

“The government is essentially dragooning YouTube into serving as a honeypot for the feds to ensnare a criminal suspect by triangulating on who’d viewed the videos in question during a specific time period,” said Pfefferkorn, speaking about the recent order targeting YouTube users. “But by asking for information on everyone who’d viewed any of the three videos, the investigation also sweeps in potentially dozens or hundreds of other people who are under no suspicion of wrongdoing, just like with reverse search warrants for geolocation.”

Demanding the digital haystack

Reverse search court orders and warrants are a problem largely of Google’s own making, in part thanks to the gargantuan amounts of user data that the tech giant has long collected on its users, like browsing histories, web searches and even granular location data. Realizing that tech giants hold huge amounts of users’ location data and search queries, law enforcement began succeeding in convincing courts into granting broader access to tech companies’ databases than just targeting individual users.

A court-authorized search order allows police to demand information from a tech or phone company about a person who investigators believe is involved in a crime that took place or is about to happen. But instead of trying to find their suspect by looking for a needle in a digital haystack, police are increasingly demanding large chunks of the haystack — even if that includes personal information on innocent people — to sift for clues.

Using this same technique as demanding identifying information of anyone who viewed YouTube videos, law enforcement can also demand that Google turn over data that identifies every person who was at a certain place and time, or every user who searched the internet for a specific query.

Geofence warrants, as they are more commonly known, allow police to draw a shape on a map around a crime scene or place of interest and demand huge swaths of location data from Google’s databases on anyone whose phone was in that area at a point in time.

Read more on TechCrunch

Police can also use so-called “keyword search” warrants that can identify every user who searched a keyword or search term within a time frame, typically to find clues about criminal suspects researching their would-be crimes ahead of time.

Both of these warrants can be effective because Google stores the granular location data and search queries of billions of people around the world.

Law enforcement might defend the surveillance-gathering technique for its uncanny ability to catch even the most elusive suspected criminals. But plenty of innocent people have been caught up in these investigative dragnets by mistake — in some cases as criminal suspects — simply by having phone data that appears to place them near the scene of an alleged crime.

Though Google’s practice of collecting as much data as it can on its users makes the company a prime target and a top recipient of reverse search warrants, it’s not the only company subject to these controversial court orders. Any tech company large or small that stores banks of readable user data can be compelled to turn it over to law enforcement. Microsoft, Snap, Uber and Yahoo (which owns TechCrunch) have all received reverse orders for user data.

Some companies choose not to store user data and others scramble the data so it can’t be accessed by anyone other than the user. That prevents companies from turning over access to data that they don’t have or cannot access — especially when laws change from one day to the next, such as when the U.S. Supreme Court overturned the constitutional right to access abortion.

Google, for its part, is putting a slow end to its ability to respond to geofence warrants, specifically by moving where it stores users’ location data. Instead of centralizing enormous amounts of users’ precise location histories on its servers, Google will soon start storing location data directly on users’ devices, so that police must seek the data from the device owner directly. Still, Google has so far left the door open to receiving search orders that seek information on users’ search queries and browsing history.

But as Google and others are finding out the hard way, the only way for companies to avoid turning over customer data is by not having it to begin with.


Software Development in Sri Lanka

Robotic Automations

OctoAI wants to make private AI model deployments easier with OctoStack | TechCrunch


OctoAI (formerly known as OctoML), announced the launch of OctoStack, its new end-to-end solution for deploying generative AI models in a company’s private cloud, be that on-premises or in a virtual private cloud from one of the major vendors, including AWS, Google, Microsoft and Azure, as well as CoreWeave, Lambda Labs, Snowflake and others.

In its early days, OctoAI focused almost exclusively on optimizing models to run more effectively. Based on the Apache TVM machine learning compiler framework, the company then launched its TVM-as-a-Service platform and, over time, expanded that into a fully fledged model-serving offering that combined its optimization chops with a DevOps platform. With the rise of generative AI, the team then launched the fully managed OctoAI platform to help its users serve and fine-tune existing models. OctoStack, at its core, is that OctoAI platform, but for private deployments.

