Is monō only for non-Microsoft shops?

No. monō works alongside Microsoft systems and reaches past them to the rest of your stack. You keep what works in Microsoft and run cross-system agents on top.

What about model choice?

monō is model-agnostic, so you can use frontier, open-source or fine-tuned models and swap them over time. You are not tied to a single provider.

Where does the data sit?

In your own cloud, inference-only. Your data stays inside your perimeter rather than the vendor cloud.

How is this different from building topic bots?

monō runs multi-agent operations on shared work items across systems, not single topic bots over one estate. The agents act, coordinate and are governed end to end.

Does the work stay auditable?

Yes. Eval, monitoring and guardrails sit around every agent action, with a full record inside your perimeter rather than a vendor cloud.

An honest comparison

monō vs Microsoft Copilot Studio

Copilot Studio builds bots in the Microsoft estate. monō runs agents across all of it.

Our honest position

Copilot Studio is a capable way to build copilots inside Microsoft 365 and Power Platform. monō is broader and model-agnostic, it orchestrates agentic work across every system, not only the Microsoft estate, and keeps data in your own cloud.

Dimension	Microsoft Copilot Studio	monō
Scope	Copilots within the Microsoft estate	Cross-system agentic operations
Model choice	Primarily OpenAI via Azure	Model-agnostic
Data residency	Microsoft cloud / Azure	Your cloud, inference-only
Multi-agent	Topic/flow-based bots	Native multi-agent + work items
Governance	Within Microsoft Purview/Power Platform	Built-in eval + monitoring
Cost to run	Message-pack / capacity pricing	Harness efficiency + BYO keys, no markup
Compounds over time?	No memory that compounds across your tools and teams	Yes, one memory across your tiles, people and time, inside your tenant

Scope

Microsoft Copilot Studio: Copilots within the Microsoft estate

monō: Cross-system agentic operations

Model choice

Microsoft Copilot Studio: Primarily OpenAI via Azure

monō: Model-agnostic

Data residency

Microsoft Copilot Studio: Microsoft cloud / Azure

monō: Your cloud, inference-only

Multi-agent

Microsoft Copilot Studio: Topic/flow-based bots

monō: Native multi-agent + work items

Governance

Microsoft Copilot Studio: Within Microsoft Purview/Power Platform

monō: Built-in eval + monitoring

Cost to run

Microsoft Copilot Studio: Message-pack / capacity pricing

monō: Harness efficiency + BYO keys, no markup

Compounds over time?

Microsoft Copilot Studio: No memory that compounds across your tools and teams

monō: Yes, one memory across your tiles, people and time, inside your tenant

Cost-to-run is illustrative, same outcome, materially fewer tokens; with your own API keys, your rates, no markup. All marks belong to their owners.

Coding agent, raw

monō harnessup to 70% fewer tokens

Same task, same outcome, a fraction of the tokens. Illustrative.

No FUD

When they're the right call.

Your organisation is all-in on Microsoft 365 and Power Platform.
You mainly need conversational copilots over Microsoft data.
You prefer to stay within the Microsoft governance model.

For a pure Microsoft shop wanting copilots over M365 data, Copilot Studio is the path of least resistance.

The architecture difference

Three decisions they can't retrofit.

Sovereign by architecture

Inference-only. Your cloud, your keys, the data never builds anyone else's product.

Model-agnostic

Frontier, open-source, fine-tuned, swap models without rewrites.

Your own API keys

Your lab accounts, your negotiated rates. We never mark up your tokens.

In depth

The fuller picture.

What Copilot Studio does well

Copilot Studio is a capable way to build copilots inside Microsoft 365 and Power Platform. For an organisation that is all-in on Microsoft, building topic-based bots over Microsoft data is well-trodden and well-governed within that estate. It is a low-friction path for a Microsoft shop.

Why a cross-system layer is different

monō orchestrates agentic work across every system, not only the Microsoft estate, and keeps data in your own cloud. It is model-agnostic rather than primarily tied to OpenAI through Azure, and it runs native multi-agent operations on shared work items. When the work spans systems beyond Microsoft, breadth and model choice start to matter.

FAQ

Questions, answered straight.

Is monō only for non-Microsoft shops?: No. monō works alongside Microsoft systems and reaches past them to the rest of your stack. You keep what works in Microsoft and run cross-system agents on top.
What about model choice?: monō is model-agnostic, so you can use frontier, open-source or fine-tuned models and swap them over time. You are not tied to a single provider.
Where does the data sit?: In your own cloud, inference-only. Your data stays inside your perimeter rather than the vendor cloud.
When is Copilot Studio the right pick?: When you are a pure Microsoft shop wanting copilots over M365 data, Copilot Studio is the path of least resistance.
How is this different from building topic bots?: monō runs multi-agent operations on shared work items across systems, not single topic bots over one estate. The agents act, coordinate and are governed end to end.
Does the work stay auditable?: Yes. Eval, monitoring and guardrails sit around every agent action, with a full record inside your perimeter rather than a vendor cloud.

See it on your own use case.

Your use case, live on the platform, beside whatever you're evaluating.