Tech
Open source companies that go proprietary: A timeline
Open source might be the building blocks of the modern software stack, but companies building businesses off the back of open source software face a perennial struggle between keeping their community happy and ensuring that third parties don’t abuse the permissions afforded by the license.
Many companies have launched with lofty open source ambitions, only to duck for cover once the realities of the commercial world hit home. It’s all about protecting their bottom line, especially with investors (public or private) to appease.
But it can be difficult keeping tabs on all these changes, while also distinguishing those that have abandoned open source altogether and those that have sought sanctuary behind a less permissive (but still open source) license (as the likes of Element and Grafana have done in the past few years).
As such, TechCrunch has compiled a timeline of open source companies that have changed course over the past decade.
Movable Type (2013)
Movable Type created an open source version (called MTOS) of its web publishing software in 2007 under a “copyleft” GPL open source license, a move that positioned it more closely to WordPress. Such licenses afford certain freedoms, but stipulate that all derivative work be released under a similar license. At any rate, this move lasted until 2013, at which point Movable Type’s then owners ditched the open source product, opining that it “hurt the adoption” of the commercial versions.
“The community has not grown because of MTOS, nor have we seen download numbers that are any greater than our paid versions of Movable Type, so at this point it does not make any economic sense to continue to maintain and distribute something that is getting very little use,” the company wrote at the time.
SugarCRM (2014)
Founded initially in 2004, customer relationship management (CRM) software maker SugarCRM announced in 2014 that it would no longer provide an open source “community edition,” noting that its two core markets — developers and first-time CRM users seeking a cheap solution — were not effectively being served by the product.
The company did continue to support the last version (v6.5) of the open source incarnation for four more years, before pulling the plug in 2018.
Redis (2018)
Redis, creators of the popular in-memory database store, has been transitioning away from its open source roots since 2018, when it moved its “Redis Modules” (e.g. RediSearch) from an open source AGPL license to Apache 2.0 with a “Commons Clause” addendum (i.e. commercial restrictions). The following year, Redis replaced the Commons Clause with its own Redis Source Available License (RSAL) that promised to maintain some freedoms, but with notable restrictions related to competing database services — such as those provided by companies such as AWS.
In many ways, this was a bellwether of what was to come, as other companies would later cite the “Amazon problem” as their reason for switching their license up. Earlier this year, Redis’ transition to the world of proprietary was complete, when it announced that its core software would be shifting from a BSD 3-Clause license to a dual-license setup — RSAL or server side public license (SSPL).
MongoDB (2018)
In 2018, database company MongoDB moved away from an open source AGPL license to SSPL. The reason? Yup: to prevent cloud hyperscalers such as AWS from selling their own version of the service without contributing back.
Confluent (2018)
The “year that was” for open source license switching concluded with Confluent, a company that sells enterprise-grade tools and services around Apache Kafka, switching some of the components of its core platform from Apache 2.0 to a proprietary Confluent Community License.
This license stipulates a notable exclusion, one that forbids any competing service from offering Confluent’s wares “as-a-service.”
Cockroach Labs (2019)
Cockroach Labs, creator of the eponymous distributed SQL database known as CockroachDB, has continued to shake up its licensing ethos.
In 2019, the company’s founders announced that they were moving CockroachDB from the permissive Apache 2.0 license to the Business Source License (BUSL). Again, cloud hyperscalers such as AWS were the driving force behind the change.
“We’re witnessing the rise of highly integrated providers take advantage of their unique position to offer ‘as-a-service’ versions of OSS [open source software] products, and offer a superior user experience as a consequence of their integrations,” the founders wrote at the time.
Back in August, Cockroach Labs announced yet another change: It would consolidate its self-hosted product under a single enterprise license, as a way to encourage larger businesses to pay for the features they really need.
Sentry (2019)
Sentry, the $3 billion company behind the app performance monitoring platform of the same name, was once available under a permissive BSD 3-Clause open source license. But in 2019, the company moved to BUSL, with co-founder and CTO David Cramer saying this was to counter “funded businesses plagiarizing or copying our work to directly compete with Sentry.”
Last year, Sentry launched its very own Functional Source License (FSL), which is similar to BUSL but a little simpler. And as of this year, Sentry is putting its weight behind a new licensing paradigm dubbed “fair source,” which, as TechCrunch reported at the time, is “designed to bridge the open and proprietary worlds, replete with new definition, terminology, and governance model.”
