News, evidence, and field notes for deploying AI.
Company developments, founder perspective, decision frameworks, and operating lessons for leaders moving AI into real infrastructure, workflows, and physical systems.
MH – Applied AI combines current company news with practical guidance on forward-deployed engineering, private and cloud AI, token efficiency, agents, open systems, and embodied intelligence.
Independent enterprise handbooks · English editions
From AI platform to changed work.
Two practical field guides connect governed engineering with adoption, operating ownership, and evidence—without pretending a platform or a license is the strategy.
Microsoft 365 Copilot Adoption Guide for Enterprises
An independent, vendor-neutral handbook for enterprise leaders taking Microsoft 365 Copilot from license assignment to governed, evidence-based adoption.
Microsoft Foundry Adoption Guide for Enterprises
A practical, independent handbook for enterprise leaders and architects moving from Microsoft Foundry exploration to governed production.
Company news & perspective
Why work with MH – Applied AI when major AI vendors have forward-deployed teams?
A practical answer for enterprise leaders choosing between global AI vendor teams and a neutral, local-market deployment partner.
Why MH – Applied AI exists
AI delivery breaks when strategy, engineering, operations, and adoption are separated. MH – Applied AI was created to keep them in one mission.
Marcel Haas and the long path to AI-infused engineering
More than 20 years of platform transitions shaped Marcel Haas’s view that AI needs operational depth, not a separate innovation theater.
People + AI delivery needs one transparent rule
MH – Applied AI combines senior engineering and agentic execution under a visible commercial model instead of treating AI usage as an opaque surcharge.
AI strategy creates value only when it reaches deployment
The MH – Applied AI partner model connects executive direction, organizational readiness, and accountable engineering without turning platforms into strategy.
From 24×7 robotics operations to embodied AI
Marcel Haas’s robotics context connects high-availability AutoStore operations with today’s open social-robotics and enterprise AI systems.
Technical field notes
From AI agents to embodied AI: an enterprise adoption roadmap
A staged path from assistive workflows to bounded agents and physical systems, with governance and human control increasing at every step.
Cloud vs. private AI is a workload decision, not an ideology
An executive framework for deciding where enterprise AI should run across cloud, private infrastructure, local devices, and hybrid systems.
What forward-deployed AI engineering means for enterprise leaders
A practical operating model for moving AI from a promising demonstration into an owned, measurable production system.
Open-source-first AI without building an unsupported platform
How enterprises can preserve choice and inspectability while assigning real ownership for models, serving, security, and lifecycle operations.
Token-efficient enterprise AI starts with system design
Reduce AI operating cost and latency by improving context, routing, model choice, caching, and evaluation—not by blindly shortening prompts.
Foundry Local and hybrid AI: put inference where the mission needs it
How to decide between on-device Foundry Local, managed cloud models, private serving, and a hybrid architecture using evidence instead of deployment ideology.
Private Microsoft Foundry: design the data boundary before the private endpoint
An enterprise architecture guide to inbound access, outbound dependencies, DNS, identity, agent networking, and validation for a private Microsoft Foundry deployment.
From Foundry prototype to production: evaluation is the deployment gate
A practical evaluation system for Microsoft Foundry applications—from representative datasets and task metrics to traces, release gates, and production monitoring.
Microsoft Foundry Agent Service: autonomy needs an operating envelope
How to choose between prompt agents, hosted agents, or an external runtime—and place identity, tools, limits, and human control around each.
Microsoft Foundry is a platform decision, not an AI strategy
A practical executive guide to deciding where Microsoft Foundry belongs in an enterprise AI architecture—and what the platform cannot decide for you.