Services
AI Agent
Our approach: from concrete case to a running agent
Our AI agents are designed to integrate into your existing processes, not to replace them all at once. We start from real work, identify where an agent can lighten the workload or improve a result, and build the solution around it.
One case, one agent
We do not deploy a generic platform hoping that uses will emerge. We start from a precise need, design the agent for that need, and evaluate it on concrete results.
An integration rooted in your environment
The agent lives in your infrastructure: your email inbox, your document storage, your business applications. We use your accounts, your permissions, your policies. Your data stays within your company.
Progressive autonomy
We train your teams to use, adjust, and evolve the agent. Documentation, precision questionnaires, and code remain in your hands. We remain available if you want to go further, but the agent does not depend on our presence to function.
Our onboarding path: an agent deployed in two phases
For organizations that want a first tangible result before investing in a broader roadmap, we offer a path in two distinct phases. The idea: go from curiosity to an operational agent in a few weeks.
Identification workshop
In-person or online with your team. At least one person from Baseline with a technical and business analysis profile participates to evaluate feasibility and anticipate integration obstacles.
We cover all your sectors of operations, without limiting ourselves to the leads already identified. The discussion remains focused on the objective: identify cases where an agent or a copilot can generate a concrete gain and focus on a first relevant and realistic case to deploy.
- The operational sectors analyzed
- The gains identified by sector
- A list of prioritized use cases
- An assessment of the complexity of each case
Broader opportunities, outside the scope of the agent, are documented and can feed a separate roadmap.
Development and deployment
We aim to deploy at least one operational agent in your real environment, based on the cases identified in Phase 1.
Before starting, we send you precision questionnaires to refine the needs. We then proceed with development, integration into your ecosystem (Microsoft 365 by default, Google Workspace on a case-by-case basis), testing, commissioning, and documentation.
More complex environments may require additional time to manage access and permissions appropriately.
- One or more operational agents in your environment
- User and maintenance guides
- Precision questionnaires and technical documentation
What types of agents can we deploy?
Administrative agents
Document preparation, email drafting, report generation, record updating. Ideal for offloading your teams from repetitive tasks that eat up their time without adding value.
Business copilots
Assistants integrated into your sales, marketing, finance, HR, or operations tools. They suggest, recommend, and accelerate work without replacing human judgment. Think of a colleague who is always available and knows your processes.
Integrated agents
Administrative and business agents, depending on their needs, can be integrated and take actions directly in your existing systems (creating POs in Business Central, etc.). These integrations are made taking into account all the best security practices and bring considerable power to the deployed agents. This also adds a level of complexity in deployment time accordingly.
Research and synthesis agents
For searching, analyzing, and summarizing internal or external information. Competitive intelligence, file preparation, data extraction from complex documents (PDFs, contracts, technical reports).
Customer and internal support agents
Answers to recurring questions from clients or employees, 24/7, based on your documentation, policies, and real data. An agent that knows what it is talking about, because it knows your documentation and policies.
Another type of agent in mind ?
Every project is unique. We can evaluate with you which type of agent would best suit your context.
AI Agents : for whom?
Executives and business owners
Who want a first tangible result before investing in a broader AI approach.
Operational teams
Who want to delegate repetitive work and focus on what requires judgment.
Quebec SMEs without an internal AI team
Who are looking for a partner to get started with a clear framework and a concrete deliverable.
Large organizations exploring
Who want to validate an agent use case before a large-scale deployment.
Why Baseline?
Multidisciplinary team. AI experts, software engineers, business analysts. We cover the entire chain, from scoping to production.
Business vision before tech. We first seek to solve a problem. If the best solution is not an AI agent, we tell you.
Responsible AI. Transparency on what the agent does and its limitations. No "black box" without explanation.
At least one agent in production. Our commitment is a running agent in your environment, used by your teams.
Concrete case approach. No generic platform, no abstract promise. One case, one agent, one result.
Documentation and knowledge transfer. You walk away with what you need to evolve the solution without depending on us.
What you gain
A tangible result in a few weeks
An operational agent emerges from the realization phase in a few weeks, ready to serve.
A structured starting point
The opportunity micro-report gives you an overview of priority use cases, even if you only deploy one agent now.
Real autonomy
Documentation, code, configurations—everything belongs to you. Your teams can evolve the agent.
A clean integration
The agent lives in your environment, with your accounts, your data, your permissions. No third-party platform hosting your sensitive information.
