Meibel Raises $7M to Keep Rogue AI on a Leash

Meibel, the runtime platform designed to bring confidence and control to AI in production, has raised $7 million in seed funding to accelerate adoption across high-trust industries. The round was led by Mosaic General Partnership with participation from Array Ventures, Denver Ventures, Cofounders Capital, and Service Provider Capital. As AI continues its rapid advance from prototype to production, Meibel is betting on an underappreciated but essential layer of infrastructure: what happens at runtime.

Founded by Kevin McGrath and Kiran Devarakonda, Meibel is built around a core insight that the future of AI won’t be won by who builds the best model, but by who controls how AI behaves while it’s live. 

In critical environments like healthcare, finance, legal tech, and government, organizations need to do more than access foundation models or tweak prompts. They need infrastructure that governs how AI ingests data, makes decisions, adapts to new information, and explains its reasoning in real time and at scale.

Unlike other tools that focus on model training or prompt engineering, Meibel’s platform operates as a control layer between data and models in live environments. 

It ingests structured and unstructured inputs and transforms them into context-aware data. It links every AI output back to its source data, model, and logic, creating full decision traceability. It evaluates outputs live using customizable scoring frameworks that assess grounding, reliability, and safety. And it allows technical teams to configure workflows that combine AI, human oversight, and system actions with rules for quality, latency, and cost. With continuous adaptation and real-time feedback, Meibel ensures that AI systems improve without retraining or downtime.

This level of control is already proving transformative for companies like SpecBooks, a commercial construction platform that struggled with the complexity of quoting from inconsistent architectural plans. Blueprints came in fragmented formats, specs were often ambiguous, and the domain-specific language made automation seem impossible. By building its quoting system on Meibel, SpecBooks now uses AI to ingest technical documents, extract product intent, resolve gaps between images and live catalogs, and surface recommendations with confidence and traceability. What began as a high-friction manual process has become one of the company’s signature product features.

For Kevin McGrath, this is the crux of what Meibel enables. It’s not observability after the fact, it’s proactive control over how AI behaves while it’s operating live, in the wild. 

Teams using Meibel define and reuse runtime configurations that combine model selection, prompt design, data access, and scoring policies. These configurations are executed as APIs across millions of interactions with consistency and auditability. Meibel enables teams to A/B test variations, adjust parameters, and scale with stability, turning AI workflows into predictable, measurable experiences.

This promise of real-time transparency and adaptability is why investors like Mosaic General Partnership are backing Meibel. “We’ve seen dozens of AI infrastructure pitches, and Meibel stood out instantly,” said Fatima Husain, General Partner at Mosaic. “It’s not just another orchestration tool. It’s a true partner to large clients prioritizing AI integration, giving them the control, traceability, and reliability needed for business-critical deployment.”

Meibel’s platform is also gaining traction in public sector and defense contexts where explainability and accountability are essential. Its governance capabilities include access control, audit logging, and runtime policies aligned with organizational compliance. Whether deployed via SaaS, private cloud, or on-prem, Meibel integrates seamlessly with modern AI stacks including Hugging Face, Ray, LangChain, and LlamaIndex. While those tools serve and compose models, Meibel handles live orchestration and evaluation, ensuring each decision aligns with performance, risk, and cost goals.

Dan Wroten, SVP of Public Sector at FAST and Supporting Effort, said Meibel is already unlocking new capabilities for government programs. “Meibel’s runtime platform makes it possible for us to deliver AI systems that meet the military’s requirements for transparency, accountability, and explainability,” he said. “It’s opened new doors for how we support mission-critical programs.”

With this new funding, Meibel plans to grow its product and engineering teams, enhance capabilities like orchestration, retrieval, and live feedback, and expand partnerships across industries moving from AI experimentation to full production. The company will also sponsor and speak at The AI Summit in London this June, where it will showcase how runtime infrastructure enables AI to operate with real-time adaptability and transparency.

In a landscape crowded with tools that help companies experiment with AI, Meibel is defining how they operationalize it. As autonomous workflows become more complex and high-stakes decisions are increasingly delegated to machines, Meibel ensures that AI systems remain explainable, reliable, and responsive. It’s not just about building AI it’s about making it trustworthy, controllable, and ready for the real world.