Practical, governed AI built around real business workflows.

We help organizations design and operationalize AI solutions that actually connect to how the business works. Internal assistants, copilots, and grounded knowledge workflows built on trusted enterprise data inside Microsoft Fabric, governed from the start and operated by your internal team without ongoing external dependency.

Applied AI and copilot enablement is the design and operationalization of AI-driven workflows — including internal assistants, copilots, and grounded knowledge tools — that are connected to enterprise data sources inside Microsoft Fabric and governed for long-term internal ownership. Lunar Point Systems helps organizations move from AI experimentation to practical, trustworthy deployment that supports real business workflows.

AI grounded in trusted internal data, not generic or hallucinated responses
Governance, guardrails, and evaluation designed in from the start
Built for internal ownership, your team operates it without ongoing external dependency
Work with a trusted Microsoft certified team
Discuss Your AI Use Case
Discuss Your AI Use Case
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The goal is AI your team can trust, use, and operate with confidence.

Applied AI delivers real value when it supports a specific business workflow, uses trusted information, and is governed clearly. Most organizations get stuck either over-investing in experimentation that never reaches production, or deploying AI tools without the governance needed to trust the outputs.

Identify AI use cases that are practical, high-value, and technically feasible given your data environment
Design AI workflows grounded in trusted internal data sources, not generic LLM outputs
Establish guardrails, evaluation, and governance so quality and risk are managed intentionally
Build for internal ownership so the AI system is operated and evolved by your team long-term

Designed for predictability, 
not surprises

We approach applied AI the same way we approach machine learning delivery with clarity, governance, practical implementation thinking, and long-term ownership in mind.

View Our Engagement Models
View Our Engagement Models
See How We Work
See How We Work
AI Use-Case Prioritization & Framing

We identify which AI opportunities are worth pursuing based on your data environment, workflows, and governance requirements. Not every use case is ready to build. We focus effort on the ones that are practical, high-value, and technically feasible given what you already have in Fabric.

Copilot & Assistant Workflow Design

We design the end-to-end workflow for your internal assistant or copilot, including retrieval patterns, grounding against trusted internal data sources, and full integration with your existing Fabric environment. The result is a system that returns answers your team can actually rely on.

Guardrail & Governance Framework

We define the evaluation criteria, access controls, and operational guardrails your AI system needs to be trusted and managed responsibly. Built into the design from the start, not added after a problem surfaces.

Documentation & Internal Handoff

We deliver structured documentation and handoff materials so your team understands how the system works, how to evaluate its outputs, and how to extend or update it without needing us involved. Full operational ownership from the day we hand it off.

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The practical difference for your team.

No Separate Vendor Assessment
Because we operate inside your environment, your security team doesn't need to onboard or assess us as an external vendor. We fall within the perimeter they already manage.
Fits Regulated Industries
Healthcare, finance, and government teams can engage confidently. No data leaves your environment, so existing data transfer restrictions simply don't apply.
See Our Services
See Our Services
Faster Time to Value
No new vendor onboarding, no procurement cycles, no integration work. We operate inside the stack you already own and can start immediately.
How We Work
How We Work
Full Control Stays With You
You define the access, own every output, and can revoke permissions at any point. Nothing we build or touch leaves your control.
See How to Engage
See How to Engage

Everything you need to know

How this service works, what’s included, and what to expect from an engagement. If yours isn’t answered here, the fastest path is a short conversation.

What is applied AI enablement?

Applied AI enablement is the design and operationalization of AI-driven workflows, internal assistants, copilots, and grounded knowledge tools, connected to enterprise data inside Microsoft Fabric and built for long-term internal ownership. The goal is AI that works reliably inside your business, not a demo that needs ongoing external support to function.

How is applied AI different from ML model development?

ML model development builds predictive models trained on structured data. Applied AI enablement builds the workflows, assistants, and knowledge tools that put AI capabilities in front of the people doing the work. One predicts outcomes. The other supports decisions and automates workflows in real time. Most mature data programs eventually need both.

Do you work exclusively with Microsoft Fabric for applied AI?

Yes. All Lunar Point Systems applied AI and copilot engagements are designed around Microsoft Fabric's data and governance capabilities, ensuring that AI workflows align with the enterprise data environment already in place.

Can applied AI be governed the same way as the rest of our data platform?

Yes — and it should be. Lunar Point Systems designs governance, data access controls, evaluation criteria, and operational ownership into every applied AI engagement from the start. Governance is not added later.

Can you help us define the use case, not just implement one?

Yes, and that is often where engagements start. Most organizations know they want to do something with AI but are not sure which use case is worth building first. We help identify which opportunities are practical, high-value, and technically feasible given your current data environment, before any implementation begins. Starting with the right use case matters as much as building it well.

Build, Deploy, and Operate Machine Learning in Microsoft Fabric

We help organizations move machine learning from experimentation to reliable production by designing and implementing Fabric-native ML systems that align with enterprise data, security, and governance standards.

Whether you’re building your first production model or scaling an existing ML footprint, we work inside your Fabric environment to ensure models are owned, operated, and evolved confidently by your teams.

Start a conversation about your Fabric roadmap

Book a Call
Book a Call
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Lunar Point Systems designs and deploys production machine learning systems that operate natively within Microsoft Fabric environments.

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