From Copilot in the side panel to an AI workforce in the process.
Copilot gives every person an assistant. An AI workforce gives the business agents that own real steps — invoice matching, case triage, lead research — while your people keep the exceptions and the approvals. ixSquare and AI Xccelerate build both, inside the Microsoft stack you already run.
Copilot, rolled out in the right order.
Copilot for Microsoft 365 and Copilot in Dynamics 365 are the fastest wins — if the tenant is ready for them. We govern permissions first, pilot with two or three roles, then scale by role with adoption metrics.
Copilot for Microsoft 365
Teams, Outlook, Word, Excel, and PowerPoint. Oversharing clean-up, sensitivity labels, and a role-based pilot before the licenses go wide.
Copilot in Dynamics 365
Sales: account summaries, email drafts, opportunity scoring. Customer Service: case summaries, drafted replies, knowledge search. Business Central: bank reconciliation, sales lines, analysis.
Copilot Studio agents
Your first agents, built on the platform your Microsoft 365 licenses already cover — with topics, actions, and connectors to Dataverse and SharePoint.
Agents own the steps. People own the exceptions.
An AI workforce is a set of agents, each responsible for a defined step in a business process, with a named owner, a permission set, a metric, and a threshold above which a person decides. It is not a chatbot with a wider remit.
How it matures
- 01
Assistants
Copilot next to every person.
- Scope
- Drafts, summaries, and answers on request.
- Autonomy
- None. A person asks, reads, and acts.
- Governance
- Tenant permissions and sensitivity labels.
- Metric
- Adoption and time saved per role.
- 02
Agents in a workflow
One step in a process, triggered by the process.
- Scope
- A bounded task: classify, match, draft, route.
- Autonomy
- Acts within a tolerance; escalates outside it.
- Governance
- Its own identity, least-privilege role, audit trail.
- Metric
- Straight-through rate and exception rate.
- 03
Digital workers
A role, end to end, with human oversight.
- Scope
- Several steps across systems, with memory and skills.
- Autonomy
- Owns the queue; a person reviews exceptions and approves impact.
- Governance
- Evaluation sets, thresholds, cost and usage monitoring.
- Metric
- Cycle time, cost per transaction, quality against the eval set.
Digital workers we deploy
Each one is scoped to a process you already run, measured against a number you already report, and handed over with a named owner.
AP clerk
- The agent does
- Reads vendor invoices from the mailbox, matches them to POs and receipts, codes and posts within tolerance.
- A person still
- Reviews price and quantity variances with the evidence attached; approves anything over the threshold.
Service triage
- The agent does
- Classifies incoming cases, sets priority and queue, drafts the first reply from the knowledge base, summarizes the thread for the agent.
- A person still
- Sends or edits the reply; handles escalations and anything involving a refund or a contract.
Sales research
- The agent does
- Builds account briefs before meetings, logs activities, fills missing CRM fields, flags stale opportunities.
- A person still
- Owns the relationship, the forecast call, and every commitment to a customer.
Onboarding & documents
- The agent does
- Collects, checks, and files onboarding and compliance documents; chases what is missing; extracts data into the system of record.
- A person still
- Signs off on completeness for regulated cases; handles the ones that don't fit the template.
IT helpdesk
- The agent does
- Resolves password, access, and device requests end to end; opens and updates tickets for the rest.
- A person still
- Approves privileged access; handles incidents and anything touching finance systems.
Collections
- The agent does
- Runs dunning sequences by customer segment, records payment promises, reconciles remittances.
- A person still
- Decides on disputes, holds, and payment plans.
Procurement intake
- The agent does
- Turns requests into structured requisitions, checks budget and preferred vendors, routes for approval.
- A person still
- Approves spend; negotiates and signs.
How they are built
Copilot Studio
For agents that live in Teams and Microsoft 365 and act through Dataverse, SharePoint, and standard connectors. Fastest to ship; covered by licenses you may already own.
Azure AI Foundry
For agents that need model choice, evaluation pipelines, and enterprise-grade orchestration inside your Azure tenant, with Microsoft, OpenAI, or open models.
Custom stack
For high-volume or multi-system workers: Azure or AWS, OpenAI or Anthropic models, our partner's accelerators for memory, knowledge, and skills — deployed into your cloud.
What makes it safe to run
One identity per agent
Each agent is an Entra ID identity with its own credentials — never a shared service account, never a person's login.
Least-privilege roles
Dataverse security roles and Microsoft 365 permissions scoped to the step the agent owns and nothing else.
