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For customer service, Ultimate.ai‘s thesis is it’s not humans or AI but humans and AI. The Helsinki- and Berlin-based startup has built an AI-powered suggestion engine that, once trained on clients’ data-sets, is able to provide real-time help to (human) staff dealing with customer queries via chat, email and social channels. So the AI layer is intended to make the humans behind the screens smarter and faster at responding to customer needs — as well as freeing them up from handling basic queries to focus on more complex issues.

AI-fuelled chatbots have fast become a very crowded market, with hundreds of so called ‘conversational AI’ startups all vying to serve the customer service cause.

Ultimate.ai stands out by merit of having focused on non-English language markets, says co-founder and CEO Reetu Kainulainen. This is a consequence of the business being founded in Finland, whose language belongs to a cluster of Eastern and Northern Eurasian languages that are plenty removed from English in sound and grammatical character.

“[We] started with one of the toughest languages in the world,” he tells TechCrunch. “With no available NLP [natural language processing] able to tackle Finnish, we had to build everything in house. To solve the problem, we leveraged state-of-the-art deep neural network technologies.

“Today, our proprietary deep learning algorithms enable us to learn the structure of any language by training on our clients’ customer service data. Core within this is our use of transfer learning, which we use to transfer knowledge between languages and customers, to provide a high-accuracy NLU engine. We grow more accurate the more clients we have and the more agents use our platform.”

Ultimate.ai was founded in November 2016 and launched its first product in summer 2017. It now has more than 25 enterprise clients, including the likes of Zalando, Telia and Finnair. It also touts partnerships with tech giants including SAP, Microsoft, Salesforce and Genesys — integrating with their Contact Center solutions.

“We partner with these players both technically (on client deployments) and commercially (via co-selling). We also list our solution on their Marketplaces,” he notes.

Up to taking in its first seed round now it had raised an angel round of €230k in March 2017, as well as relying on revenue generated by the product as soon as it launched.

The $1.3M seed round is co-led by Holtzbrinck Ventures and Maki.vc.

Kainulainen says one of the “key strengths” of Ultimate.ai’s approach to AI for text-based customer service touch-points is rapid set-up when it comes to ingesting a client’s historical customer logs to train the suggestion system.

“Our proprietary clustering algorithms automatically cluster our customer’s historical data (chat, email, knowledge base) to train our neural network. We can go from millions of lines of unstructured data into a trained deep neural network within a day,” he says.

“Alongside this, our state-of-the-art transfer learning algorithms can seed the AI with very limited data — we have deployed Contact Center automation for enterprise clients with as little as 500 lines of historical conversation.”

Ultimate.ai’s proprietary NLP achieves “state-of-the-art accuracy at 98.6%”, he claims.

It can also make use of what he dubs “semi-supervised learning” to further boost accuracy over time as agents use the tool.

“Finally, we leverage transfer learning to apply a single algorithmic model across all clients, scaling our learnings from client-to-client and constantly improving our solution,” he adds.

On the competitive front, it’s going up against the likes of IBM’s Watson AI. However Kainulainen argues that IBM’s manual tools — which he argues “require large onboarding projects and are limited in languages with no self-learning capabilities” — make that sort of manual approach to chatbot building “unsustainable in the long-term”.

He also contends that many rivals are saddled with “lengthy set-up and heavy maintenance requirements” which makes them “extortionately expensive”.

A closer competitor (in terms of approach) which he namechecks is TC Disrupt battlefield alum Digital Genius. But again they’ve got English language origins — so he flags that as a differentiating factor vs the proprietary NLP at the core of Ultimate.ai’s product (which he claims can handle any language).

“It is very difficult to scale out of English to other languages,” he argues. “It also uneconomical to rebuild your architecture to serve multi-language scenarios. Out of necessity, we have been language-agnostic since day one.”

“Our technology and team is tailored to the customer service problem; generic conversational AI tools cannot compete,” he adds. “Within this, we are a full package for enterprises. We provide a complete AI platform, from automation to augmentation, as well as omnichannel capabilities across Chat, Email and Social. Languages are also a key technical strength, enabling our clients to serve their customers wherever they may be.”

