Techin' Geek

Ventures Platform has raised an oversubscribed $83 million second fund as the Pan-African venture firm expands beyond its home market of Nigeria with a strategy shaped by a tougher, more selective venture market.

The firm plans to back early-stage founders across a range of sectors, including fintech, healthcare, SaaS and other areas “where technology can address essential needs and build large, enduring businesses,” Kola Aina, the firm’s founding partner, told TechCrunch. 

Of course, AI is part of that thesis.

“We’re particularly interested in where AI changes the economics of serving African markets,” he said, pointing to its potential to reduce the cost of delivering services and help overcome labor shortages. “For us, AI is most interesting when it is not simply a feature, but an enabler of an entirely different cost structure, business model or market.” 

Ventures Platform, which is headquartered in Nigeria, previously raised a $46 million Fund I in 2022 with a similar, albeit more limited scope. The first fund focused primarily on pre-seed and seed rounds.

“It allowed us to demonstrate that our approach to early-stage investing in Africa could work at an institutional scale and laid the foundation for Fund II,” Aina said. 

Now, Ventures Platform is back with a larger fund and wider geographic mandate.

The firm is expanding its focus beyond Nigeria and has already written checks from Fund II to five companies based in Kenya, South Africa, and Egypt. Check sizes will be up to $3 million, and the firm hopes to deploy the capital over the next three to four years.

“We are particularly interested in markets where technology can expand access to essential products and services, address critical infrastructure gaps, and create entirely new categories of consumption,” Aina said. 

The fundraising process took about a year and a half, with Aina describing the environment as more “selective,” than it was when Ventures Platform raised Fund I.

“LPs are asking harder questions about performance, portfolio construction, liquidity, manager discipline, and differentiation,” Aina said.

From his perspective, the market is still cautious, as LPs demand more evidence that managers can turn portfolio value into realized returns. Capital is no longer assumed to be unlimited, especially after many LPs felt burned by the venture bust a few years ago. 

“The result is a much greater appreciation for capital efficiency, stronger fundamentals, governance, regulatory engagement, and the importance of building businesses that can survive different funding cycles,” he said. “There is a much clearer understanding that building valuable companies and generating venture returns require more than simply raising successive rounds of capital.” 

This year, African startups have raised around $930 million across more than 200 deals. Last year, startups on the continent raised $1.16 billion across 447 deals.

As TechCrunch previously reported, the venture market is now a barbell — with LPs giving capital to a handful of firms at the top and to emerging managers with a track record they can trust.

“Three years ago, there was still a significant amount of curiosity around the African opportunity. Today, LPs expect proof,” Aina said, adding that this discipline is actually healthy for the market. 

“The conversation has moved from ‘Why Africa’ to ‘Why you and how exactly are you going to generate returns,’” he said, adding that simply being a pan-African fund is no longer a strategy. LPs want to know more about access to top talent, how funds are navigating individual markets, and “why you have the right to win,” Aina said. “That combination of local depth and global connectivity is increasingly important as the ecosystem matures.”

In fact, he said that is the biggest edge his firm offers. This latest generation of founders and fund managers has seen what it is like to deal with both an abundance of capital and hardly any at all. He said it’s more important than ever to understand the institutional and market realities founders face while also connecting companies to regional and global networks as they scale. 

That pitch seems to have resonated with existing investors: 70% of Fund I’s LPs returned for Fund II. Backers include the European Bank for Reconstruction and Development, Norfund (Norway’s development finance institution), and Ghana’s Ashesi University Foundation.

“We don’t take that for granted,” he said. 

More than 76% of consumers in India prefer talking to businesses over a phone call, according to a recent study from Truecaller. Since voice is still consumers’ preferred way to communicate, that leaves a big opportunity to automate support and outreach calls using voice AI in the country. Voice AI startup Ringg, which already processes 20 million call attempts a month, is betting that volume keeps climbing over the coming months, and it just raised more money on that belief.

The company said today it has landed $10 million from Peak XV Partners as an extension of its Series A. It had previously raised $5.5 million in a Series A round earlier this year, bringing the round’s total to $15.5 million.

Ringg started life as a text-to-speech startup called DesiVocal, but training its own speech models proved expensive, so the founders moved up the stack — building voice AI agents for enterprises instead. Indian fintech Cred became its first customer, and Ringg has since signed Indian startups like Flipkart, Practo, Groww, and Policybazaar.