Audit by default
Every read, write, and decision is logged with the evidence the agent used, retrievable per transaction.
Evaluation sets
A test set built from your real cases; the agent ships only when it meets the bar, and is re-run on every change.
Human-in-the-loop thresholds
Amounts, confidence, and customer impact define where the agent stops and a person decides.
Cost and usage monitoring
Tokens, calls, and cost per transaction tracked per agent, with alerts before a budget is exceeded.
Pilots stall when five questions go unanswered.
Copilot, ChatGPT, and Claude are already in use. Ideas are not the bottleneck. What's usually missing is a decision on these five points — so we answer them in the first engagement.
Which opportunities are worth pursuing?
Out of dozens of candidate use cases, which few create material value in the next 12 months?
What does measurable value look like?
Hours returned, cycle time cut, revenue protected — defined before anything is built.
How does it fit your data and processes?
Where the system reads from, what it writes back to, and which steps stay human.
How will governance and evaluation work?
Permissions, audit, quality checks, and what 'good enough to ship' means for each use case.
Who owns it in production?
Which team runs it, monitors it, and improves it after handover.
Strategy and execution happen together.
We don't run a long assessment and hand you a plan. Two tracks start on day one and converge on something you can see working before you commit to the roadmap.
Discovery & direction
Where AI creates value, what to prioritize, and how it fits your data, governance, and teams.
Delivery
A working system on your data for the highest-value use case — fast enough to matter.
AI roadmap + working proof of impact
Decide on the roadmap with evidence in hand — before any major commitment.
- 01
Discover
Identify where AI creates meaningful value in your operations — grounded in how work actually happens.
- 02
Prioritize
Rank opportunities by value, feasibility, and risk. Decide what merits investment now.
- 03
Prove
Build a real, working system on your data for the top use case. Evidence, not a slide deck.
- 04
Deploy
Ship inside your environment, identity, permissions, and governance — with evaluation built in.
- 05
Scale
Execute the roadmap with a forward-deployed team embedded alongside yours until it's fully handed over.
What you have at the end
A prioritized AI roadmap
The opportunities worth pursuing, in order, with the value case and dependencies for each.
A working proof of impact
A real system running on your data for the top use case — measured against the value you defined.
A governance & evaluation framework
Who can use what, how quality is checked, and how you'll know it's working after launch.
A deployment plan for your environment
Architecture, integration points, and ownership — ready to execute with an embedded team.
A hybrid workforce, not another chatbot.
The goal isn't an assistant in a side panel. It's AI workers and your people operating in the same business process — with AI taking the volume and humans taking the judgment.
- Intake and triage of requests, emails, and documents
- Gathering and reconciling data across systems
- Drafting, classifying, and executing routine steps
- Flagging exceptions with the evidence attached
- Review exceptions and edge cases
- Approve decisions with financial or customer impact
- Set policy, thresholds, and quality bars
- Improve the process as the data comes in
Finance operations
AP intake, invoice matching, and close tasks inside Business Central and Dynamics 365 Finance.
Customer service
Case triage, drafted responses, and knowledge retrieval in Dynamics 365 Customer Service and Teams.
Sales operations
Lead qualification, account research, and CRM hygiene agents in Dynamics 365 Sales.
Document-heavy processes
Contracts, onboarding, compliance, and procurement flows across SharePoint and Microsoft 365.
Built on what you already run
We're Microsoft-native, and model-agnostic. Systems deploy into your cloud and identity, with the model that fits each job.
- Clouds
- Microsoft AzureAWSGoogle CloudCloudflareVercel
- Models
- Microsoft Copilot & Copilot StudioOpenAIAnthropicOpen-source models
Optional accelerators
Infrastructure our partner has already built so your team doesn't start from zero — used only where they shorten the path.
Governed knowledge
Permission-aware retrieval over your documents and systems.
Agent memory
Persistent context so agents improve instead of starting over.
Agent data infrastructure
Structured stores and pipelines built for agentic workloads.
Skills library
Reusable, tested capabilities across use cases.
Meeting intelligence
Capture decisions and actions from Teams meetings automatically.
Identity & permissions
One backbone for who — and which agent — can do what.
ixSquare × AI Xccelerate
AI Xccelerate is an AI execution partner: forward-deployed engineering teams that take AI from idea to governed production systems. ixSquare brings the Microsoft platform depth; AI Xccelerate brings the AI engineering — one accountable team for both.