The multi-language architecture is not the only claimed differentiator, either.

Kainulainen points to the team’s mission as another key factor on that front, saying: “We want to transform how people work in customer service. It’s not about building a simple FAQ bot, it’s about deeply understanding how the division and the people work and building tools to empower them. For us, it’s not Superagent vs. Botman, it’s Superagent + Botman.”

So it’s not trying to suggest that AI should replace your entire customers service team but rather enhance your in house humans.

Asked what the AI can’t do well, he says this boils down to interactions that are transactional vs relational — with the former category meshing well with automation, but the latter (aka interactions that require emotional engagement and/or complex thought) definitely not something to attempt to automate away.

“Transactional cases are mechanical and AI is good at mechanical. The customer knows what they want (a specific query or action) and so can frame their request clearly. It’s a simple, in-and-out case. Full automation can be powerful here,” he says. “Relational cases are more frequent, more human and more complex. They can require empathy, persuasion and complex thought. Sometimes a customer doesn’t know what the problem is — “it’s just not working”.

“Other times are sales opportunities, which businesses definitely don’t want to automate away (AI isn’t great at persuasion). And some specific industries, e.g. emergency services, see the human response as so vital that they refuse automation entirely. In all of these situations, AI which augments people, rather than replaces, is most effective.

“We see work in customer service being transformed over the next decade. As automation of simple requests becomes the status-quo, businesses will increasingly differentiate through the quality of their human-touch. Customer service will become less labour intensive, higher skilled work. We try and imagine what tools will power this workforce of tomorrow and build them, today.”

On the ethics front, he says customers are always told when they are transferred to a human agent — though that agent will still be receiving AI support (i.e. in the form of suggested replies to help “bolster their speed and quality”) behind the scenes.

Ultimate.ai’s customers define cases they’d prefer an agent to handle — for instance where there may be a sales opportunity.

“In these cases, the AI may gather some pre-qualifying customer information to speed up the agent handle time. Human agents are also brought in for complex cases where the AI has had difficulty understanding the customer query, based on a set confidence threshold,” he adds.

Kainulainen says the seed funding will be used to enhance the scalability of the product, with investments going into its AI clustering system.

The team will also be targeting underserved language markets to chase scale — “focusing heavily on the Nordics and DACH [Germany, Austria, Switzerland]”.

“We are building out our teams across Berlin and Helsinki. We will be working closely with our partners – SAP, Microsoft, Salesforce and Genesys — to further this vision,” he adds. 

Commenting on the funding in a statement, Jasper Masemann, investment manager at Holtzbrinck Ventures, added: “The customer service industry is a huge market and one of the world’s largest employers. Ultimate.ai addresses the main industry challenges of inefficiency, quality control and high people turnover with latest advancements in deep learning and human machine hybrid models. The results and customer feedback are the best I have seen, which makes me very confident the team can become a forerunner in this space.”

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Divido, the consumer finance platform that lets you take out credit at the point of purchase to help spread the cost of buying new things, has raised $15 million in Series A funding.

Leading the round is Dawn Capital, and DN Capital, with participation from Mastercard, American Express Ventures and a number of previous investors. Renier Lemmens, who previously served as Chief Executive Officer of PayPal EMEA and was an executive at Barclays, has also been appointed as chairman.

Launched in late 2015, London-based Divido currently works with over 1,000 partners to enable them to offer B2C and B2B finance to their customers at checkout. This includes being able to spread the cost of any product or service over a period of time by providing instant access to credit at the point of purchase, either online and in-store.

However, where the company differentiates from the likes of Klarna is that Divido doesn’t provide the line of credit itself or work with a single lender, instead operating a marketplace model. This sees lenders compete to offer the most suitable credit.

The broader pitch is that Divido’s consumer finance at the point of sale leads to up to 20 percent more sales for retailers, more lending for banks and more transactions for payment partners. The company’s clients include Mercedes-Benz, BNP Paribas Shopify.

