AI agents designed, integrated and governed, within a clear scope.

We choose the use cases that matter with you, design and implement your agents, then calibrate them under human approval before extending their autonomy. Each step has an agreed scope, owners and success criteria.

Let’s talk about your project

Three engagements

Three distinct engagements. You can start with the first one and decide afterwards.

Strategy: scope your agentic approach

Identify the use cases that matter and draw the roadmap.

Before investing in agents, integrations or a platform, we work out with you where agentic AI can create real value and what needs to be connected to get there: use cases, processes, systems and data, integration, security and governance. For each agent selected, we define its role, the data it can access, the actions it can take and what a person must approve.

What you get: prioritized use cases, a target architecture, success criteria and a roadmap, usable on their own.

Success criteria: the selected use cases are justified, each agent has a defined role, data and approvals, and you know where to start.

Scoping is an offer in its own right: the result is yours, whether you continue with us, with your own teams or with another partner.

Design and implementation: build, test and deploy a first agent

A first agent in production, within a defined scope.

We configure the agent in the chosen environment (its instructions, actions and guardrails), connect it to authorized data sources (CRM, PSA, Microsoft 365) and test it on real-world scenarios, expected and unexpected. Results are reviewed with your users before deployment.

What you get: a deployed agent, its connections documented, the test results and the runbook to operate it.

Success criteria: the agent passes the agreed test scenarios, including unexpected cases; its access, actions and human approvals are documented; a designated person can suspend the agent.

Calibration and expansion: move from a first agent to broader use

Measure first, then give it more autonomy.

At first, a person approves every important action the agent takes. We measure the quality of its results against the agreed criteria and review its access and guardrails. Then a person decides, based on those measurements, whether to give it more autonomy. We support adoption by your teams and expand use to other processes, so your teams oversee their agents themselves.

What you get: regular reviews, quality tracking, the criteria for moving to more autonomy and a gradual handover of oversight.

Success criteria: the decision to extend autonomy is made by a named person, on measured results; irreversible, external or financial actions always remain approved by a person.

How we build an agent

Humans direct. Agents execute. Your systems govern.

A useful agent is not just intelligent: it has boundaries. Every agent we build follows five rules, whatever the tool and the size of your organization.

Only the access it needs
The agent sees and touches only what its task requires.
A person approves what cannot be undone
Every external message, every payment and every irreversible action goes through human approval.
What the agent reads is never an order
An email or a document that says “ignore your instructions” triggers nothing.
A named owner and a way to stop it
A person answers for the agent and can suspend it without technical help.
A log of its actions
The agent’s actions are recorded, so you can trace what it did.

Four autonomy levels, chosen action by action.

A0
Reads and summarizes.
A1
Proposes, a person acts.
A2
Acts after human approval.
A3
Acts alone, reserved for internal, reversible actions, once calibration is complete.

The same agent can be at level A2 to send an email and at level A3 for a reversible internal write.

Our design principles.

01
The right tool for the task
A deterministic process when the path is known, an agent when judgment is needed.
02
Tested before it serves
Real and unexpected scenarios before going into production.
03
A test environment
Trials run with test accounts, not your production credentials.
04
Native first
We use your platform’s own capabilities before building custom.
05
Results observed, not promised
We assess results after go-live.

Our expertise: the architecture that makes an agent useful, meaning its instructions, its knowledge, its connections, its permissions and its governance.

Security and Governance

Requirements considered from the design stage.

Your security and governance requirements guide solution choices: system access, data handling, integrations and permitted AI use. Together, we examine constraints specific to your organization, including applicable local, legal and professional requirements. These requirements apply to your agents as well as your PSA.

During delivery, we maintain visibility into decisions, risks and dependencies. Scope changes are reviewed with you, and operating responsibilities are clarified before transition.

For each agent, we document the sources it consults, the actions it can take, the human approvals required, the person responsible for operating it and how to suspend it. We review the available settings of your environments (user access, permitted models, data residency) with your administrators.

When an agent handles personal information, such as employee data used for resource assignment, we take it into account from the design stage, according to the requirements that apply to your organization and the data handled, including Quebec’s Law 25 where applicable.

Your teams in control

A well-configured AI environment lets your teams do more, faster and more independently. Our goal is for you to evolve it yourselves. And if one day you no longer need consultants like us, we’ll have done our job well.

After go-live, you choose the level of support. Your teams can supervise the agent themselves, or we can take on a larger share, as your needs require.

Use cases for your organization.

Come prepared to every client meetingSales and client relations.
Track progress without chasing informationDelivery.
Spot projects eroding their margin earlierSteering.

See all use cases

Tell us where you stand: we’ll tell you where to start.