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Exclusive: Simbian brings AI to existing security tools


Ambuj Kumar is nothing if not ambitious.

An electrical engineer by training, Kumar led hardware design for eight years at Nvidia, helping to develop tech including a widely used high-speed memory controller for GPUs. After leaving Nvidia in 2010, Kumar pivoted to cybersecurity, eventually co-founding Fortanix, a cloud data security platform.

It was while heading up Fortanix that the idea for Kumar’s next venture came to him: an AI-powered tool to automate a company’s cybersecurity workflows, inspired by challenges he observed in the cybersecurity industry.

“Security leaders are stressed,” Kumar told TechCrunch. “CISOs don’t last more than a couple of years on average, and security analysts have some of the highest churn. And things are getting worse.”

Kumar’s solution, which he co-founded with former Twitter software engineer Alankrit Chona, is Simbian, a cybersecurity platform that effectively controls other cybersecurity platforms as well as security apps and tooling. Leveraging AI, Simbian can automatically orchestrate and operate existing security tools, finding the right configurations for each product by taking into account a company’s priorities and thresholds for security, informed by their business requirements.

With Simbian’s chatbot-like interface, users can type in a cybersecurity goal in natural language, then have Simbian provide personalized recommendations and generate what Kumar describes as “automated actions” to execute the actions (as best it can).

“Security companies have focused on making their own products better, which leads to a very fragmented industry,” Kumar said. “This results in a higher operational burden for organizations.”

To Kumar’s point, polls show that cybersecurity budgets are often wasted on an overabundance of tools. More than half of businesses feel that they’ve misspent around 50% of their budgets and still can’t remediate threats, according to one survey cited by Forbes. A separate study found that organizations now juggle on average 76 security tools, leading IT teams and leaders to feel overwhelmed.

“Security has been a cat-and-mouse game between attackers and defenders for a long time; the attack surface keeps growing due to IT growth,” Kumar said, adding that there’s “not enough talent to go around.” (One recent survey from Cybersecurity Ventures, a security-focused VC firm, estimates that the shortfall of cyber experts will reach 3.5 million people by 2025.)

In addition to automatically configuring a company’s security tools, the Simbian platform attempts to respond to “security events” by letting customers steer security while taking care of lower-level details. This, Kumar says, can significantly cut down on the number of alerts a security analyst must respond to.

But that assumes Simbian’s AI doesn’t make mistakes, a tall order, given that it’s well established that AI is error-prone.

To minimize the potential for off-the-rails behavior, Simbian’s AI was trained using a crowdsourcing approach — a game on its website called “Are you smarter than an LLM?” — that tasked volunteers with trying to “trick” the AI into doing the wrong thing. Kumar explained that Simbian used this learning, along with in-house researchers, to “ensure the AI does the right thing in its use cases.”

This means that Simbian effectively outsourced part of its AI training to unpaid gamers. But, to be fair, it’s unclear how many people actually played the company’s game; Kumar wouldn’t say.

There are privacy implications of a system that controls other systems, especially concerning those that are security-related. Would companies — and vendors, for that matter — be comfortable with sensitive data funneling through a single, AI-controlled centralized portal?

Kumar claims that every attempt has been made to protect against data compromise. Simbian uses encryption — customers control the encryption keys — and customers can delete their data at any time.

“As a customer, you have full control,” he said.

While Simbian isn’t the only platform to attempt to apply a layer of AI over existing security tools — Nexusflow offers a product along a similar vein — it appears to have won over investors. The company recently raised $10 million from investors including Coinbase board member Gokul Rajaram, Cota Capital partner Aditya Singh, Icon Ventures, Firebolt and Rain Capital.

“Cybersecurity is one of the most important problems of our time, and has famously fragmented ecosystem with thousands of vendors,” Rajaram told TechCrunch via email. “Companies have tried to build expertise around specific products and problems. I applaud Simbian’s method of building an integrated platform that would understand and operate all of security. While this is extremely challenging approach from technology perspective, I’ll put my money — and I did put my money — on Simbian. It’s the team with unique experience all the way from hardware to cloud.”

Mountain View-based Simbian, which has 15 employees, plans to put the bulk of the capital it’s raised toward product development. Kumar’s aiming to double the size of the startup’s workforce by the end of the year.


Software Development in Sri Lanka

Robotic Automations

Tesla Semi charging corridor project is still alive despite Biden admin funding snub | TechCrunch


Tesla is pushing forward with a plan to build an electric big rig charging corridor stretching from Texas to California, despite being snubbed by a lucrative federal funding program that’s part of Biden’s Bipartisan Infrastructure Law. But the original scope of the project could still change, TechCrunch has learned.

The company had been seeking nearly $100 million from the Charging and Fueling Infrastructure (CFI) Discretionary Grant program under the Federal Highway Administration (FHWA). Combined with around $24 million of its own money, Tesla wanted to build nine electric semi-truck charging stations between Laredo, Texas and Fremont, California.