Explains Christer Holloman, CEO of Divido, in a statement: “Proactive retailers know they have to try new initiatives to grow sales. Offering customers the option to pay later doesn’t just increase footfall and eyeballs, but it also raises average order values and conversion rates. And what’s good for the retailers is also good for the lenders who are providing this credit, and the intermediaries that facilitate the transactions”.

Meanwhile, Divido says the injection of capital will be used for global expansion. The platform is currently available in the U.K., Germany, France, Spain, Italy, the Nordics, and the U.S., and the company wants to be in 10 more countries by the end of 2019. Divido is also pivoting to licence its platform to banks and lenders via a service called “Powered by Divido”. This will let partners white label its technology to provide finance services to their customers.

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Ola, the arch-rival of Uber in India, has raised $50 million at a valuation of about $4.3 billion from Sailing Capital, a Hong Kong-based private equity firm, and the China-Eurasian Economic Cooperation Fund (CEECF), a state-backed Chinese fund. The funding was disclosed in regulatory documents sourced by Paper.vc and reviewed by Indian financial publication Mint.

According to Mint, Sailing Capital and CEECF will hold a combined stake of more than 1% in Ola . An Ola spokesperson said the company has no comment.

Ola’s last funding announcement was in October, when it raised $1.1 billion (its largest funding round to date) from Tencent and returning investor SoftBank Group. Ola also said it planned to raise an additional $1 billion from other investors that would take the round’s final amount to about $2.1 billion.

At the time, a source with knowledge of the deal told TechCrunch that Ola was headed toward a post-money valuation of $7 billion once the $2.1 bllion raise was finalized. So while the funding from Sailing Capital and CEECF brings it closer to its funding goal, the latest valuation of $4.3 billion is still lower than the projected amount.

Ola needs plenty of cash to fuel its ambitious expansion both within and outside of India. In addition to ride hailing, Ola got back into the food delivery game at the end of last year by acquiring Foodpanda’s Indian operations to compete with UberEats, Swiggy, Zomato and Google’s Areo. It was a bold move to make as India’s food delivery industry consolidated, especially since Ola had previously launched a food delivery service that shut down after less than one year. To ensure the survival of Foodpanda, Ola poured $200 million into its new acquisition.

A few months later after buying Foodpanda, Ola announced the acquisition of public transportation ticketing startup Ridlr in an all-stock deal. Outside of India, Ola has been focused on a series of international launches. It announced today that it will begin operating in New Zealand, fast on the heels of launches in the United Kingdom and Australia (its first country outside of India) this year.

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Late last week, Congress moved one step closer to passing the American Innovation Act of 2018, a bill that would make accounting and tax changes that would likely increase the valuation of startups in an acquisition.

The House Ways and Means committee approved a bill containing text that would improve the treatment of Net Operating Losses (NOLs) for start-ups. While many startup founders would probably rather watch paint dry (or build their companies) than dive into complex tax code changes, the provisions in the bill could greatly improve the ability of start-ups to invest in growth activity, and could drive meaningfully positive impacts to valuations, acquisition prices, capital markets participation, and venture returns.

First, though, what are NOLs? Each year, if a company loses money, it can claim the losses as a deduction off of its future taxes. Traditionally, the U.S. tax code has allowed companies to cumulatively track and carry forward NOLs to offset taxable income in future years, reducing the amount of cash required to pay taxes. These NOLs are essentially a cash-like asset, and they can be exchanged in the event that a company is acquired.

However, a long-standing IRS provision, Section 382, which was originally implemented to prevent companies with large tax appetites from acquiring those with large operating losses exclusively to reduce taxes, limits the use of NOL carry-forwards in instances of ownership change. 

Currently, in cases of an ownership change, specified as a more than 50% change in the ownership of shareholders who own at least 5% of a company’s stock, the amount of taxable income for the “post-change” company that can be offset by existing NOLs cannot exceed the value of the “pre-change” company, multiplied by the long-term tax exempt rate set by the IRS.

