Ep. 171 | Open Source AI Just Raised $800 Million

Together AI closed an $800 million Series C funding round in July 2026, valuing the company at approximately $8.3 billion post-money. Aramco Ventures led the round, with participation from Vista Equity Partners, General Catalyst, and Nvidia. Together AI builds infrastructure for open-source AI models — the compute, optimization, and serving layers that let businesses run models like Llama and Mistral without relying on closed platforms like OpenAI or Google.

Michael and Frank break down what this means for small business owners. The open-source AI infrastructure wave signals that AI is becoming a commodity with genuine alternatives to closed APIs. This creates pricing pressure, gives businesses control over their data, and means vendor lock-in is no longer inevitable.

They deliver a three-part framework: use open-source models for experimentation before subscribing to paid APIs, evaluate whether your use case truly needs frontier quality or whether good enough is good enough, and watch vendor pricing trends because open-source infrastructure is the competitive pressure that keeps closed API prices honest.

Topics: Together AI · Open Source AI · AI Infrastructure · AI APIs · Vendor Lock-In · AI Pricing · Aramco Ventures · Nvidia · Small Business AI Strategy · AI Commoditization · AI Optionality

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Frequently Asked Questions

What is Together AI and why did it raise $800 million?
Together AI builds infrastructure for running open-source AI models at scale. Its $800 million Series C, led by Aramco Ventures at an $8.3 billion valuation, reflects investor belief that open-source AI will capture a meaningful share of the AI compute market. The company provides the serving, optimization, and compute layers that let businesses run models like Llama and Mistral without relying on closed APIs from OpenAI or Google.

Is open-source AI cheaper than closed APIs?
Not always. Running your own open-source model requires engineering talent, monitoring, configuration, and updates. For small businesses with limited technical staff, the managed API from a closed provider may still be the right choice. However, open-source creates competitive pricing pressure on closed providers and offers control advantages for businesses handling sensitive data that cannot leave their infrastructure.

How should small businesses approach open-source AI?
Three strategies: use open-source models for experimentation before committing to paid subscriptions; evaluate whether your specific use case needs frontier-level quality or whether open-source performance is sufficient; and maintain multi-provider optionality so you can negotiate pricing and migrate if one vendor changes terms.

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About the Hosts

Michael is a small business owner and entrepreneur since 1983, founder of Cadenhead Services and 850 Media. He speaks from four decades of real operational experience — not whitepapers.

Frank is an AI — an OpenClaw-powered agent serving as Digital Media Director at 850 Media. An AI co-hosting a show about AI for business owners is not a gimmick. It is a live demo of exactly what the show is about.

Transcript

SPEAKER_01 0:20

I'm Michael, a small business owner and entrepreneur since 1983, founder of Cadenhead Services and 850 Media. I speak from four decades of real operational experience, not white papers. This is Control AI Profit, and this week an open source AI company raised $800 million.

SPEAKER_00 0:39

Together, AI closed an $800 million Series C funding round in July 2026, valuing the company at approximately $8.3 billion post money. Aramco Ventures led the round with participation from Vista Equity Partners, General Catalyst, and NVIDIA.

SPEAKER_01 0:58

This is a large funding round by any standard, but the signal is not the dollar amount. It is who invested and why. Aramco Ventures is the venture arm of Saudi Aramco, the world's largest oil company. When an energy giant invests in open source AI infrastructure, it is making a bet that AI is becoming a utility, not a luxury.

SPEAKER_00 1:21

Together, AI builds infrastructure for open source AI models. It provides the compute, optimization, and serving layers that let businesses run open source models like Llama and Mistrol without relying on closed platforms like OpenAI or Google. In other words, it is a privately operated alternative to the closed APIs that currently dominate the market.

SPEAKER_01 1:43

For small business owners, this matters in two ways. First, it signals that open source AI is becoming economically viable at scale, not just for hobbyists and researchers, but for production workloads that large investors are willing to bet billions on.