The corridor, if built, would be a first-of-its-kind charging network that could enable both long-distance and regional electric trucking and help clean up a big chunk of the otherwise dirty transportation sector. Without it, though, Tesla’s promise to electrify heavy-duty trucking could fall even farther behind schedule than it already is.

The project as pitched to the FHWA was called TESSERACT, which stands for “Transport Electrification Supporting Semis Operating in Arizona, California, and Texas,” according to a slide buried in a 964-page filing with the South Coast Air Quality Management District. (Tesla collaborated with SCAQMD on the application.)

But Tesla was not among the 47 recipients that the Biden administration announced in January. Collectively, those winners received $623 million to build electric vehicle charging and refueling stations across the country. This is despite Tesla winning around 13% of all other charging awards so far from the Infrastructure Act, though that has only netted the company around $17 million.

Rohan Patel, who left his VP position at Tesla this week as the company laid off 10% of its workforce, said in a message to TechCrunch that Tesla may turn to state funding opportunities, or future rounds of the CFI program. Some of the sites along the route “are no-brainers even without funding,” he said.

Image Credits: TechCrunch

The 1,800-mile route would theoretically connect Tesla’s two North American vehicle factories, as well as one that is planned — but delayed — in Mexico. Each station was originally slated to be equipped with eight 750kW chargers for Tesla Semis, and four chargers open to other electric trucks. It’s unclear how effective it would be if the company was unable to build all nine stations, which are situated at roughly equal distances along the route.

About half of the Biden administration’s choices for the CFI funding focused on building out EV charging infrastructure in “urban and rural communities, including at convenient and high-use locations like schools, parks, libraries, multi-family housing, and more.”

The other half was dedicated to funding 11 “corridor” projects, including a number on the same I-10 corridor that makes up part of Tesla’s proposed route. That includes $70 million to the North Texas Council of Governments to build up to five hydrogen fueling stations for medium and heavy-duty trucks in the Dallas, Houston, Austin, and San Antonio areas.

“The project will help create a hydrogen corridor from southern California to Texas,” the Department of Transportation wrote in a statement in January.

“Funding hydrogen stations will go down as purely wasted money,” Patel told TechCrunch this week.

While he no longer speaks on behalf of Tesla, he also criticized funding hydrogen infrastructure when he was still with the company.

“Governments around the globe are wasting tax dollars on hydrogen for light/heavy duty infrastructure,” he wrote on X in February. “Like smoking, it’s never too late to quit.”

Funding isn’t the only challenge to the project. Another complicating factor could be Tesla’s recent restructuring.

Tesla CEO Elon Musk has said the company is now “balls to the wall for autonomy,” and has reportedly already sacrificed a planned low-cost EV in favor of making a purpose-built robotaxi the company’s priority. The Semi is years behind schedule, and Tesla has only built around 100 to date.

Despite all this, the Tesla Semi program is still slowly attracting customers. Just a few days after the restructuring, the head of the Semi program Dan Priestly announced via social media a new potential customer for the trucks. Priestly also said in March that Tesla has been using Semis to ship battery packs from Nevada to the Fremont factory.




Software Development in Sri Lanka

Robotic Automations

Orbex's new funding may accelerate its Prime microlauncher into orbit | TechCrunch


UK-based small launch developer Orbex got another boost from Scotland’s national bank and other investors as it gears up for its first orbital launch, though that mission still does not have a set date.

Founded in 2015, Orbex is one of a handful of firms racing to develop the next generation of European launch vehicles. These companies are looking to fill the massive gap left by the retirement of the Ariane 5 and major delays to the Ariane 6 and Vega C rockets; the absence of these vehicles means there is essentially zero native launch capacity coming out of Europe.

But the absence also means opportunity for Orbex. The company is developing what’s sometimes called a microlauncher: a two-stage vehicle called Prime that stands just 19 meters tall, designed to carry payloads up to 180 kilograms. The closest comparison is Rocket Lab’s Electron, which is a meter shorter but can carry up to 300 kilograms.

To Orbex, this small stature is a benefit, not a drawback, and Orbex CEO Philip Chambers told TechCrunch via email that the company is seeing “positive market conditions” for its product.

“We are seeing an exponential growth of satellites being launched into LEO and demand for launch is far exceeding supply – at the present time it’s not possible to launch a single kilogram from Europe and there is pent-up demand for sovereign launch capabilities,” he said. “We will offer freedom of action to European customers to be in control of their own launches and launch European Payloads from European soil.”

Prime will be launched from a new spaceport in Sutherland, northern Scotland, which is being constructed with the help of funding from UK’s national space agency. The aim is eventually to incorporate a patented recovery technology which the company calls REFLIGHT. This is an interstage structure that sits between the rocket stages; after the booster detaches, four ‘petals’ will fold out and, along with a parachute, create enough drag to enable a soft ocean splashdown.

A larger vehicle could eventually be in the plans as well, though Chambers was clear that Prime was the company’s first priority. However, he said that many of that rocket’s core technologies could scale to support larger payloads.

“The laws of physics dictate that if you want to compete on cost per kg you need to do this with larger vehicles, therefore, I think that it makes sense for Orbex to consider this.”