Elastic (2021)
It was several years in the making, but Elastic — creator of enterprise search engine Elasticsearch and the Kibana visualization dashboard — went proprietary in 2021. It was a familiar story, one that can be traced back to 2015 when AWS launched its own managed Elasticsearch service.
However, Elastic stands somewhat alone as one of the only companies to move away from open source, and then move back. Back in August, Elastic announced it would be adopting an AGPL license — different to the Apache 2.0 license it used prior to 2021, but open source nonetheless.
HashiCorp (2023)
HashiCorp also abandoned the open source ship last year, announcing that it was switching its popular “infrastructure as code” tool Terraform from a copyleft open source license to BUSL.
The familiar reason was to prevent certain vendors from monetizing Terraform without contributing anything back to the project.
An open source fork called OpenTofu was launched earlier this year by third parties, and as a notable aside, IBM snapped up HashiCorp for $6.4 billion.
Snowplow (2024)
Snowplow, a VC-backed platform that helps companies collect behavioral data for AI applications, this year switched from an open source Apache 2.0 license to the Snowplow Limited Use License Agreement.
The reason, the company said, was that it needs to fund its “exciting technology roadmap,” and thus everyone running its software in production should “pay for the value they receive in return.” The new license also explicitly prevents users from creating a competitive product built on top of Snowplow.
Tech
Volkswagen’s cheapest EV ever is the first to use Rivian software
Volkswagen’s ultra-cheap EV called the ID EVERY1 — a small four-door hatchback revealed Wednesday — will be the first to roll out with software and architecture from Rivian, according to a source familiar with the new model.
The EV is expected to go into production in 2027 with a starting price of 20,000 euros ($21,500). A second EV called the ID.2all, which will be priced in the 25,000 euro price category, will be available in 2026. Both vehicles are part of the automaker’s new of category electric urban front-wheel drive cars that are being developing under the so-called “Brand Group Core” that makes up the volume brands in the VW Group. And both vehicles are for the European market.
The EVERY1 will be the first to ship with Rivian’s vehicle architecture and software as part of a $5.8 billion joint venture struck last year between the German automaker and U.S. EV maker. The ID.2all is based on the E3 1.1 architecture and software developed by VW’s software unit Cariad.
VW didn’t name Rivian in its reveal Wednesday, although there were numerous nods to next-generation software. Kai Grünitz, member of the Volkswagen Brand Board of Management responsible for Technical Development, noted it would be the first model in the entire VW Group to use a “fundamentally new, particularly powerful software architecture.”
“This means the future entry-level Volkswagen can be equipped with new functions throughout its entire life cycle,” he said. “Even after purchase of a new car, the small Volkswagen can still be individually adapted to customer needs.”
Sources who didn’t want to be named because they were not authorized to speak publicly, confirmed to TechCrunch that Rivian’s software will be in the ID EVERY1 EV. TechCrunch has reached out to Rivian and VW and will update the article if the companies respond.
The new joint venture provides Rivian with a needed influx of cash and the opportunity to diversify its business. Meanwhile, VW Group gains a next-generation electrical architecture and software for EVs that will help it better compete. Both companies have said that the joint venture, called Rivian and Volkswagen Group Technologies, will reduce development costs and help scale new technologies more quickly.
The joint venture is a 50-50 partnership with co-CEOs. Rivian’s head of software, Wassym Bensaid, and Volkswagen Group’s chief technical engineer, Carsten Helbing, will lead the joint venture. The team will be based initially in Palo Alto, California. Three other sites are in development in North America and Europe, the companies have previously said.
“The ID. EVERY1 represents the last piece of the puzzle on our way to the widest model selection in the volume segment,” Thomas Schäfer, CEO of the Volkswagen Passenger Cars brand and Head of the Brand Group Core, said in a statement. “We will then offer every customer the right car with the right drive system–including affordable all-electric entry-level mobility. Our goal is to be the world’s technologically leading high-volume manufacturer by 2030. And as a brand for everyone–just as you would expect from Volkswagen.”
The Volkswagen ID EVERY1 is just a concept for now — and with only a few details attached to the unveiling. The concept vehicle reaches a top speed of 130 km/h (80 miles per hour) and is powered by a newly developed electric drive motor with 70 kW, according to Volkswagen. The German automaker said the range on the EVERY1 will be at least 250 kilometers (150 miles). The vehicle is small but larger than VW’s former UP! vehicle. The company said it will have enough space for four people and a luggage compartment volume of 305 liters.
