AI is perhaps the hottest thing since sliced bread. But that doesn't mean it's getting easier to develop and run. A recent Boston Consulting Group poll suggests that 74% of organizations are struggling to derive value from their AI investments.

William Falcon, creator of the popular open source AI framework PyTorch Lightning, says that in his opinion, businesses very much underplay the amount of legwork involved in AI orchestration.

"Building your own AI platform today is like building your own Slack — it's complex, costly, and not core to your business," he said in TechCrunch. "The value for enterprises lies in their data, domain knowledge, and unique models — not in maintaining AI infrastructure."

Falcon, a former trainee of the Navy Seal and Facebook AI Research intern, started building PyTorch Lightning while an undergraduate at Columbia. The framework raises the high-level interface of the AI library PyTorch, abstracting away the code to set up and maintain AI systems.

Falcon ditched his PhD program at NYU to join forces with Luis Capelo, the former lead on data products at Forbes, to make PyTorch Lighting a commercial venture. Lightning AI layers enterprise-focused services and tools atop this open source framework.

"We have thousands of developers single-handedly training and deploying models [with Lightning AI] at a scale that would have required teams of developers without Lightning," Falcon said.

Lightning AI addresses typically cumbersome tasks such as distributing AI workloads across servers and provisioning the infrastructure needed to evaluate and train AI. The company's flagship product, AI Studios, enables customers to fine-tune and run AI models in the cloud environments that they prefer.

Companies can even host AI-powered apps that run on private cloud infrastructure or their on-premises data centers by using Lightning AI. Pricing is pay-as-you-go, with a free tier including 22 "GPU hours" per month.

The goal is to make dev AI as intuitive as using the iPhone," declares Falcon. The platform has enabled researchers at his alma mater, Columbia, to finish hundreds of experiments in 12 hours.

"Most people don't know this, but most of the world's leading AI products were built or trained on Lightning," Falcon said. "For example, Nvidia's suite of models, NeMo, was built using Lightning tools. Stable Diffusion by Stability AI is another."

Clearly, Lightning AI is gaining steam. Today over 230,000 AI developers and 3,200 organizations use the platform, with the company just recently raising $50 million in a funding round.

There’s competition, though. Comet, Galileo, FedML, Arize, Deepset, Diveplane, Weights & Biases, and InfuseAI offer comparable mixes of paid and free AI orchestration services.

Falcon, for his part, believes the market for managed AI solutions is big enough to support many players. And he’s likely not wrong. Per Fortune Business Insights, the machine learning operations industry vertical — Lightning AI’s vertical — could be worth roughly $13 billion by 2030.

With the new $50 million investment, which comes from Cisco Investments, J.P. Morgan, Nvidia, and K5 Global, Lightning AI’s total war chest stands at $103 million. The New York-based, 50-person company plans to spend the proceeds on recruiting new customers, including government customers, and expanding the Lightning platform to new markets.

With a lean, high-performance team and a 90%+ gross margin product," said Falcon, "we are on track to reach $10 million to $20 million in annual recurring revenue by the end of next year and become profitable shortly after.