The company is kicking off its Series D with £16.7 million ($20.7 million) in fresh funding, with additional contributions from Octopus Ventures, BGF, Heartcore, EIFO and others. The new capital comes after Orbex closed a £40.4 million ($50 million) Series C in October 2022. While a spokesperson confirmed the new funding will “help Orbex ramp up the development of Prime … to ensure full readiness and scalability for its launch period,” a firm launch window has yet to be announced.


Software Development in Sri Lanka

Robotic Automations

Evolution Equity Partners raises $1.1B for new cybersecurity and AI fund | TechCrunch


Cybersecurity has had a rough go of it lately, with investment in the sector dropping a precipitous 40% compared to the year prior. But there’s promising early — if preliminary — signs of a recovery.

The vast majority of chief information security officers reported higher budgets for 2024, according to the cybersecurity-focused VC firm NightDragon. And, despite lower overall investment in the cybersecurity industry in Q1 2024, the number of deals increased compared to Q1 2023, per recruitment outfit Pinpoint.

It’s against this backdrop that Evolution Equity Partners, a growth capital investment firm based in NYC, today launched a $1.1 billion cybersecurity and AI fund, the third such fund in Evolution’s history.

The fund — Evolution Technology Fund III — was oversubscribed, with participation from existing and new endowments, sovereign investors, insurance companies, foundations, fund of funds, family offices and angels. It’ll pursue investments ranging from $20 million to $150 million in cybersecurity firms and startups leveraging machine learning and AI to build “market-leading” platforms, Richard Seewald, managing partner at Evolution and one of the firm’s founders, told TechCrunch.

“The Evolution Technology Fund III has already backed fifteen leading cybersecurity companies, initiating its investment period over 12 months ago,” Seewald said. “We expect to invest in a portfolio of up to thirty companies in the present fund. We’ll work with management teams and founders, providing them with support and insight in areas including sales and marketing, product technology, human capital, M&A and business development, really enabling them to excel.”

With Evolution Technology Fund III, Evolution’s strategy will be to reserve ~75% of the $1.1 billion total for early-growth-stage companies, ~15% for later-growth-stage startups and ~10% for earlier-stage VC tranches, with investments to be made not only in North America but in Europe and Israel — a hotspot for security tech.

“Our strategy is to invest that fund in a diversified portfolio across the different stages of maturity,” Seewald said. “We believe that provides private markets investors with diversified exposure to cybersecurity opportunities.”

ESG will be another factor, according to Seewald.

“Evolution is committed to integrating material environmental, social and governance (ESG) criteria in its investment processes and ownership practices,” he said. “We actively engage with our portfolio companies creating diverse boards and leadership teams bringing varied perspectives to decision-making processes, reducing the risk of groupthink and enhancing accountability.”

We’ll hold them to it.

Evolution, which has offices in Palo Alto, London and Zurich in addition to New York, was founded in 2008 by Seewald and Dennis Smith, who met while working together at the cybersecurity giant AVG (now owned by Avast). J.R. Smith and Karel Obluk — the former CEO and chief scientist at AVG, respectively — joined Seewald and Smith to start Evolution after AVG went public.

Evolution’s 30-person teams manages around $2 billion in assets and has backed 60 companies to date; its previous fund was $400 million. Among some of the firm’s more successful bets are Arctic Wolf (which is planning for an IPO), Talon Cyber (which is reportedly in negotiations with Palo Alto Networks for an M&A deal), Snyk, Aqua Security, SecurityScorecard and Carbon Black.


Software Development in Sri Lanka

Robotic Automations

GovDash aims to help businesses use AI to land government contracts | TechCrunch


Tim Goltser and Curtis Mason have been building things together since high school, when the two were the co-captains of their school’s robotics team. In college, Goltser and Mason teamed up to create an app — Hang, for scheduling hangouts with friends — with Sean Doherty, who Mason had met while an undergrad at Boston University.

Fast forward to 2022, and Goltser and Mason — along with Doherty — felt the entrepreneurial itch strike again. After considering a few ideas, they decided to go after what they saw as a largely unaddressed market: Tools to help small businesses secure U.S. government contracts.

“The federal contracting community has seen a shrinking of the small business industrial base for much of the past decade,” Doherty told TechCrunch. “It’s hard for these companies to compete against giants like Lockheed Martin or Northrop Grumman. It’s also expensive for them to bid on contracts — if they don’t win, they may run out of cash.”

As a result of labyrinthine systems and mountains of paperwork, finding and bidding for U.S. federal contracts is a laborious process. It takes weeks at a minimum to complete, according to Doherty — and often the best-resourced companies are the most successful.

In a 2023 survey from Setscale, a purchase order financing startup, small business owners cited insufficient cash flow and working capital — and a lack of time and resources — as their top roadblocks to securing government contracts.

To attempt to give these small businesses a boost, Goltser, Mason and Doherty founded GovDash, a platform that provides workflows to support government contract capture, proposal, development and management processes. GovDash was accepted to Y Combinator in 2022; Goltser dropped out of college to help spearhead it.