(Yes, this is why you hire a tax attorney).

The net-net is that this provision has been particularly challenging for startups, which often trigger this limiting condition, given they frequently operate in the red through growth stages and often see frequent, sizable changes in their ownership structure due to fundraising, public offerings, and acquisitions.

The House bill would alleviate this complication by protecting these tax offsets and creating an exception to the section 382 provision for startups, allowing the application of NOLs and R&D tax credits realized in the first 3 years of operations regardless of ownership change limitations.

These changes have a number of benefits for startups. It would provide increased flexibility around early-stage financing activities and remove potential issues that could arise with capital markets activity. Additionally, with startups more easily maintaining tax offsets to reduce their cash taxes, startups would have larger cash balances to invest in growth efforts.

The protection of the NOL from ownership change limitations could also have serious impacts to company valuations and the attractiveness of startups as acquisition candidates. With acquirers better able to utilize existing tax offsets, startups should benefit from higher purchase prices from the inclusion of NOL balances in valuations, helping founder and VC returns.

The bill passed through committee through a voice vote with no objections and is now expected to be voted on by the rest of the House later this month before advancing to the Senate. The bill has 23 co-sponsors, all Republican.

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WHILL, the startup known for creating sleek, high-tech personal mobility devices, announced today that it has closed a $45 million Series C. The funding will be used for expanding into new international markets, as well as developing new products for large venues, including airports and “last-mile” sidewalk transportation. The round’s lead investors were SBI Investment, Daiwa Securities Group and WHIZ Partners, with participation from returning investors INCJ, Eight Road Ventures, MSIVC, Nippon Venture Capital, DG Incubation and Mizuho Capital.

This brings WHILL’s total funding so far to about $80 million. Founded in Tokyo in 2012, WHILL plans to open a branch in the European Union and enter 10 new European countries. It also plans to start working with partners on developing autonomous capabilities for its mobility devices, senior marketing manager Jeff Yoshioka told TechCrunch. The company will build its own sensors and cameras to use in its “mobility as a service” program, which allows users to control vehicles and call customer service through a mobile app.

One of WHILL’s biggest projects is developing an autonomous personal mobility device system for airports. Yoshioka says that an estimated 20 million people request wheelchairs in U.S. airports each year. This means they need to wait for an airline employee to bring a wheelchair to them and then push them from check-in to their gates. At the same time, it doesn’t give users a lot of flexibility.

The system that WHILL has in mind, on the other hand, would allow individuals to use an app to summon a mobility device over to them. Then they can go wherever they want — coffee shops, restrooms, shops — before heading to the gate without an assistant. Once they are done with the device, it will return to a docking station on its own. WHILL has already begun testing a similar program at Tokyo International Airport in partnership with Panasonic.

Yoshioka says WHILL will most likely pursue distribution partnerships with U.S. airlines, which are responsible for supplying and maintaining the wheelchair systems in American airports, and airports to build the necessary infrastructure.

Along with airports, WHILL wants to bring its technology to other large venues, including shopping malls and sports arenas, as well as create a system for last-mile transportation. Yoshioka notes that “there are already a lot of companies out there like LimeBike and MoBike that offer bikes and electric scooters, but there’s nothing out there for people with disabilities who can’t use those devices.”

Instead, many rely on Ubers or public transportation even for short distances. Like the airport system, WHILL’s last-mile sidewalk system will use autonomous electric vehicles that can be called to users with an app. It faces unique challenges, however, because WHILL’s devices are larger and more expensive than bikes or electric scooters, so the company needs to find safe places to dock them that are still accessible to people with limited mobility. Yoshioka says WHILL likely will focus on partnering with commercial properties to create indoor docking stations.