Image Credits: OctoAI

OctoAI CEO and co-founder Luis Ceze told me the company has over 25,000 developers on the platform and hundreds of paying customers who use it in production. A lot of these companies, Ceze said, are GenAI-native companies. The market of traditional enterprises wanting to adopt generative AI is significantly larger, though, so it’s maybe no surprise that OctoAI is now going after them as well with OctoStack.

“One thing that became clear is that, as the enterprise market is going from experimentation last year to deployments, one, all of them are looking around because they’re nervous about sending data over an API,” Ceze said. “Two: a lot of them have also committed their own compute, so why am I going to buy an API when I already have my own compute? And three, no matter what certifications you get and how big of a name you have, they feel like their AI is precious like their data and they don’t want to send it over. So there’s this really clear need in the enterprise to have the deployment under your control.”

Ceze noted that the team had been building out the architecture to offer both its SaaS and hosted platform for a while now. And while the SaaS platform is optimized for Nvidia hardware, OctoStack can support a far wider range of hardware, including AMD GPUs and AWS’s Inferentia accelerator, which in turn makes the optimization challenge quite a bit harder (while also playing to OctoAI’s strengths).

Deploying OctoStack should be straightforward for most enterprises, as OctoAI delivers the platform with read-to-go containers and their associated Helm charts for deployments. For developers, the API remains the same, no matter whether they are targeting the SaaS product or OctoAI in their private cloud.

The canonical enterprise use case remains using text summarization and RAG to allow users to chat with their internal documents, but some companies are also fine-tuning these models on their internal code bases to run their own code generation models (similar to what GitHub now offers to Copilot Enterprise users).

For many enterprises, being able to do that in a secure environment that is strictly under their control is what now enables them to put these technologies into production for their employees and customers.

“For our performance- and security-sensitive use case, it is imperative that the models which process calls data run in an environment that offers flexibility, scale and security,” said Dali Kaafar, founder and CEO at Apate AI. “OctoStack lets us easily and efficiently run the customized models we need, within environments that we choose, and deliver the scale our customers require.”


Software Development in Sri Lanka

Robotic Automations

Canoo spent double its annual revenue on the CEO’s private jet in 2023 | TechCrunch


Tucked inside Canoo’s 2023 earnings report is a nugget regarding the use of CEO Tony Aquila’s private jet — just one of many expenses that illustrates the gap between spending and revenue at the EV startup.

Canoo posted Monday its fourth-quarter and full-year earnings for 2023 in a regulatory filing that shows a company burning through cash as it tries to scale up volume production of its commercial electric vehicles and avoid the same fate as other EV startups, like recently bankrupt Arrival. The regulatory filing once again contained a “going concern” warning — which has persisted since 2022 — as well as some progress on the expenses and revenue fronts.

The company generated $886,000 in revenue in 2023 compared to zero dollars in 2022, as the company delivered 22 vehicles to entities like NASA and the state of Oklahoma. And it did reduce its loss from operations by nearly half, from $506 million in 2022 to $267 million in 2023. The revenue-to-losses gap is still considerable though: The company reported total net losses of $302.6 million in 2023. 

Still, one only needs to look at what Canoo is paying to rent the CEO’s private jet to put those “wins” into perspective. Under a deal reached in November 2020, Canoo reimburses Aquila Family Ventures, an entity owned by the CEO, for use of an aircraft. In 2023, Canoo spent $1.7 million on this reimbursement — that’s double the amount of revenue it generated. Canoo paid Aquila Family Ventures $1.3 million in 2022 and $1.8 million in 2021 for use of the aircraft.

Separately, Canoo also paid Aquila Family Ventures $1.7 million in 2023, $1.1 million in 2022 and $500,000 in 2021 for shared services support in its Justin, Texas, corporate office facility, according to regulatory filings.

This could be chalked up to small monetary potatoes if Canoo reaches its revenue forecast for 2024 of $50 million to $100 million.

We’ve asked Canoo for comment and will update this post if we hear back.


Software Development in Sri Lanka

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