GovDash is essentially a contract proposal generator. The platform automatically finds contracts possibly relevant to a business, reads through the requests for proposals and — leveraging generative AI — writes proposals

GovDash can trawl through solicitation documents to identify requirements, requested formats, evaluation factors and submission schedules for contracts, Doherty says. It can also identify contracts a business might be qualified for based on their past performance, sending alerts to the inbox of a customer’s choosing, according to Doherty.

“When a contractor wants to respond to a government solicitation, they can run that through GovDash to produce a proposal in a fraction of the time,” Doherty said.

Now, generative AI makes mistakes. It’s a well-established fact. So why should businesses expect GovDash to be any different?

Two reasons, argues Doherty.

One, GovDash built a system that cross-checks a businesses’ info to see just how relevant the business is to a given federal contract. If the relevancy — as judged by the system — isn’t obvious, GovDash prompts the business to template out sections of the contract proposal with more information.

GovDash’s platform tries to automate many of the more tedious aspects of going after — and securing — U.S. federal contracts.

Two, GovDash involves heavy human review. At each stage of the proposal-generating process, the platform checks in with a human reviewer to get their seal of approval.

These steps — cross-checking and human review — aren’t infallible, Doherty admits. But he claims they’re better than what a lot of the competition’s doing.

“Companies now have one place where their business development data flows seamlessly, with an AI agent at its core to automate tedious workflows,” Doherty said. “This is a huge win for the C-suite as they can get out more proposals, at a higher quality level, in a fraction of the time, and put all the associated workflows on autopilot.”

GovDash’s competition is growing — and quickly.

GovDash competes with Govly, whose platform lets companies assess, search and analyze government contracting requirements across disparate sources. A more recent rival, Hazel, aims to use AI to automate government contracting discovery, drafting and compliance. Both — like GovDash — are Y Combinator-backed, interestingly.

But Doherty claims that GovDash is positioned well for expansion.

Having raised $12 million from investors including Northzone and Y Combinator, inclusive of a $10 million Series A funding tranche this month, GovDash plans to grow its engineering team, hire additional federal proposal managers to guide its product efforts and add new capabilities to its existing platform.

New York-based, six-employee GovDash currently works with around 30 federal contractors across the U.S., Doherty said, and is “nearly” cash-flow positive.

“We’re building for the long term for our customer base,” Doherty said. “[We’re] well-capitalized for eventual market tailwinds.”


Software Development in Sri Lanka

Robotic Automations

Apple lawsuit behind it, chip startup Rivos plots its next moves | TechCrunch


Rivos made headlines in 2022 after Apple filed a trade secrets suit against it, which accused Rivos of hiring away dozens of Apple engineers and using confidential info to develop chips to rival the iPhone maker’s own.

Rivos denied the allegations and countersued Apple for unfair competition. Apple ended up settling its lawsuit in February. Around the same time, it ended separate litigation with several of the Apple engineers Rivos had hired.

Now, with the courtroom drama behind it, Rivos is redoubling its efforts to bring its chipset tech to market, CEO Puneet Kumar told TechCrunch.

“Rivos was founded with the mission of building industry-leading power-efficient, high-performance chips,” Kumar said. “We’re excited to be targeting customers who are building data driven solutions.”

A substantial new funding tranche will help to finance those efforts.

Rivos on Tuesday announced that it raised over $250 million in an oversubscribed, extended Series A led by Matrix Capital Management with participation from chip giants including Intel (via its corporate VC division) and MediaTek. Other backers included Cambium Capital, Hotung Venture Group, Walden Catalyst, Dell Technologies Capital and Koch Disruptive Technologies.

It’s quite the turnaround for Rivos, which was founded in 2021 and roughly a year ago was struggling to raise funds from investors and recruit employees under the shadow of the Apple suit. In August, Rivos laid off nearly two dozen employees, or 6% of its workforce at the time, and was forced to delay a planned $400 billion Series A fundraising round, The Information reported at the time.

A custom server chip

The long-term goal with Rivos, Kumar said, is to build chips primarily for servers that can handle intensive data analytics and AI workloads, including generative AI workloads.

“We’re targeting customers building data-driven solutions, e.g., those utilizing generative AI and data analytics to drive decisions,” Kumar said. “There’re many companies targeting such markets; Rivos supports the intense hardware requirements of the AI models and analytics that will remake the enterprise.”

Rivos’ first chipset is built on RISC-V, the open standard instruction set architecture (ISA).

ISAs are a technical spec at the foundation of every chip, describing how software controls the chip’s hardware. For general-purpose computing, chip design teams typically license an existing ISA from an incumbent (e.g. Arm or Intel). But RISC-V presents an open, no-royalties-attached alternative.

Rivos’ chip features what Kumar describes as a “data parallel accelerator” to speed up AI- and big data-related computations, essentially a GPU designed for purposes beyond graphics processing. It was made using TSMC’s 3nm fabrication process. In chip manufacturing, “process” refers to the size of the smallest component that can be embedded on a chip.