“At the start, we were doing high-volume, low-complexity use cases like outbound calling, lead qualification, loan collection, and more. We quickly realized these are not sticky use cases, and so it’s always going to be a price game,” the startup’s co-founder Siddharth Tripathi told TechCrunch.

Ringg still serves some of those simpler use cases, but it has set its sights on more complex workflows: appointment booking for healthcare clinics, abandoned-cart recovery for e-commerce sites, and onboarding/KYC (“know your customer”) checks for fintech apps.

Tripathi said Ringg’s voice agent now runs across 1,200 clinics for the healthcare app Practo, helping patients book visits or follow up on next steps post-visit.

Voice calls still make up over 70% of Ringg’s business, but the startup has started branching into other channels, including chat and WhatsApp. For some clients like Shell, it’s also automating browser-based support requests.

“We are trying to position ourselves as a platform for agents that bring outcomes or get things done rather than voice agents for enterprises,” Tripathi said.

Most of Ringg’s customers are based in India, with a handful in the Middle East and the U.S. But the startup isn’t trying to sell directly to U.S. companies; instead, it wants to partner with global capability centers in India — the offshore hubs multinationals increasingly lean on for back-office and support work — to sell automation capacity alongside human support.

Tripathi said the company builds its own speech recognition and generation models and would eventually like to own the full voice stack, including infrastructure and deployment. For now, though, that remains too costly, so the product works as an orchestration layer, routing tasks to different models depending on the use case.

Rishen Kapoor, a principal at Peak XV, said that because Ringg started as a research lab building its own models, that technical depth shows up in the complex use cases it’s now tackling.

“Because of the technical capabilities, they can actually do these hard-won enterprise workflows end to end. They can complete these higher-value tasks like merchant onboarding, like L1 and L2 support, with quality and with consistency,” Kapoor told TechCrunch.

Voice AI in India is a crowded field. Model makers, including Deepgram, ElevenLabs, Cartesia, and local players like Sarvam and Smallest.ai, are all jockeying for pole position. Orchestration-focused startups like Bolna and Blue Machines are chasing the same layer Ringg occupies, while sector-focused players like Gnani and Arrowhead concentrate heavily on finance.

That layered stack — model makers, orchestrators, and application-layer players all trying to lock in enterprise workflows — is itself the story. The money and the defensibility increasingly sit with whoever owns the customer relationship and the outcome.

Ringg currently has 40 employees, with more than 15 hired in the last three months. The startup is hiring for forward-deployed engineer roles that combine technical chops with product management skills, along with researchers focused on bringing down the cost of running its models.

Generalist, a robotics startup, is now valued at $3 billion after raising additional capital led by 8VC, according to two people with knowledge of the funding.

The fresh capital totals nearly $200 million according to a regulatory filing. That additional capital is an extension of a $400 million Series B led by Radical Ventures that the company announced in June at a $2 billion valuation, the people said. The new capital brings the round’s total funding to $600 million.

Generalist and 8VC didn’t respond to a request for comment.

Generalist was founded in 2024 by former Google DeepMind researchers Pete Florence and Andy Zeng, along with former Boston Dynamics engineer Andrew Barry. It received early backing from 8VC and Radical Ventures as well as Nvidia, Union Square Ventures, Bezos Expeditions, and AI researcher Fei-Fei Li.

Until recently, the startup operated quietly and with little publicity.

Generalist is developing an AI foundation model that can work with various robots. It claims its newly released Gen 1.5 model enables robots to master new tasks from video demonstrations as short as 3 to 12 seconds long.

The startup is working with a handful of customers, using their feedback to tailor the model for specific use cases, according to one source.

Generalist isn’t alone in its pursuit of building a brain for a broad range of robots. Other competitors include Physical Intelligence, which is reportedly valued at $11 billion, and SoftBank-backed Skild AI, valued at $14 billion, as well as Genesis AI, which was in talks as of last month to raise capital at a $3 billion valuation.

The funding surge reflects a bet from some investors that robotics may soon reach its own “ChatGPT moment,” meaning that robots will be able to perform general tasks without being explicitly trained for each one. However, because robots cannot be trained on the entirety of the internet’s data the way LLMs can, some VCs warn that a truly general robotics model may still be years away.

Nitter, an open source project that allowed people to read X posts without logging into or even opening the X app, has received cease-and-desist letters from X demanding that it shut down. The news was shared via a brief message posted to the project’s website, and follows X’s earlier attempts to knock Nitter offline by technical means.