WHILL’s largest market is still Japan, where it has between 4,000 to 5,000 resellers. In its home market, WHILL’s devices are subsidized by the government and also available for rent. In the U.S., however, many customers need to purchase devices out-of-pocket. To make their products more accessible, WHILL launched the less expensive Model Ci (called the Model C in Europe and Japan) earlier this year. While there is still plenty of room for innovation in the wheelchair market, the Model Ci and other WHILL products compete with devices like the iBot, which can climb stairs, and the Trackchair, designed for off-road use. WHILL’s current products can’t climb stairs, but they do have the advantage of being designed for both indoor and outdoor use, giving users more flexibility, says Yoshioka.

The company also expects demand for its products to grow thanks to a rapidly aging world population, citing statistics that show there are expected to be more than 2.1 billion people over the age of 60 by 2050, up from about 900 million last year.

“We don’t necessarily see [the other companies] as direct competitors. They definitely do impact sales, because people might want something that climbs stairs instead of having better outdoor capabilities, but I think overall it’s very beneficial for the industry,” Yoshioka adds. “As a company that’s trying to disrupt the industry, it’s nice to have them around because it pushes the industry forward and opens eyes for other manufacturers.”

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A fascinating project called Amadeus Code promises to out-Tay-Tay Tay Tay and out-Bon Bon Iver. The AI-based system uses data from previous musical hits to create entirely new compositions on the fly and darn if these crazy robots-songs aren’t pretty good.

The app, which is available from the iTunes Store but doesn’t seem to be working properly, creates song sketches in minutes, freeing you up to create beautiful lyrics and a bit of accordion accompaniment.

The video above is a MIDI version of an AI-produced song and the video below shows the song full produced using non-AI human musicians. The results, while a little odd, are very impressive.

Jun Inoue, Gyo Kitagawa, and Taishi Fukuyama created Amadeus Code and all have experience in music and music production. Inoue is a renowned Japanese music producer and he has sold 10 million singles. Fukuyama worked at Echo Next and launched the first Music Hack Day in Tokyo. Fukujama is the director of the Hit Song Research Lab and went to Berklee College of Music.

“We have analyzed decades of contemporary songs and classical music, songs of economic and/or social impact, and have created a proprietary songwriting technology that is specialized to create top line melodies of songs. We have recently released Harmony Library, which gives users direct access to the songs that power the songwriting AI for Amadeus Code,” said Inoue. “We uniquely specialize in creating top line melodies for songs that can be a source of high quality inspiration for music professionals. We also do have plans that may overlap with other music AI companies in the market today in terms of offering hobbyists a service to quickly create completed audio tracks.”

When asked if AI will ever replace his favorite musicians, folks like Michael & Janet Jackson or George Gershwin, Inoue laughed.

“Absolutely not. This AI will not tell you about its struggles and illuminate your inner wolds through real human storytelling, which is ultimately what makes music so intimate and compelling. Similarly to how the sampler, drum machine, multitrack recorder and many other creative technologies have done in the past, we see AI to be a creative tool for artists to push the boundaries of popular music. When these AI tools eventually find their place in the right creative hands, it will have the potential to create a new entire economy of opportunities,” he said.

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Stripe is expanding beyond online payments with the launch of a new product for in-person payments at brick-and-mortar stores, called Terminal.

The company said Terminal has three main components — there’s hardware, namely card readers built by Stripe partners BBPOS and Verifone, but also SDKs and APIs for customizing checkout experiences, as well as software for managing connected devices.

Stripe’s co-founder and president John Collison discussed the launch at the Code Commerce conference today. Interviewer Jason Del Rey brought up Square, which seems like the obvious point of comparison, and Collison acknowledged that there will probably be areas where the companies will compete.

However, he argued that Stripe and Square are largely targeting different customers — where Square built a card reader for businesses like coffee shops and restaurants, Stripe is aimed at more tech-saavy businesses. Its initial Terminal customers include Warby Parker and Glossier, and it’s also being used by software platforms like Mindbody, Zenoti, AtVenu and Universe.

As Collison put it, Stripe is built for companies “who will geek out about APIs with us.” And that applies to Terminal as well, which Collison said is specifically built for online businesses that are moving into brick-and-mortar stores. The goal here is to help them unify their online and offline customer data and experiences.