That 3nm is considered close to the cutting edge. While Qualcomm, MediaTek, Nvidia and AMD among others are expected to employ TSMC’s process for their upcoming chip families, Apple was the only company to use it in 2024 in its M3 chipset series.

In addition to building the chip, Rivos is working on self-contained data center hardware based on the Open Compute Project modular standard, which will effectively serve as plug-and-play chip housing. And it’s creating a “firmware-to-app” software stack for programming the chip, Kumar said.

“Customer workloads can be easily deployed on our more efficient hardware, but still using their existing models and databases, giving them an immediate benefit,” Kumar added.

Rivos, which is pre-revenue at the moment, plans to make money by charging customers — chiefly large data center operators — for its hardware and complementary software solutions. David Goel, an early investor, said that Rivos’ “low-friction” adoption pipeline is a key differentiator in the cutthroat chip market.

“The Rivos team has adeptly integrated the groundbreaking new RISC-V architecture with an inventive accelerator, effectively bringing this vision to life,” Goel told TechCrunch. “Their prototype chip serves as a compelling demonstration of their unique capability.”

But is it differentiating enough?

Stiff competition

One of Rivos’ potential customer segments,  big tech firms, are racing to develop their own in-house chips for AI and big data analytics as the generative AI boom continues.

Google’s on its fifth-gen TPU and recently revealed Axion, its first dedicated chip for running models. Amazon has several custom chip families under its belt. Microsoft last year jumped into the fray with the Azure Maia AI Accelerator and the Azure Cobalt 100 CPU. And Meta’s inching along with its own designs.

Startups by the dozens, meanwhile, are angling for a slice of a custom data center chip market that could reach $10 billion this year and double by 2025.

Groq, a company developing chips to run AI models faster than conventional hardware, recently formed a new business unit geared toward enterprise applications and use cases. AI hardware startup Tenstorrent, helmed by engineering luminary Jim Keller, is looking to build its chipsets into data centers. And Rebellions, a South Korean fabless AI chip firm, has raised hundreds of millions of dollars in capital to ramp up production of its data center-focused chip, Atom.

But Nvidia, the dominant force in chips right now, is proving to be a tough one to topple.

Nvidia briefly became a $2 trillion company this year, riding high on the demand for its GPUs for AI training. Wells Fargo Equity Research estimates that Nvidia has a 98% market share in data center GPUs, and the company’s data center business was up more than 400% in Q4 2023 as Nvidia builds a new unit to design bespoke chips for cloud computing firms and others.

Given the fierceness of the competition — and the chilling effect Nvidia’s supremacy has had on funding for would-be rivals — it’s been rough going for some custom server chip upstarts.

Graphcore, which reportedly had its valuation slashed by $1 billion after a deal with Microsoft fell through, a few months ago said that it was planning job cuts due to the “extremely challenging” macroeconomic environment. Habana Labs, the Intel-owned AI chip company, laid off an estimated 10% of its workforce last year. Also last year, SiFive — like Rivos, a RISC-V startup — let go 20% of its workforce and discontinued its core product line.

So will Rivos fare better? Maybe.

Kumar wouldn’t talk about customers, and Rivos’ chip isn’t anticipated to reach mass production until sometime next year. But with 375 employees and hundreds of millions of dollars in the bank, Kumar said that Rivos is well-positioned to expand manufacturing and double down on platform and software engineering.

“The rapid changes in generative AI and the merger with the data analytics stack makes it vital that accelerators be easy to program and debug, and that data can seamlessly move between CPU and accelerator,” Kumar said. “Rivos addresses this need through our ‘recompile-not-redesign’ approach.”


Software Development in Sri Lanka

Robotic Automations

Draftboard lets companies list referral bonuses for anyone | TechCrunch


Companies that offer role referral bonuses do so with the assumption that their employees know their work culture — and a role’s requirements — best. But what if companies were to open up those referral bonuses to people outside the organization?

That’s the idea behind Draftboard, co-founded by Zach Roseman, the former CEO of mobile app dev group Mosaic. Draftboard lets employers post referral bonuses and have referrers compete to earn them by scouring their networks for talent.

“If you’re a large enterprise, you’re getting thousands of resumes per role you post,” Roseman told TechCrunch. “So you either have a massive talent team spending inordinate amounts of time poring through each one, or you’re spending six or seven figures a year on an AI screening solution that undoubtedly has big downsides, like privacy, bias, errors and so on.”

Draftboard is Roseman’s first project after Mosaic and IAC, the American holding company that owns a number of consumer brands including Allrecipes, Handy and Care.com. At IAC, Roseman was senior director of strategy and mergers and acquisitions, and frequently had to deal with finding the right fits for talent.

“The thought behind Draftboard was, why not leverage existing referral bonus programs and the power of a networked world to identify the best candidates?” Roseman said. “You get a much smaller, but much higher-quality, funnel of applicants — allowing you to hire faster.”

So how does Draftboard work?