A foundation for what's next
Once the first agent is in place, you know what works, what requires more depth, and where to go next : roadmap, governance, or other deployments.
Our method
Needs scoping
We start from your operational reality : your processes, your data, your constraints.
Identification workshop
A half-day to map out agent or copilot opportunities across your different sectors. Deliverable: a micro-report of prioritized opportunities.
Precision questionnaires Optional
Depending on the results of the identification workshop, additional details needed to evaluate the relevance of the agents considered are transmitted as targeted questionnaires to the appropriate teams.
Project validation
Based on the information gathered, a first candidate project for implementation is proposed and validated. This process includes defining requirements for the project to be a success, as well as detailing the time and resources needed to complete it.
Design and development
Architecture choice, integration with existing tools, prompts, safeguards, logging. We build the agent so it holds up over time.
Deployment in your environment
Commissioning, testing with your teams, adjustments. The agent goes live in your tenant, not on a third-party server.
Documentation and knowledge transfer
User guides, maintenance guides, user and internal technical team training as needed.
Post-deployment follow-up
We remain available for adjustments, evolutions, and planning next steps : roadmap, governance, other agents.
AI Agents - FAQ
What is the difference between an AI agent and traditional automation?
Traditional automation (scripts, Zapier, Power Automate) follows fixed rules : if X, then Y. It is effective for stable processes, but breaks down as soon as an exception appears or the format changes.
An AI agent reasons with unstructured text, makes contextual decisions, and handles cases that were not explicitly programmed. It can also integrate directly into your existing systems (Business Central, CRM, etc.) to take action in the real workflow.
In practice, we often combine both : the agent handles the parts requiring judgment, and automation executes the predictable steps.
How long does an AI agent deployment take?
Our onboarding path typically spans a 2 to 3-hour identification workshop (Phase 1) followed by 3 to 5 weeks of development and deployment (Phase 2).
More complex environments, with strict security policies or heavy integrations, may require additional time to manage access and permissions appropriately.
For very complex cases (highly sensitive data, high-volume processes, custom models), deployment falls under our AI Development offering with a timeline adjusted to the actual complexity.
How do you guarantee data security and confidentiality?
Our agents are deployed in your own environment (your Microsoft 365 or Google Workspace tenant, or your internal infrastructure). Your data does not leave your perimeter, with the exception of API calls strictly necessary for the language models chosen with you.
We apply cybersecurity best practices : strong authentication, permission controls, agent action logging, secrets management. We comply with Law 25, GDPR, and industry requirements applicable to your business.
For environments with strict security policies, we allow extra time to configure access and permissions appropriately.
On which ecosystems can you deploy an agent?
Microsoft 365 by default. This is the ecosystem for which our connectors and governance framework are most advanced.
Google Workspace is possible on a case-by-case basis. We validate the necessary connectors upstream of the realization phase to ensure deployment is feasible within the planned timeframe.
What is the difference between AI Agents, AI Development, and AI Support?
AI Agents. You want to deploy one or more operational agents or copilots quickly. Focused path, clear scoping, concrete deliverable in a few weeks.
AI Development. You need a broader custom solution, with custom models, complex integrations, prototypes, end-to-end production launch. Longer cycle, project structured like a major software development project.
AI Support. You want to structure your AI strategy before developing anything. Roadmap, governance, awareness, prioritization.
If you are unsure, starting with AI Agents is often a good way to generate a first tangible result, which can then feed strategic support or more ambitious development.
Are we owners of the agent?
Yes. You remain owners of the configurations, code, data, and documentation. You can evolve the agent internally or with us depending on your needs.
What is the cost of an AI agent deployment?
The cost depends on the complexity of the use case, the necessary integrations, and the sensitivity of the data. Our two-phase path offers a predictable starting framework.
Contact us for a personalized quote.
Can an agent be integrated into our existing systems (ERP, CRM)?
Yes, and that is often where agents generate the most value. We integrate agents into systems like Business Central, your CRM, or your internal business applications, while respecting your security and permissions rules.
This type of integration requires more deployment time, but multiplies the concrete impact for your teams.
How do you choose the right use case for a first agent?
We are not looking for the best possible use case, but a good case with real impact and manageable complexity.
During the identification workshop, we speak with the people who do the work every day to identify repetitive tasks that take up time, where the agent can bring a concrete gain. We prioritize based on generated value and technical feasibility, then validate the candidate project together before starting.