The service also powers a number of other sites, including XCancel, that allow people to view X posts directly.

This isn’t X’s first attempt to shut down Nitter. In 2024, Nitter’s flagship instance, Nitter.net, went dark temporarily after X rolled out new API restrictions. Nitter worked by fetching public X posts and then stripping out the ads, tracking cookies, and JavaScript, giving people a clean, clutter-free way to read posts without an account or the app.

After that crackdown, those who wanted to host a Nitter instance had to connect it to a real X account, according to the project’s GitHub page. Despite the restrictions, development picked back up and Nitter instances came back online.

This time, X is working to shut down Nitter and its instances via legal means. Nitter’s website states that the Nitter.net project is offline while its creator seeks legal advice after receiving a cease-and-desist letter. That creator, a developer who goes by the handle Zedeus, told TechCrunch by email that other Nitter instances received similar letters.

On Nitter’s website, the message currently reads:

On 24 August 2026 cease and desist letters have been sent by X Corp. demanding a permanent takedown of Nitter instances and the project’s repository.

nitter.net is offline and development has stopped for the time being. I’m seeking legal advice and won’t be commenting further on the specifics for now.

Thank you to everyone who used, hosted, packaged, donated and contributed to Nitter over the past seven years.

The letter from X, which TechCrunch has viewed, accuses Nitter of an “unlawful use and circumvention of X’s Application Programming Interface (API) and associated data,” through its service, saying that X has evidence that Nitter scraped X data and accessed X accounts and session tokens in violation of X’s rules.

Lawyers for X said the actions are in violation of “various state and federal laws, including, but not limited to, the Texas Harmful Access by Computer Act (§ 143.001 and § 33.02) and the Lanham Act (15 U.S.C. §§ 1114, 1125).” The letter gave Nitter until 5 p.m. EST on August 25 to shut down.

X is hardly alone in policing alleged scrapers. Meta has taken numerous scrapers to court, and most larger social networks today restrict the use of third-party readers, forcing users to log in and access the site’s content through the official app, where they can be tracked and shown personalized ads.

It’s an unfortunate development for lurkers, given that Nitter and its instances offered a handy way to keep up with certain people’s posts on X without an account. Now those people will either need to give up that access or, as X likely hopes, create an account and log in.

Airbound, an Indian startup building autonomous drones, has raised $37 million in fresh capital as it pushes to make moving goods through the air as cheap as trucking them by road.

The Series A round, led by Greenoaks with participation from DoorDash, Lachy Groom, Lightspeed, and Humba Ventures, comes less than a year after Airbound raised an $8.65 million seed round. With this funding, the three-year-old startup has raised nearly $50 million.

Airbound, and other startups in this nascent sector, argue that drones can move certain goods faster and cheaper than vehicles on the road. And while there have been successful deployments, drone delivery is still far from matching the scale and versatility of trucking.

Airbound is trying to close that gap by redesigning the aircraft to make it more competitive with ground transportation.

Conventional aircraft spend a lot of energy carrying their own weight rather than the payload, making flight expensive, particularly for moving smaller loads. Airbound’s answer is to build vertical-flight drones designed to weigh less than the cargo they carry, founder and CEO Naman Pushp said in an interview.

Airbound’s current drone, called TRT, weighs about 3.3 pounds and can carry around 2.2 pounds of payload. Its next version, currently under development, is expected to weigh about 6.6 pounds and be able to carry up to 11 pounds, Pushp told TechCrunch.

The startup uses a rocket-like, tail-sitter design for its drones, which takes off and lands vertically in an upright position before transitioning to horizontal flight. Pushp said Airbound intends to retain vertical takeoff and landing even as it develops larger aircraft to avoid dependence on runways.

“We want to build towards a world where everything has cost parity with trucking,” he said.

Founded in 2023, Airbound has completed more than 13,000 autonomous flights across the southern Indian cities of Bengaluru and Guntur, Pushp said. That includes more than 1,000 flights with the Indian hospital network Narayana Health, where its drones transport diagnostic samples between healthcare facilities.

The startup uses a single active drone on the Narayana route, flying diagnostic samples about 2.5 miles in around seven minutes. The same samples can take three to five hours to be transported by two-wheelers when factoring in the time spent waiting for enough samples to be bundled for road transport, according to Pushp.

That partnership is expanding to include Narayana’s new Banashankari hospital in Bengaluru, which was designed without an on-site diagnostic lab or blood bank and will instead rely on Airbound’s drones to connect with centralized facilities.