Image Credits: Draftboard

Free for companies, Draftboard notifies its roughly 1,000 referrers — in Draftboard’s parlance, “scouts” — as referrals move through the different stages of companies’ recruiting processes. Referrers are graded on the quality of their referrals, and Draftboard takes a 20% cut of each referral bonus.

I asked how Draftboard found its initial group of referrers. Cold calling, Roseman replied.

“We started by putting out calls to our network — via WhatsApp groups, listservs, LinkedIn, etc. — for people who ran and owned tech communities,” he said. “I’d do discovery calls with them and ask them what their pain points were … On top of that, every time I had a call with a founder or talent person to try to get their company to list roles on Draftboard, it almost always ended up with them saying, ‘I know three people who would be great scouts — I’m going to ping them right now.’”

Aren’t there requirements to be a referrer? Not really, Roseman said — which might sound like a massive risk for companies to take. But he asserted that, in fact, it democratizes the process in a sort of meritocratic way.

“There aren’t requirements to be a referrer — and that’s by design,” Roseman said. “I thought, why not make the system data-driven and self-reinforcing? Companies set minimum scores; if your score is lower than their minimum, then you’re not allowed to send referrals to them anymore. So rather than us top-down policing who can and can’t be a referrer, we let the referrers moderate their own behavior in a bottoms-up way all by themselves.”

But, you might say, isn’t Draftboard essentially contracting out headhunting and recruiting without calling it that? Roseman claims this isn’t so — and that in fact many recruiters support the platform, which they use to run side hustles.

“Scouts run the gamut, from Substackers to recruiters to everyday employees at tech startups like Amazon, Spotify, Deel and TikTok,” Roseman said. “We think referrals can and should be open to everyone, not just company employees — as long as you can control for quality, which we do via our reputation score system.”

Image Credits: Draftboard

The business model certainly seems to be appealing to brands. Around 70 are on Draftboard today, including SeatGeek, Via and Formlabs.

It’s evidently intriguing to investors, too. Draftboard has raised $4.1 million from investors, including Founder Collective and Twelve Below, at a $13 million valuation.

“Job boards like LinkedIn, Indeed and ZipRecruiter exist to connect job seekers and companies, which results in some funky incentives and selection bias,” Roseman said. “We don’t do that. Instead, we connect referrers with companies, and those referrers bring the talent — whether they’re active job seekers or simply open to opportunities passively.”

New York-based Draftboard, which has 10 employees, plans to spend the bulk of its early capital on hiring and growing both sides of its marketplace — referrers and companies.


Software Development in Sri Lanka

Robotic Automations

Varda Space's orbital drug factory success fuels $90M in new funding | TechCrunch


Varda Space Industries has closed a massive tranche of funding just weeks after its first drug manufacturing capsule returned from orbit.

The company’s $90 million Series B round marks an inflection point for the company, which is now gearing up to scale from the initial demonstration mission to a regular set of missions carrying customer payloads, Varda founder Delian Asparouhov told TechCrunch.

El Segundo-based Varda was founded in 2021 by Asparouhov, who is also a partner at Founders Fund, and Will Bruey, a spacecraft engineer who cut his teeth at SpaceX. The pair had an audacious goal to commercialize what until very recently was promising but ultimately small-scale research into the effects of microgravity on pharmaceutical crystals.

Indeed, Varda’s first mission, which returned to Earth in February after 10 months in orbit, does not mark the first time a drug has been crystallized in microgravity. Astronauts have been conducting protein crystallization experiments in space for decades on the International Space Station and before that, the Space Shuttle.

But the business case for expanding this research has never materialized — until now. This is for a few different reasons, Asparouhov explained: because of the crew, there are significant limitations to the types of solvents or other materials you can bring onboard the ISS; there are constraints related to intellectual property for work that happens on the station; and pharmaceutical lab equipment designed for use in-space was generally lacking in sophistication compared to the terrestrial versions.

But much has changed, especially in the space industry. Part of the reason Varda is possible today is due to the availability of regular, low-cost rideshare launches from SpaceX and Rocket Lab’s innovations in satellite bus manufacturing. Even beyond these external partnerships, the startup has made significant headway in its own right, as the success of the first mission showed: Their reentry capsule appears to have performed flawlessly and the experiment to reformulate the HIV medicine ritonavir was executed without a hitch, it says.

Varda has also started publishing the results of its internal R&D efforts, including a scientific paper on its hyper-gravity (as opposed to microgravity) crystallization platform, which the startup developed as a sort of screening method prior to sending drugs to space. It’s an entirely new field of research that takes advantage of the ability to truly unlock gravity as a variable in scientific experiments.

“Over time, we will be able to generate data sets between both hyper-gravity and microgravity and start to show correlations,” he said. “As Varda flies more and more, we are confident that we will start to be able to develop systems of thinking where, for patterns of particular types of chemical systems, hyper-gravity will be used as a way to determine the correlation between, ultimately, microgravity and the drug performance.”

There’s still lots of work ahead. While engineers will study this first spacecraft, called Winnebago, to understand the wear and tear on the vehicle, the company as a whole will focus more on cadence before reusability, he said.

