Meibel, a runtime platform for confident AI, announced it has raised $7 million in seed funding to accelerate adoption across industries. The funding round was led by Mosaic General Partnership with participation from Array Ventures, Denver Ventures, Cofounders Capital, and Service Provider Capital.
What Meibel does: Meibel puts technical teams in control of how AI performs in production. Its systems are explainable, reliable, and built to power critical products and workflows in high-trust environments.
While many tools focus on model access/prompt tuning, Meibel focuses on what happens between data and models in live environments. And the platform provides a runtime layer for ingestion, orchestration, evaluation, and governance. This enables the deployment of AI systems into production with confidence, rather than relying on experimentation.
Meibel was created for product and technical teams responsible for delivering reliable AI systems in production. And the platform provides:
1.) Intelligent Data Ingestion – Converts structured and unstructured inputs into context-aware data optimized for accurate, traceable decisions.
2.) Decision Traceability – Links every output to its underlying data, model, and logic for full auditability.
3.) Customizable Confidence Scoring – Evaluates outputs live across dimensions such as grounding, reliability, and safety, with scores tailored to the use case and domain.
4.) Agentic and Adaptive Workflows – Coordinates AI, human, and system actions using both flexible logic and structured oversight.
5.) Continuous Adaptation – Applies live feedback without downtime or retraining to improve outcomes over time.
6.) Execution Control – Enables teams to set configurable rules for decision quality, latency, and cost.
Meibel enables teams to configure and reuse AI experiences at scale, combining model selection, prompt design, data access, and scoring policies into a single runtime definition. And these experiences can be executed through API calls across thousands or millions of interactions, delivering consistent outputs and measurable performance. Teams can A/B test variations by cloning experiences and adjusting key parameters while maintaining a stable foundation for controlled experimentation.
Meibel was designed for teams deploying AI in environments where transparency, control, and performance matter, such as legal tech, financial services, healthcare, energy, and the public sector. The platform is gaining traction in government, finance, and manufacturing, where explainability and control are crucial for production AI.
Meibel gives teams real-time control over how AI pulls data, generates outputs, and decides when to involve a human. It orchestrates workflows across multiple models and data sources, evaluates each output with confidence scoring, and adapts decision logic based on performance or risk. This platform integrates with modern AI infrastructure, including model hosts like Hugging Face and Ray, and tools such as LlamaIndex and LangChain.
SpecBooks Case: SpecBooks, a commercial construction platform, faced a challenge many considered too complex to automate: quoting from architectural plans filled with inconsistent formats, ambiguous specifications, and domain-specific language. Estimators had to interpret product intent, resolve information gaps, and match requirements to a live and evolving product catalog. Working with Meibel, SpecBooks transformed this process into a repeatable and intelligent AI system. Rather than manually reviewing blueprints, the company now uses Meibel’s runtime platform to drive a quoting workflow that is both structured and adaptive.
How the funding will be used: With this funding, Meibel will grow its product and engineering teams, advance core capabilities like orchestration, retrieval, and live feedback, and expand its partnerships across industries adopting AI in production. And these investments will help more teams move beyond pilots into production with AI systems that adapt continuously, explain every decision, and scale with confidence.
KEY QUOTES:
“The future of AI will be won at runtime. Meibel gives teams the control layer they need to manage how AI behaves while it is live. That includes how it retrieves data, makes decisions, and adapts to new inputs in real-time. We are building the runtime platform for AI systems that operate reliably, adapt in real-time, and explain every decision they make at scale.”
Kevin McGrath, CEO and co-founder of Meibel
“We’ve seen dozens of AI infrastructure pitches, and Meibel stood out instantly. It’s not just another orchestration tool. It is a true partner to large clients across industries that are prioritizing AI integration, giving teams the control, traceability, and production reliability needed for business-critical AI deployment. Meibel is defining what it means to operationalize generative AI at scale.”
Fatima Husain, General Partner at Mosaic General Partnership
“For product and engineering teams building AI-driven features, success requires more than integrating models. It’s about delivering customer experiences that create real business value. That means using infrastructure like Meibel that provides transparency, ensures confidence in every output, and integrates seamlessly into the product. These capabilities are now essential for turning AI into a strategic advantage.”
Paul Baier, CEO and Co-Founder of GAI Insights, the leading advisory firm focused on enterprise GenAI
“What began as a manual, high-friction process has become one of our core product features. We didn’t just automate quoting. We automated a workflow that people said couldn’t be done. Meibel gave us the infrastructure to turn that challenge into a product.”
Rob Murray, CEO of SpecBooks
“Meibel’s runtime platform makes it possible for FAST and Supporting Effort to deliver AI systems that meet the military’s requirements for transparency, accountability, and explainability. It has opened new doors for how we support mission-critical programs.”
Dan Wroten, SVP Public Sector
