Meibel, the runtime platform for confident AI, today announced it has raised $7 million in seed funding to accelerate adoption across industries. The round was led by Mosaic General Partnership with participation from Array Ventures, Denver Ventures, Cofounders Capital, and Service Provider Capital.
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.
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“The future of AI will be won at runtime,” said Kevin McGrath, CEO and co-founder of Meibel. “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.”
While many tools focus on model access and prompt tuning, Meibel focuses on what happens between data and models in live environments. The platform provides a runtime layer for ingestion, orchestration, evaluation, and governance. This makes it possible to deploy AI systems into production with confidence rather than experimentation.
“We’ve seen dozens of AI infrastructure pitches, and Meibel stood out instantly,” said Fatima Husain, General Partner at Mosaic General Partnership. “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.”
MEIBEL IS THE AI RUNTIME CONTROL LAYER
Meibel is purpose-built for product and technical teams responsible for delivering reliable AI systems in production. The platform delivers:
- Intelligent Data Ingestion – Converts structured and unstructured inputs into context-aware data optimized for accurate, traceable decisions.
- Decision Traceability – Links every output to its underlying data, model, and logic for full auditability.
- Customizable Confidence Scoring – Evaluates outputs live across dimensions like grounding, reliability, and safety, with scores tailored to use case and domain.
- Agentic and Adaptive Workflows – Coordinates AI, human, and system actions using both flexible logic and structured oversight.
- Continuous Adaptation – Applies live feedback without downtime or retraining to improve outcomes over time.
- Execution Control – Allows teams to set configurable rules for decision quality, latency, and cost.
“This is not observability after the fact. It is active control over how AI makes decisions at runtime,” said McGrath.
“For product and engineering teams building AI-driven features, success requires more than integrating models,” said Paul Baier, CEO and Co-Founder of GAI Insights, the leading advisory firm focused on enterprise GenAI. “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.”
Meibel allows teams to configure and reuse AI experiences at scale, combining model selection, prompt design, data access, and scoring policies into a single runtime definition. 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.
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FROM CHALLENGE TO COMPETITIVE EDGE: SPECBOOKS’ TRANSFORMATION
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 gaps in information, and match requirements to a live and evolving product catalog.
Working with Meibel, SpecBooks transformed this process into a repeatable, intelligent AI system. Instead of manually reviewing blueprints, the company now uses Meibel’s runtime platform to drive a quoting workflow that is both structured and adaptive.
With Meibel, SpecBooks:
- Ingests specification documents in varied and unstructured formats
- Extracts product intent from technical descriptions
- Bridges gaps between PDF and image specs and live product catalogs
- Surfaces recommendations that reflect domain-specific logic
- Operates with traceability and confidence across customers, manufacturers, and regions
“What began as a manual, high-friction process has become one of our core product features,” said Rob Murray, CEO of SpecBooks. “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.”
See the case study and video here.
BUILT FOR HIGH-TRUST USE CASES, READY FOR SCALE
Meibel is 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 critical for production AI.
Meibel gives teams real-time control over how AI retrieves 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.
The platform integrates with modern AI infrastructure, including model hosts like Hugging Face and Ray, and tools such as LlamaIndex and LangChain. While those tools compose and serve, Meibel manages execution and ensures each step aligns with operational goals.
Deployment is flexible. Meibel supports SaaS, private cloud, and on-premises environments to meet compliance and security needs. Governance capabilities include access control, audit logging, and runtime controls aligned with organizational requirements.
It also supports real-time cost and risk management. Routing and retrieval strategies are dynamically adjusted to meet performance and budget requirements, helping teams scale AI safely and efficiently.
“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,” said Dan Wroten, SVP Public Sector. “It has opened new doors for how we support mission-critical programs.”
As AI workflows become more autonomous and complex, Meibel ensures that explainability scales with automation, so every decision remains transparent, even when made across multi-agent chains.
WHAT COMES NEXT
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. These investments will help more teams move beyond pilots into production with AI systems that adapt continuously, explain every decision, and scale with confidence.
Meibel will also be sponsoring and speaking at The AI Summit in London, booth 305, taking place June 11-12 at Tobacco Dock. The team will be on site to showcase how runtime infrastructure enables AI systems to operate with transparency, adaptability, and real-time control.
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