Tech
The hottest AI models, what they do, and how to use them
AI models are being cranked out at a dizzying pace, by everyone from Big Tech companies like Google to startups like OpenAI and Anthropic. Keeping track of the latest ones can be overwhelming.
Adding to the confusion is that AI models are often promoted based on industry benchmarks. But these technical metrics often reveal little about how real people and companies actually use them.
To cut through the noise, TechCrunch has compiled an overview of the most advanced AI models released since 2024, with details on how to use them and what they’re best for. We’ll keep this list updated with the latest launches, too.
There are literally over a million AI models out there: Hugging Face, for example, hosts over 1.4 million. So this list might miss some models that perform better, in one way or another.
AI models released in 2025
Cohere’s Aya Vision
Cohere released a multimodal model called Aya Vision that it claims is best in class at doing things like captioning images and answering questions about photos. It also excels in languages other than English, unlike other models, Cohere claims. It is available for free on WhatsApp.
OpenAI’s GPT 4.5 ‘Orion’
OpenAI calls Orion their largest model to date, touting its strong “world knowledge” and “emotional intelligence.” However, it underperforms on certain benchmarks compared to newer reasoning models. Orion is available to subscribers of OpenAI’s $200 a month plan.
Claude Sonnet 3.7
Anthropic says this is the industry’s first ‘hybrid’ reasoning model, because it can both fire off quick answers and really think things through when needed. It also gives users control over how long the model can think for, per Anthropic. Sonnet 3.7 is available to all Claude users, but heavier users will need a $20 a month Pro plan.
xAI’s Grok 3
Grok 3 is the latest flagship model from Elon Musk-founded startup xAI. It’s claimed to outperform other leading models on math, science, and coding. The model requires X Premium (which is $50 a month.) After one study found Grok 2 leaned left, Musk pledged to shift Grok more “politically neutral” but it’s not yet clear if that’s been achieved.
OpenAI o3-mini
This is OpenAI’s latest reasoning model and is optimized for STEM-related tasks like coding, math, and science. It’s not OpenAI’s most powerful model but because it’s smaller, the company says it’s significantly lower cost. It is available for free but requires a subscription for heavy users.
OpenAI Deep Research
OpenAI’s Deep Research is designed for doing in-depth research on a topic with clear citations. This service is only available with ChatGPT’s $200 per month Pro subscription. OpenAI recommends it for everything from science to shopping research, but beware that hallucinations remain a problem for AI.
Mistral Le Chat
Mistral has launched app versions of Le Chat, a multimodal AI personal assistant. Mistral claims Le Chat responds faster than any other chatbot. It also has a paid version with up-to-date journalism from the AFP. Tests from Le Monde found Le Chat’s performance impressive, although it made more errors than ChatGPT.
OpenAI Operator
OpenAI’s Operator is meant to be a personal intern that can do things independently, like help you buy groceries. It requires a $200 a month ChatGPT Pro subscription. AI agents hold a lot of promise, but they’re still experimental: a Washington Post reviewer says Operator decided on its own to order a dozen eggs for $31, paid with the reviewer’s credit card.
Google Gemini 2.0 Pro Experimental
Google Gemini’s much-awaited flagship model says it excels at coding and understanding general knowledge. It also has a super-long context window of 2 million tokens, helping users who need to quickly process massive chunks of text. The service requires (at minimum) a Google One AI Premium subscription of $19.99 a month.
AI models released in 2024
DeepSeek R1
This Chinese AI model took Silicon Valley by storm. DeepSeek’s R1 performs well on coding and math, while its open source nature means anyone can run it locally. Plus, it’s free. However, R1 integrates Chinese government censorship and faces rising bans for potentially sending user data back to China.
Gemini Deep Research
Deep Research summarizes Google’s search results in a simple and well-cited document. The service is helpful for students and anyone else who needs a quick research summary. However, its quality isn’t nearly as good as an actual peer-reviewed paper. Deep Research requires a $19.99 Google One AI Premium subscription.
Meta Llama 3.3 70B
This is the newest and most advanced version of Meta’s open source Llama AI models. Meta has touted this version as its cheapest and most efficient yet, especially for math, general knowledge, and instruction following. It is free and open source.
OpenAI Sora
Sora is a model that creates realistic videos based on text. While it can generate entire scenes rather than just clips, OpenAI admits that it often generates “unrealistic physics.” It’s currently only available on paid versions of ChatGPT, starting with Plus, which is $20 a month.