“If you just amortize the total cost to operate the business, we have so much more to gain by initially increasing cadence of flights before we really started to go for reusability. In some ways, it’s like we need to get to a once-a-month cadence before reusability is actually the biggest lever for us.”   

Varda does aim to significantly drive down mission costs by refurbishing and reusing the Winnebago capsules, as SpaceX does with its Dragon capsule, but Asparouhov said that won’t happen until later in the decade, around 2027. (In a recent podcast appearance, he specified that the all-in initial mission cost around $12 million, which will drop to $5-6 million by mission 4 and $2.5 million or less by mission 10.) Larger capsules are also in the longer-term pipeline, though also not until the 2027 time frame.

Asparouhov also confirmed that pharmaceuticals will be Varda’s sole focus for the next 10-20 (or more) years, based on the company’s conviction that pharmaceutical products will generate more economic value compared to other materials. A lot of that comes down to the fact that there are a significant set of drugs that require only a “seed” of the material that can only be made in microgravity, and the rest of the drug formulation can be completed here on Earth. That means the product is high revenue but low mass.

The company is also aiming to improve the processing capabilities of the on-board pharmaceutical reactor. The first mission carried just one drug protein, but in the future the company hopes to process multiple drug products that could be run through different processing regimes. In the future, other missions could carry larger reactors for drugs that do need more than the “seed” crystal, and those mission profiles would be closer to something like mass manufacturing.

Varda has “a handful” of signed contracts with publicly traded biotech companies, and the next three missions already manifested with Rocket Lab, which provided the spacecraft bus for mission 1. The startup’s next manufacturing mission will launch later this year, and the team plans to land that spacecraft in Australia.

The new financing was led by Caffeinated Capital, with participation from Lux Capital, General Catalyst, Founders Fund and Khosla Ventures. Varda has now raised $145 million to date.


Software Development in Sri Lanka

Robotic Automations

Investors are growing increasingly wary of AI | TechCrunch


After years of easy money, the AI industry is facing a reckoning.

A new report from Stanford’s Institute for Human-Centered Artificial Intelligence (HAI), which studies AI trends, found that global investment in AI fell for the second year in a row in 2023.

Both private investment — that is, investments in startups from VCs — and corporate investment — mergers and acquisitions — in the AI industry were on the downswing in 2023 versus the year prior, according to the report, which cites data from market intelligence firm Quid.

AI-related mergers and acquisitions fell from $117.16 million in 2022 to $80.61 million in 2023, down 31.2%; private investment dipped from $103.4 million to $95.99 million. Factoring in minority stake deals and public offerings, total investment in AI dropped to $189.2 billion last year, a 20% decline compared to 2022.

Yet some AI ventures continue to attract substantial tranches, like Anthropic’s recent multibillion-dollar investment from Amazon and Microsoft’s $650 million acquisition of Inflection AI. And more AI companies are receiving investments than ever before, with 1,812 AI startups announcing funding in 2023, up 40.6% versus 2022, according to the Stanford HAI report.

So what’s going on?

Gartner analyst John-David Lovelock says that he sees AI investing “spreading out” as the largest players — Anthropic, OpenAI and so on — stake out their ground.

“The count of billion-dollar investments has slowed and is all but over,” Lovelock told TechCrunch. “Large AI models require massive investments. The market is now more influenced by the tech companies that’ll utilize existing AI products, services and offerings to build new offerings.”

Umesh Padval, managing director at Thomvest Ventures, attributes the shrinking overall investment in AI to slower-than-expected growth. The initial wave of enthusiasm has given way to the reality, he says: that AI is beset with challenges — some technical, some go-to-market — that’ll take years to address and fully overcome.

“The deceleration in AI investing reflects the recognition that we’re still navigating the early phases of the AI evolution and its practical implementation across industries,” Padval said. “While the long-term market potential remains immense, the initial exuberance has been tempered by the complexities and challenges of scaling AI technologies in real-world applications … This suggests a more mature and discerning investment landscape.”

Other factors could be afoot.

Greylock partner Seth Rosenberg contends that there’s simply less appetite to fund “a bunch of new players” in the AI space.

“We saw a lot of investment in foundation models during the early part of this cycle, which are very capital intensive,” he said. “Capital required for AI applications and agents is lower than other parts of the stack, which may be why funding on an absolute dollar basis is down.”

Aaron Fleishman, partner at Tola Capital, says that investors might be coming to the realization that they’ve been too reliant on “projected exponential growth” to justify AI startups’ sky-high valuations. To give one example, AI company Stability AI, which was valued at over $1 billion in late 2022, reportedly brought in just $11 million in revenue in 2023 while spending $153 million on operating expenses.

“The performance trajectories of companies like Stability AI might hint at challenges looming ahead,” Fleishman said. “There’s been a more deliberate approach by investors in evaluating AI investments compared to a year ago. The rapid rise and fall of certain marquee name startups in AI over the past year has illustrated the need for investors to refine and sharpen their view and understanding of the AI value chain and defensibility within the stack.”