And while there’s been some debate about whether most web-based, direct-to-consumer businesses are true tech companies, he argued, “All of them value technology and fundamentally, their assets are not the retail distribution they have or anything like that.”

“We will happily work with all manner of companies, but the kinds of customers we get excited about, the kinds of customers we are designing for, are the ones who are moving very quickly,” he added.

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“There’s nothing like it out there,” says Commander Bill “Doc” Shoemaker (Ret.), chief test pilot for Boom Supersonic, the startup aiming to make a passenger airliner for transoceanic flights at speeds (as you might guess from the name) faster than sound. Shoemaker, a former Navy aviator, fighter pilot and aeronautics engineer, will have the daunting privilege of being the first to fly the company’s proof of concept single-seater during tests next year.

That there’s nothing like Boom is not exactly a controversial opinion — there aren’t a lot of companies out there trying to resurrect supersonic flight. The Concorde is, after all, so well known a cautionary tale of engineering ambition exceeding the constraints of reality that it verges on hackneyed. But Shoemaker isn’t a Silicon Valley startup commentator, he’s a test pilot, and his perspective is that of someone who has worked on and flown dozens of aircraft, including supersonic ones, over his decades-long career.

The first question I asked (though not entirely a serious one) when I had a chance to chat with Shoemaker was whether it was a bit premature to have a chief pilot at a company that doesn’t yet have a plane to fly.

“There’s a good reason to have a pilot at this point,” Shoemaker said. As he delicately put it: “Among the team, the pilots are… uniquely committed to the outcome.”

Among other things, test pilots seem to have a knack for understatement. But it’s certainly true.

“You want the operator’s perspective, like how to build the cockpit, how you’ll operate the aircraft. The designer will come to me for that perspective — he’ll say, ‘how can I tweak the design to be more suitable for you?’ You want that cross-industry expertise.”

Boom is making a supersonic airliner, but it’s still mostly a paper plane, if you will. The company’s test craft, the XB-1, however, is being built and should be taking to the air about a year from now. That’s where many of the components, materials and design choices will be flight-proven. Interestingly, however, actually flying the test craft is a rather analog affair.

“The aircraft is definitely designed around a philosophy, which is ‘keep it simple.’ We’re not trying to introduce any more tech than we really need to. The flight controls are not fly-by-wire, they’re mechanical,” explained Shoemaker. “It’s going to be an interesting airplane to fly. It goes from 150 knots up to Mach 2.2, and up to 45,000 feet. It’ll be a challenge because of that mechanical stuff, but with what we’re trying to do, keeping it simple makes a lot of sense.”

That’s not to say nothing has changed over the last few decades of aeronautics, a topic in which, if you’ll recall, Shoemaker has a doctorate. Although he said he considers his role as being separate from the flight test engineers who put together the craft he’s flown, he’s still an important part of the team.

He suggested a few areas where he’s seen or expects improvements to the aircraft creation and testing process.

“One is composite materials. That’s huge,” he said, referring to things like carbon fiber and more exotic weaves and alloys that combine a number of desirable characteristics. “The strength and weight improvements offer new opportunities. You know, the Concorde would contract like a foot during flight temperatures, then expand again. Composites don’t do that. All these things make the aircraft lighter, faster and stronger.”

Second, he briefly noted, engine technology these days is “brisk,” especially combined with the materials advances.

“Last,” he said, “the Concorde design was wind-tunnel based, but a lot of the work we do is computation. We can do all the testing they did for the Concorde in a couple days.”

Wind tunnels are still involved, of course, but the models are so good that it’s more for verification than testing. But it also lets designers speed through ideas, evaluating but skipping wild ones without wasting time: “You can look at all these weird corner cases, and explore those very quickly.”

Basic advances in tech mean the team can avoid quirks like the Concorde’s drooping nose, which was there so that pilots could see the runway. “You can imagine all the mechanical complexity that comes with that,” said Shoemaker. “For us we’ll be going with a direct camera or some kind of vision system that’s integrated with all the systems.”