Alibaba Qwen QwQ-32B-Preview
This model is one of the few to rival OpenAI’s o1 on certain industry benchmarks, excelling in math and coding. Ironically for a “reasoning model,” it has “room for improvement in common sense reasoning,” Alibaba says. It also incorporates Chinese government censorship, TechCrunch testing shows. It’s free and open source.
Anthropic’s Computer Use
Claude’s Computer Use is meant to take control of your computer to complete tasks like coding or booking a plane ticket, making it a predecessor of OpenAI’s Operator. Computer use, however, remains in beta. Pricing is via API: $0.80 per million tokens of input and $4 per million tokens of output.
x.AI’s Grok 2
Elon Musk’s AI company, x.AI, has launched an enhanced version of its flagship Grok 2 chatbot it claims is “three times faster.” Free users are limited to 10 questions every two hours on Grok, while subscribers to X’s Premium and Premium+ plans enjoy higher usage limits. x.AI also launched an image generator, Aurora, that produces highly photorealistic images, including some graphic or violent content.
OpenAI o1
OpenAI’s o1 family is meant to produce better answers by “thinking” through responses through a hidden reasoning feature. The model excels at coding, math, and safety, OpenAI claims, but has issues deceiving humans, too. Using o1 requires subscribing to ChatGPT Plus, which is $20 a month.
Anthropic’s Claude Sonnet 3.5
Claude Sonnet 3.5 is a model Anthropic claims as being best in class. It’s become known for its coding capabilities and is considered a tech insider’s chatbot of choice. The model can be accessed for free on Claude although heavy users will need a $20 monthly Pro subscription. While it can understand images, it can’t generate them.
OpenAI GPT 4o-mini
OpenAI has touted GPT 4o-mini as its most affordable and fastest model yet thanks to its small size. It’s meant to enable a broad range of tasks like powering customer service chatbots. The model is available on ChatGPT’s free tier. It’s better suited for high-volume simple tasks compared to more complex ones.
Cohere Command R+
Cohere’s Command R+ model excels at complex Retrieval-Augmented Generation (or RAG) applications for enterprises. That means it can find and cite specific pieces of information really well. (The inventor of RAG actually works at Cohere.) Still, RAG doesn’t fully solve AI’s hallucination problem.
Tech
Not all cancer patients need chemo. Ataraxis AI raised $20M to fix that.
Artificial intelligence is a big trend in cancer care, and it’s mostly focused detecting cancer at the earliest possible stage. That makes a lot of sense, given that cancer is less deadly the earlier it’s detected.
But fewer are asking another fundamental question: if someone does have cancer, is an aggressive treatment like chemotherapy necessary? That’s the problem Ataraxis AI is trying to solve.
The New York-based startup is focused on using AI to accurately predict not only if a patient has cancer, but also what their cancer outcome looks like in 5 to 10 years. If there’s only a small chance of the cancer coming back, chemo can be avoided altogether – saving a lot of money, while avoiding the treatment’s notorious side effects.
Ataraxis AI now plans to launch their first commercial test, for breast cancer, to U.S. oncologists in the coming months, its co-founder Jan Witowski tells TechCrunch. To bolster the launch and expand into other types of cancer, the startup has raised a $20.4 million Series A, it told TechCrunch exclusively.
The round was led by AIX Ventures with participation from Thiel Bio, Founders Fund, Floating Point, Bertelsmann, and existing investors Giant Ventures and Obvious Ventures. Ataraxis emerged from stealth last year with a $4 million seed round.
Ataraxis was co-founded by Witowski and Krzysztof Geras, an assistant professor at NYU’s medical school who focuses on AI.
Ataraxis’ tech is powered by an AI model that extracts information from high-resolution images of cancer cells. The model is trained on hundreds of millions of real images from thousands of patients, Witowski said. A recent study showed Ataraxis’ tech was 30% more accurate than the current standard of care for breast cancer, per Ataraxis.
Long term, Ataraxis has big ambitions. It wants its tests to impact at least half of new cancer cases by 2030. It also views itself as a frontier AI company that builds its own models, touting Meta’s chief AI scientist Yann LeCun as an AI advisor.
“I think at Ataraxis we are trying to build what is essentially an AI frontier lab, but for healthcare applications,” Witowski said. “Because so many of those problems require a very novel technology.”
The AI boom has led to a rush of fundraises for cancer care startups. Valar Labs raised $22 million to help patients figure out their treatment plan in May 2024, for example. There’s also a bevvy of AI-powered drug discovery firms in the cancer space, like Manas AI which raised $24.6 million in January 2025 and was co-founded by Reid Hoffman, the LinkedIn co-founder.
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