The three questions we get asked most.
If you're a regulated mid-market IT leader looking at AI options, there are realistically three alternatives to Ajutant: Microsoft Copilot, building it yourself, or assembling it from Azure-native services.
Here is what we think about all three, said plainly.
"We have Copilot already. What's different here?"
Copilot is a productivity overlay, not a deployment platform for your specific AI use cases. It gives every user a fast answer; it doesn't give your organisation a way to build, govern, and operate the AI capabilities your business actually needs.
"We could build this ourselves. Why pay you?"
You probably could. But by the time you've built the build experience, the governance, the audit trail, the model gateway, and the operational tooling, and committed to maintaining it forever, you'll have spent considerably more than the platform costs.
"We could assemble this from Azure services. Why pay you?"
You could. The parts all exist. What you'd be buying is twelve to eighteen months of integration work, and a specialist AI team to keep it running, for something that's live in your tenant in weeks, not quarters.
Copilot is a productivity tool. Ajutant is a deployment platform.
Microsoft Copilot is a good productivity tool. Every desk worker in a Microsoft 365 estate benefits from a model integrated into their daily flow. What it isn't, and isn't designed to be, is a way to put your organisation's specific AI use cases into production safely.
When a regulated mid-market IT team tries to use Copilot for that job, they hit a recurring set of problems: agents that inherit user credentials and bypass data restrictions, agent-to-agent calls with no governed audit, no way to build assistants grounded in your own document base with the controls your security team needs, no way to swap models, and no real way to operate the thing as one governed AI capability across the organisation.
What that looks like inside the organisation is what we saw repeatedly before we started building Ajutant: the people who went around governance shipped. The team that respected it looked incapable. Not because the responsible team couldn't do the work, but because the right way had no platform to run on.
That's not Copilot failing at what it's built for. It's people trying to use Copilot for what it isn't built for.
What Copilot is genuinely good at
Copilot makes individual Microsoft 365 users more productive in their daily work. Summarising long Teams threads, drafting in Word, working in Excel: real benefits, delivered to every seat, with very little IT effort. If that is what you bought Copilot for, you have probably had a good experience.
The problem is that "make our people more productive" and "put our organisation's AI use cases into production safely" are different jobs. Copilot does the first one.
Ajutant is built to make Microsoft's AI investment actually pay off for regulated organisations. Same Azure environment, same enterprise contracts, same identity provider. We aren't asking you to leave the Microsoft stack. We're asking you to put a governed deployment platform on top of it.
For the people doing their day-to-day work, keep Copilot. For everything that needs governance, build it on Ajutant.
You could build this. The question is whether you should.
Most IT teams in regulated mid-market organisations are capable of building this. The components are real and available. With a competent engineering team and a clear runway, twelve to eighteen months gets you a working version.
The question isn't whether you can. It's whether the eighteen months, the engineering capacity, and the long-term maintenance cost of doing so is the best use of either. Here is the honest reckoning.
When build-your-own is the right answer
It is the right answer when AI delivery is a strategic capability you want to own rather than buy. Some organisations have made that choice deliberately and well, usually because their use cases are so unusual, or their scale is so large, that a packaged platform can't fit. For most regulated mid-market organisations, those conditions don't apply.
If you're building because you've been told build-vs-buy was the default analysis, ask a sharper question: what's the actual strategic value of owning the AI delivery platform itself, versus owning the use cases that run on it?
Ajutant exists because building it yourself isn't a good use of most IT teams' time, but the use cases you'd build it for are still worth running. The platform compresses the eighteen-month build into a deployment, and frees your engineering capacity to work on the things that are actually unique to your organisation.
The question we'd encourage you to ask: in twelve months' time, would you rather have built a platform, or shipped twelve use cases that run on one?
Yes, it's a wrapper. The wrapper is the product.
If you're technical, there's a third question behind the first two, and it's usually the real one: "Why wouldn't I just assemble this myself from Azure AI Foundry, Copilot Studio, Purview, and Entra ID?" Read that way, Ajutant is a governance wrapper around services you could buy or build yourself. That's partly true, and we'd rather say it out loud than dance around it.
Here is the honest version. The components are all real: a model service, an authoring tool, a data-governance layer, an identity provider, an LLM gateway, a build workflow, an audit pipeline, a cost-management layer. The work isn't acquiring them. It's integrating them into a single governed runtime that a normal IT team can deploy and operate. That integration is the twelve-to-eighteen-month internal project that regulated mid-market organisations start and rarely finish. Ajutant is that integration, packaged, and live in your tenant in weeks, not quarters.
Microsoft will keep encroaching on parts of this, and some of it, tenant isolation especially, will probably become table stakes. But there is one thing Microsoft structurally cannot ship: a platform that routes equally well to Anthropic, to OpenAI directly, to open-weight models, and to whatever comes next. Microsoft's commercial model is selling Microsoft AI. Model independence runs against the grain of their business, so it will always be a second-class path on a Microsoft-native stack. If you want genuine optionality on models, you need a platform whose business isn't selling you one.
There is a second catch, quieter but just as expensive. Wiring Azure-native components into a governed runtime, and keeping it working as each service changes, needs a standing AI engineering function. That is the team regulated mid-market firms struggle to hire and struggle harder to retain. Ajutant is built to be operated by the IT team you already have.
When assembling it yourself is the right answer
It is the right answer when you already run a standing AI engineering function you intend to keep, and owning the integration is a deliberate strategic choice. A few large organisations are right to make it. For most regulated mid-market firms, the specialist team it depends on is exactly what they can't reliably hire or retain.
The sharper question is the same one as before: is owning the integration the thing that creates value for you, or is it the use cases that run on top of it?
Ajutant is the integration, packaged. The same Azure services underneath, the same tenant, the same identity provider. What you're buying is the eighteen months of wiring them into a governed runtime, and the model independence Microsoft has no commercial reason to give you.
Four questions every AI platform should answer.
Most don't. We do, directly, in writing, on day one.
Built for organisations who need to govern AI in production today, and want to be ready for the agentic workflows their board is asking about. You can't govern an agent if you can't govern an assistant first.
Read the thesisComparing options seriously? Bring your alternatives.
We'll talk through your specific situation, your current Copilot estate or your build plan, and where Ajutant fits or doesn't. If we aren't the right answer for you, we'll say so.
Book a 30-minute discovery call