“The airliner itself,” he said, “will be highly augmented [compared to the test jet]. It’ll be fly-by-wire. Its handling qualities are really quite benign across the envelope. It’s surprising, but the way the aircraft handles on one side of the speed of sound isn’t so different from how it handles on the other side.”

Ultimately Shoemaker was optimistic about the whole enterprise, both the company and the prospect of supersonic passenger flight.

“As far as an ambitious project with an ambitious goal, there’s nothing like it out there,” he said. “That’s the value and reward of working with a team this size, a team that really believes they can reinvent and do it better. And it’s well within what we can do with technology — we can do it better than Concorde did, possibly by orders of magnitude.”

As for his part, the test flights set to take place next year, he’s more than a little excited.

“It’ll be a challenge to fly for sure — but it’ll be nice to go that fast again.”

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Saudi Arabia’s sovereign wealth fund is investing $1 billion into Lucid Motors, capital that will finance the commercial launch of the startup’s first electric vehicle.

The agreement comes just six weeks after Tesla CEO Elon Musk tweeted that he was considering taking Tesla private at $420 a share and had secured the proper funding to make the leap. Musk suggested that Saudi’s wealth fund, which already owns almost 5 percent of Tesla stock, was interested in backing the company’s move from public to private.

Tesla’s board and Musk have since quashed those plans to go private.

The investment came at a crucial moment for Lucid Motors, which has struggled recently to raise the funds needed to produce its luxury EV, the Lucid Air. The funding will be used to complete engineering development and testing of the Lucid Air, construct its factory in Casa Grande, Arizona, begin the global rollout of its retail strategy starting in North America and enter production, the company said.

Lucid Motors was founded 10 years ago with a different name and mission. The company, called  Atieva at the time, was focused on developing electric car battery technology. It then shifted to producing electric cars and changed its name in 2016.

The company seemed to have momentum at the time. Lucid Motors had successfully raised money, unveiled the Air, announced plans to build a $700 million factory in Arizona, signed a deal with Samsung SDI to supply it with lithium-ion batteries and moved into spacious new digs. But building a factory is expensive, and the company fell silent for nearly a year as it sought funding to produce the Air.

It’s also a notable investment for the Saudi kingdom, which under its Vision 2030 plan is seeking to diversify its economy away from fossil fuels. In the past year, the Saudi Public Investment Fund has invested in renewable energy, established and developed recycling companies and energy efficiency services, the kingdom noted in a release.

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Saudi Arabia’s sovereign wealth fund is investing $1 billion into Lucid Motors, capital that will finance the commercial launch of the startup’s first electric vehicle.

The agreement comes just six weeks after Tesla CEO Elon Musk tweeted that he was considering taking Tesla private at $420 a share and had secured the proper funding to make the leap. Musk suggested that Saudi’s wealth fund, which already owns almost 5 percent of Tesla stock, was interested in backing the company’s move from public to private.

Tesla’s board and Musk have since quashed those plans to go private.

The investment came at a crucial moment for Lucid Motors, which has struggled recently to raise the funds needed to produce its luxury EV, the Lucid Air. The funding will be used to complete engineering development and testing of the Lucid Air, construct its factory in Casa Grande, Arizona, begin the global rollout of its retail strategy starting in North America and enter production, the company said.

Lucid Motors was founded 10 years ago with a different name and mission. The company, called  Atieva at the time, was focused on developing electric car battery technology. It then shifted to producing electric cars and changed its name in 2016.

The company seemed to have momentum at the time. Lucid Motors had successfully raised money, unveiled the Air, announced plans to build a $700 million factory in Arizona, signed a deal with Samsung SDI to supply it with lithium-ion batteries and moved into spacious new digs. But building a factory is expensive, and the company fell silent for nearly a year as it sought funding to produce the Air.

It’s also a notable investment for the Saudi kingdom, which under its Vision 2030 plan is seeking to diversify its economy away from fossil fuels. In the past year, the Saudi Public Investment Fund has invested in renewable energy, established and developed recycling companies and energy efficiency services, the kingdom noted in a release.

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