“Deliberate” seems to be the name of the game now, indeed.

According to a PitchBook report compiled for TechCrunch, VCs invested $25.87 billion globally in AI startups in Q1 2024, up from $21.69 billion in Q1 2023. But the Q1 2024 investments spanned across only 1,545 deals compared to 1,909 in Q1 2023. Mergers and acquisitions, meanwhile, slowed from 195 in Q1 2023 to 176 in Q1 2024.

Despite the general malaise within AI investor circles, generative AI — AI that creates new content, such as text, images, music and videos — remains a bright spot.

Funding for generative AI startups reached $25.2 billion in 2023, per the Stanford HAI report, nearly ninefold the investment in 2022 and about 30 times the amount from 2019. And generative AI accounted for over a quarter of all AI-related investments in 2023.

Samir Kumar, co-founder of Touring Capital, doesn’t think that the boom times will last, however. “We’ll soon be evaluating whether generative AI delivers the promised efficiency gains at scale and drives top-line growth through AI-integrated products and services,” Kumar said. “If these anticipated milestones aren’t met and we remain primarily in an experimental phase, revenues from ‘experimental run rates’ might not transition into sustainable annual recurring revenue.”

To Kumar’s point, several high-profile VCs including Meritch Capital — whose bets include Facebook and Salesforce — TCV, General Atlantic and Blackstone have steered clear of generative AI so far. And generative AI’s largest customers, corporations, seem increasingly skeptical of the tech’s promises,  and whether it can deliver on them.

In a pair of recent surveys from Boston Consulting Group, about half of the respondents — all C-suite executives — said that they don’t expect generative AI to bring about substantial productivity gains and that they’re worried about the potential for mistakes and data compromises arising from generative AI-powered tools.

But whether skepticism, and the financial downtrends that can stem from it, are a bad thing depends on your point of view.

For Padval’s part, he sees the AI industry undergoing a “necessary” correction to “bubble-like investment fervor.” And, in his belief, there’s light at the end of the tunnel.

“We’re moving to a more sustainable and normalized pace in 2024,” he said. “We anticipate this stable investment rhythm to persist throughout the remainder of this year … While there may be periodic adjustments in investment pace, the overall trajectory for AI investment remains robust and poised for sustained growth.”

We shall see.


Software Development in Sri Lanka

Robotic Automations

ShareChat's valuation drops below $2 billion in new funding | TechCrunch


Social media startup ShareChat’s valuation has cratered below $2 billion from nearly $5 billion in a new funding round, a source familiar with the situation told TechCrunch, marking a steep decline for the nine-year-old Indian startup that boasts over 400 million users in the South Asian market.

The Bengaluru-based startup, which operates a popular social network supporting a dozen Indian languages as well as a short-form video app, announced on Monday that it had raised $49 million in a convertible round. It did not disclose the valuation at which the funds were raised but strongly denied that its new valuation was below $2 billion, asserting there was “no valuation” attached to the round.

Existing investors including Lightspeed, Temasek, Alkeon Capital, Moore Strategic Ventures and HarbourVest have invested in the new round, the startup said. Their debt will convert to equity at a valuation below $2 billion in the next round, according to a source with direct knowledge of the terms. The source requested anonymity to speak candidly. TechCrunch reported in December that ShareChat was facing a steep valuation cut.

ShareChat also counts Google, X, Snap, Tiger Global and Tencent among its backers. It has raised about $1.75 billion to date. ShareChat was valued at $4.9 billion in a funding round it raised in mid-2022.

The markdown comes despite ShareChat experiencing a remarkably positive year, aggressively cutting expenses while managing to double its revenue. “When the market turned, we had to temper [acquisitions and creator payments] and move towards more profitable growth,” Ankush Sachdeva, ShareChat’s co-founder and chief executive, told TechCrunch in an interview.

ShareChat has not spent money acquiring users in the past year, with Sachdeva crediting improvements to the startup’s content recommendation engine for driving user retention and engagement. The company has also invested heavily in AI talent, particularly for senior roles in its London-based team. ShareChat also unveiled that it has doubled the ESOP grant for each employee in the firm as part of a special bonus grant.

It has also been able to pare down its single-largest expense, the cost to serve content, he said. “When you fetch content on one of our apps, we do a lot of computation to find the 10 best content. To serve and consume that, there is another delivery cost. Optimizing this has helped us lower our burn,” he said.

ShareChat has reduced its monthly cash burn by 90% over the past two years while doubling revenue, attracting large FMCG firms and gaming companies as advertisers.

The startup also remains committed to the short-video market in India, despite strong competition from YouTube and Instagram following the country’s ban on TikTok in 2020.

“In terms of traffic, ours is lower than those of Instagram and YouTube, but we are the largest in terms of a standalone app,” said Sachdeva. He believes ShareChat’s unique focus on live-streaming as a destination for entertainment and creator-user connections will differentiate it from American rivals. The startup acquired local rival MX TakaTak in a deal valued over $700 million in 2022.


Software Development in Sri Lanka

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