Microsoft 365 Copilot and AI agents · AI and agents

We implement Copilot and AI agents.

We take Copilot and AI agents to production on your real systems and data, with governance, security and usage measurement from the start.

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Microsoft 365 Copilot

Copilot Studio

Azure AI Foundry

Signs you need it

Do you recognize any of these situations?

These are the situations we see most often when a project starts. If any sounds familiar, let's talk.

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Pilots that do not scale
There are proofs of concept, but none has reached production.
Answers without sources
The assistant answers, but cites no internal documents and cannot be audited.
Licenses without adoption
Copilot licenses were purchased and actual usage is low or unknown.
Ungoverned data
It is unclear what information an agent can see or use.
Uncertain costs
There is no reliable estimate of credit and token consumption.

What we implement

Microsoft technology, chosen for your process.

Microsoft 365 Copilot

AI assistant inside Word, Excel, Outlook and Teams.

When it fits: When the goal is personal and team productivity.

Details at Microsoft ↗

Copilot Studio

Building agents connected to your systems and processes.

When it fits: When you need your own agent for a specific process.

Details at Microsoft ↗

Azure AI Foundry

Agents and assistants with RAG over your documents and systems, with quality evaluation and guardrails, from pilot to production deployment.

When it fits: When the case requires fine-grained control of models, data and deployment.

Details at Microsoft ↗

Agent 365

Management and governance of agents across the organization.

When it fits: When there are several agents and centralized control is needed.

Details at Microsoft ↗

Dynamics 365

Copilot built into the Dynamics 365 applications.

When it fits: When you already use Dynamics 365 and want AI in the workflow.

Details at Microsoft ↗

Product icons and names are Microsoft trademarks and are used only to identify the products we implement.

How we do it

From prototype to production, with continuous evaluation.

Prototype with real data, measurable evaluation before deployment and permanent monitoring. Based on the Cloud Adoption Framework's agent adoption guidance, Success by Design's AI-first practices and Microsoft Foundry observability.

We choose the use case by its value, the available data and the risk.
Milestone · Use case and metrics approved
What we do
- Use case workshop: prioritization by value, feasibility and risk.
- AI maturity level and adoption barriers: from assisted to autonomous.
- Agent type: productivity, action or automation.
- Available data and knowledge: quality, permissions and gaps.
What you get
- Prioritized use cases with success metrics.
- Agent definition: scope, channel and degree of autonomy.
- Data and permissions plan.
AIResponsible AI
Every use case is assessed for risk: what the agent may decide and what stays in human hands.
Rules before code: responsible AI, security and environment ready.
Milestone · Responsible AI review
What we do
- Responsible AI principles applied to the case: transparency, privacy and fairness.
- Agent scope, limits and escalation paths to people.
- Least-privilege access to data and systems, with auditing.
- Environment prepared: Copilot Studio or Azure AI Foundry, connectors and channels.
What you get
- Agent usage and governance policy.
- Human oversight and escalation design.
- Environment ready to build.
AIResponsible AI
Every automated decision has an owner, a record and a person who can step in.
Prototype with real data and an evaluation set from the start.
Milestone · Evaluation passed
What we do
- Agent prototype: instructions, knowledge, tools and memory.
- Evaluation set with real scenarios; quality and safety evaluators.
- Short iterations: measure, adjust and measure again.
- Adversarial testing (red teaming) before exposing it to users.
What you get
- Working agent tested with pilot users.
- Evaluation results: accuracy, groundedness, safety and latency.
- Design decision log.
AIResponsible AI
No version moves forward without passing the quality and safety evaluations.
We go live by channel and group, with monitoring from the first minute.
Milestone · Go-live with responsible AI approval
What we do
- Gradual rollout: pilot, expansion and opening by channel (Teams, web, WhatsApp).
- Integration with the systems and the real workflow.
- Telemetry, traces and alerts active before go-live.
- Training for users and the support team.
What you get
- Agent in production with monitoring.
- Usage, quality and cost dashboard.
- Incident response plan.
AIResponsible AI
Documented approval from business owners before going live.
We measure quality and value continuously, and expand the cases that deliver results.
Milestone · Periodic quality and value review
What we do
- Continuous evaluation on real traffic and scheduled tests.
- Drift monitoring after model updates.
- Tuning of instructions, knowledge and tools based on usage.
- New use cases and greater autonomy when the data supports it.
What you get
- Periodic quality, usage and cost report.
- Backlog of improvements and new agents.
- Reviewed autonomy level.
AIResponsible AI
People keep supervising: they review samples, escalated cases and drift.

Practices based on the AI agent adoption guidance (Cloud Adoption Framework), Success by Design and Microsoft Foundry observability. AI agent adoption (Cloud Adoption Framework) ↗ · Observability and evaluation in Microsoft Foundry ↗

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Credential behind this solution

Solutions Partner for AI Business Solutions · Agentic specialization

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Chile and Peru

Copilot and AI agents for companies in Peru too.

We implement Microsoft 365 Copilot, Microsoft Copilot Studio and Azure AI Foundry from Santiago and Lima. In Peru we operate through W-IT LATAM S.A.C., with an office in Santiago de Surco.

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Clients with operations in Peru