Three-city drone network

Airbound has set its sights on a far larger ambition to create a drone delivery network that connects three cities in the state of Andhra Pradesh. The startup has sign an agreement with the state government with an eventual target of 10,000 flights a day for retail, e-commerce, and healthcare deliveries. That daily flight target will require between 250 and 1,000 aircraft, depending on route lengths, though Pushp expects the number to be closer to 250.

The agreement does not involve a government contract or subsidy, Pushp said, adding that the Andhra Pradesh government is working with Airbound on the regulatory framework needed to enable the network. The startup expects to generate business from companies using it for deliveries.

Indian startups including Skye Air Mobility and TSAW Drones are already building aerial logistics businesses, while other Indian drone makers such as Garuda Aerospace have also explored delivery use cases. Nonetheless, Pushp argues that Airbound wants to build the aircraft that other logistics networks could eventually use rather than just trying to become the largest delivery operator.

“That’s the Boeing role — the aircraft airlines everywhere rely on, not the airline itself,” he said.

Airbound designs and manufactures its aircraft in a 43,000-square-foot facility in Bengaluru, where it keeps work on the airframe and other core systems in-house. While Pushp declined to disclose its production capacity or how many aircraft the startup has built so far, he said manufacturing would not be the bottleneck as Airbound scales.

The bigger bottleneck, Pushp noted, is regulation, particularly securing approvals for beyond visual line of sight (BVLOS) operations, a certification that allows drones to fly beyond the direct sight of an operator and is critical to operating delivery networks at scale.

Those regulatory constraints have also limited Airbound’s ability to turn its flights into meaningful commercial revenue. Moreover, the startup remains broadly pre-revenue despite having a team of more than 150 employees.

“The goal is to be a giant in a few decades, not to make revenue as soon as we can,” Pushp said.

The Dutch Data Protection Authority is fining Uber €825 million (around $966 million) — the second largest penalty issued so far under Europe’s General Data Protection Regulation, according to Reuters.

The Dutch regulator was investigating complaints that Uber had deactivated driver accounts through an automated process without sufficient warning or human oversight. In a statement, deputy chair Monique Verdier said that the company had “committed serious infringements.”

“A computer should not make decisions on its own that have [such] major consequences,” Verdier said.

Uber, however, argued that most driver suspensions are brief, that no permanent deactivations take place without human review, and that drivers have the ability to appeal. (Dutch regulators said some drivers were permanently deactivated without human review, which Uber disputes.) The company said it will appeal the decision.

“We strongly disagree with this decision ​and disproportionate fine,” an Uber spokesperson told Reuters. TechCrunch has reached out to the company for additional comment.

Brahim Ben Ali, a former Uber driver in France, told the Dutch newspaper de Volkskrant that after his account was deactivated in 2019, he collected testimonies from 170 other Uber drivers and eventually brought his complaint to the Netherlands, where Uber’s European headquarters are located.

Ben Ali was assisted in this effort by a Swiss nonprofit focused on digital rights called PersonalData.io, which helped the drivers collect data about how the deactivation decisions were made. Founder Paul-Olivier Dehaye said a driver “can complete a thousand journeys with satisfied passengers, but if just one person reports a very serious problem, the consequences can be enormous.”

Dehaye told me that this is the third fine that the Dutch regulator has levied on Uber, following a €290 million fine over its handling of drivers’ personal data and a €10 million fine stemming from related issues. He also said he plans to start a class action suit through which drivers can seek compensation.

In fact, Dehaye said these fines all originate with complaints made by the same group of drivers. And he’s starting a new company called StartClaims to support the litigation and other regulatory action — first against Uber and then eventually expanding to other gig economy cases, as well as related areas like adtech.

While discussing the case with Dehaye (who I’ve known casually since college), I brought up a blog post by Daring Fireball’s John Gruber, in which Gruber worried that this fine makes it “unlawful in the EU for Uber to monitor its drivers for pulling scams against customers, or just never picking riders up, leaving them stranded.”

Gruber also took issue with Verdier’s statement, arguing, “Saying that ‘a computer’ made these decisions is like saying that when a company suspends or fires a habitually late employee, that ‘the time clock’ made the decision. Managers at the company set the policies, and the devices measure employee compliance.”

Dehaye countered that Gruber “misses the point.”

“Uber is free to use humans to punish drivers who scam, but then [it] has to take responsibility for this decision making (like ‘being an employer’, not ‘being a marketplace’),” he said.