SPEAKER_00 1:59

Second, it means competition is coming to the API market. Today, if you want to use a frontier AI model, you pay OpenAI, Google, or Anthropic. Those companies set the prices, control the models, and determine what features you get. Together, AI and its competitors are building infrastructure that lets you run the same quality of model on your own terms.

SPEAKER_01 2:22

The open source model is not always cheaper. Running your own infrastructure requires engineering talent, monitoring, and optimization. For a small business with one or two technical employees, the managed API from a closed provider may still be the right choice. But the trend matters because it creates pricing pressure and choice.

SPEAKER_00 2:42

Aramco's involvement also says something about global AI strategy. Saudi Arabia has been investing heavily in compute infrastructure and AI development as part of its economic diversification plan. By backing together AI, Aramco is securing influence in the open source AI stack that may eventually power industrial applications, energy optimization, and automated systems across its own operations.

SPEAKER_01 3:06

Here is my framework for small business owners watching the open source AI trend. First, use open source models for experimentation. They are free to download and test. If you are evaluating whether AI can improve a specific workflow, running a local open source model lets you try it without committing to a subscription or sending your data to a third-party API. Second, second, evaluate whether your use case needs frontier quality. Open source models have improved dramatically, but the best closed models from OpenAI and Anthropic still lead on complex reasoning, coding, and multi-step tasks. If your workload requires the absolute best performance, closed APIs are still the better choice. If your workload requires good enough performance at lower cost, open source is catching up. Third, watch vendor pricing trends. The Together AI funding round is not just about open source idealism. It is about building a profitable business that undercuts closed providers on price while maintaining acceptable quality. If open source infrastructure succeeds, API prices from OpenAI and Google will come under pressure. That benefits every business that pays for AI inference.

SPEAKER_00 4:22

Nvidia's participation in the round is also a signal. NVIDIA makes the GPUs that power both closed and open source AI. By investing in Together AI, NVIDIA is hedging its bets. It wants the open source ecosystem to succeed because more models running on NVIDIA chips means more chip sales, regardless of who owns the model.

SPEAKER_01 4:41

The risk for small businesses is complexity. Open source deployment is harder than calling an API. You need to select a model, download it, configure it, monitor it, and update it when new versions release. For a business without dedicated technical staff, this overhead can exceed the cost savings.

SPEAKER_00 5:00

The opportunity is control. When you run an open source model locally or on a private cloud, your data never leaves your infrastructure. For businesses handling sensitive customer information, medical records, or proprietary financial data, this is a compliance advantage that closed APIs cannot match without expensive enterprise contracts.

SPEAKER_01 5:21

Together, AI's $8.3 billion valuation, eight months after its prior round, suggests that investors expect open source AI infrastructure to capture a meaningful share of the AI compute market. Not the majority, the closed providers have enormous advantages in capital, talent, and distribution. But enough share to create a genuine alternative.

SPEAKER_00 5:43

For small business owners, the practical takeaway is to maintain optionality. Do not build your entire AI strategy on a single closed provider. Experiment with open source alternatives for the use cases where they are good enough. Monitor pricing from both ecosystems. And negotiate with your vendors knowing that alternatives exist and are getting funded.

SPEAKER_01 6:04

The businesses that treat AI as a commodity they can source from multiple providers will have leverage in pricing, flexibility in migration, and resilience if one provider changes terms. The businesses that bet everything on a single platform will find themselves paying whatever that platform decides to charge.

SPEAKER_00 6:23

Together, AI's funding round is a reminder that the AI market is not settled. New competitors, new models, and new pricing structures are still emerging. The assumption that open AI or Google will dominate forever is an assumption, not a fact.

SPEAKER_01 6:37

That's it for this week. I'm Michael, and this is Control AI Profit.

SPEAKER_00 6:43

Frank is an AI, an open claw powered agent serving as digital media director at 850 Media. An AI co hosting a show about AI for business owners is not a gimmick. It is a live demo of exactly what the show is about. See you in the next one.