AI for business
AI agents and automations that do real work, with a person approving every change
We build and run AI agents and automations on Microsoft and the systems you already use: finance, marketing, sales and support work done by agents that ask before they act.
29 AI projects · 20 in production · 2,900+ agent runs
Any model, hosted on Azure. Your data stays in your systems.
Short answer
Communication Square builds and runs AI agents and automations for businesses on Microsoft: agents in Azure AI Foundry and Microsoft Teams connected to ERP, CRM, helpdesk, websites and Microsoft 365, plus Copilot and Copilot Studio where they fit. Every agent has a pinned model, a daily cost cap, an audit log and an off switch, and any change it wants to make goes to a person for approval. The 20 agents and automations in production have completed more than 2,900 runs.
Starting points
Where agents earn their keep first
The cost of waiting
Agents are spreading faster than the controls around them
What it really is
A chatbot answers. An agent acts, inside your rules.
The value is in agents that change things in your systems. The risk is the same. So every agent we build ships with the same controls.
AI projects
Agents and automations we have built, by business function
Every project below exists and has been verified. Status shows whether it is in production, in pilot or built.
Finance
Marketing
Sales
Support and client services
Operations and AI platform
Your options
Copilot licenses, an AI app, or agents built on your stack
All three can be right. They solve different problems.
| Copilot licenses alone | Off-the-shelf AI app | Agents built on your stack (us) | |
|---|---|---|---|
| Works with your systems | Microsoft 365 data | Its own data | Your ERP, CRM, helpdesk and Microsoft 365 |
| Takes actions | Limited | Inside the app | In your systems, after approval |
| Model choice | Microsoft’s | The vendor’s | Any leading model in Azure AI Foundry |
| Controls | Tenant settings | Vendor settings | Approvals, cost caps, audit log, off switch |
| Cost model | Per user | Per user | Fixed-price build, then usage |
Microsoft AI tools
Microsoft 365 Copilot rollout, Copilot Studio and Power Automate
When the Microsoft tool is the right fit, we deploy it with the same controls as our own agents.
Already on Copilot licenses? The free AI readiness assessment is the first step of every rollout.
Our approach
One process at a time, proven before it goes live
- Pick a processHigh volume, clear rules, measurable time saved.
- Build with controlsAgent, approvals, cost cap and audit log in your tenant.
- Shadow modeThe agent proposes while people still do the work.
- Run and measureGo live, then report runs, approvals and savings monthly.
Our promise: no agent changes anything in your systems without a person approving it, unless you decide a step is safe to automate.
Data handling
Where your data goes
- Your systems, your data. Agents read and write through your own APIs and Microsoft tenant.
- Model choice stated up front. Azure OpenAI, Meta and Mistral models run under Microsoft’s data terms in Azure AI Foundry; Anthropic’s Claude models are processed by Anthropic under its own terms. You see which applies before work starts.
- Credentials never with the agent. Access goes through a governed gateway with secrets in Key Vault.
- Everything logged. Runs, tool calls and approvals are recorded for audit.
The offer
Start with a free AI readiness assessment
See what an AI assistant could reach in your Microsoft 365 tenant today, which processes are worth an agent, and what the first one would cost.
Exposure map
What AI could reach today: oversharing and unlabeled sensitive data.
Process shortlist
The three to five processes where an agent saves the most time.
Fixed price
A fixed price for the first agent, built in shadow mode.
- Free, with no obligation
- About one week
- Read-only: nothing changes
- The report is yours to keep
Why free? It is how we scope an agent worth building. If none is worth it yet, we will say so.
How it runs
Day 030-minute call with the engineer who would build it.
Days 1–2Read-only consent to your Microsoft 365 tenant.
Days 2–4Tenant review and process interviews you choose.
Day 5Findings, shortlist and a fixed price.
We reply within one business day.
Read-only Microsoft Graph permissions only, consented by your administrator and revoked at the end. No content leaves your tenant.
Why us
We run these agents every day
Transparent investment
What an agent costs
| Engagement | Typical timeline | Investment |
|---|---|---|
| AI readiness assessment | About one week | Free |
| Copilot Studio proof of concept | 1–2 weeks | $1,997 |
| First agent pilot: one process, shadow mode | 4–6 weeks | $14,900 |
| Production agent with integrations and approvals | 6–10 weeks | $24,900–$49,900 |
| Managed AI operations | Monthly | From $3,500 a month |
Model usage is billed at cost and capped per agent per day.
Questions buyers ask
Before you decide
Which AI models do you use?
The one that fits each task: Azure OpenAI, Anthropic Claude, Meta or Mistral models hosted in Azure AI Foundry, and Gemini where you are on Google. Each agent is pinned to a model tier so cost and behavior stay predictable.
Will our data be used to train models?
No. Models in Azure AI Foundry do not train on your prompts or outputs under Microsoft’s product terms, and Anthropic’s commercial terms also exclude training on customer content.
Do we need Microsoft Copilot licenses?
No. Agents run in Azure and Teams without Copilot licenses. Where Copilot or Copilot Studio is the better fit, we use it.
Copilot Studio or a custom agent on Azure?
Copilot Studio suits agents that mostly answer from Microsoft 365 and SharePoint and need little custom logic. A custom agent on Azure suits work that writes to your ERP, CRM or helpdesk, needs a specific model, or must run at high volume. We recommend one per process.
Do you build Power Automate workflows?
Yes. Simple approvals and document routing stay in Power Automate. When a step needs judgment, such as reading a document or deciding where a ticket goes, we add an agent to that step.
What if an agent gets something wrong?
It proposes rather than acts, so a person catches it at approval. Error rates are reported, and any agent can be switched off in one step.
Put your first agent to work
Start with a free AI readiness assessment and a fixed price for the first agent.