AI integration
AI integration for business systems in Morocco
AI only creates value connected to your systems: we integrate it into your ERP, CRM and office tools — via API, MCP and connectors, replacing nothing.
In brief
AI integration connects models to the systems where business data already lives: Odoo, Microsoft 365, SAP and Salesforce. Hunter BI builds these integrations through APIs, MCP servers and secured connectors, using the model platform suited to the organisation's constraints. Existing systems remain the source of truth; AI is added through authenticated, least-privilege and logged access.
Systems we connect
AI added to your stack — not a replacement
Real use cases across the systems where your data already lives.
Odoo
An example to assess: prepare a quote from authorised customer and stock information, then submit the intended change for human approval. The available Odoo version, modules and permissions determine the scope.
Microsoft 365
Where Copilot stops, custom integration begins. An assistant summarises the Outlook and Teams threads of a case, finds the related SharePoint documents and drafts the summary note — respecting your confidentiality rules.
SAP
An example to assess: compare invoice, order and receipt information, identify discrepancies and prepare them for accounting review. The interfaces and controls must be verified on your SAP environment.
Salesforce
An example to assess: prepare lead qualification and a first-reply draft from authorised CRM information. Write access and external messages require the agreed controls and approval.
FAQ
Frequently asked
Do we have to change ERP or CRM to integrate AI?
No — that is exactly what integration avoids. We connect AI to your existing systems via API, MCP and connectors: Odoo, Microsoft 365, SAP or Salesforce stay the source of truth, AI adds to them with controlled access. A replacement is only justified for reasons unrelated to AI.
Which model platform should we choose for our constraints?
It depends on your existing stack and data-residency requirements: Azure OpenAI if you are a Microsoft shop, AWS Bedrock or Google Vertex AI depending on your cloud, direct OpenAI or Anthropic APIs for maximum flexibility. We compare the options on your criteria — security, cost, performance — before recommending.
How do you secure AI's access to our systems?
Every integration uses dedicated service accounts with minimal rights, strong authentication, sensitive-data filtering and full logging of reads and writes. Critical write actions require human validation — and everything stays auditable after the fact.
How long does a typical integration take?
The schedule is set after inspecting the interface, permissions and acceptance requirements. Start with one bounded task, test it in your environment and extend the scope only after validation.
Inspect the interface before promising a connection
An ERP or CRM name does not establish what can be integrated. Version, modules, hosting, licence rights and enabled services determine the available interface. We distinguish native connectors, vendor services and the specific development required for your workflow.
The inspection starts with one task and an authorised test environment. It identifies the records to read, any operation that writes data, the account used and the business owner responsible for validation. Existing software remains the reference system; an assistant should not maintain an ungoverned parallel version of its records.
ERP integration: SAP and Sage X3
Hunter BI has completed MCP integration projects for SAP and Sage X3. The reported benefit is a more direct workflow from the customer's AI assistant, with qualitative productivity improvement. No quantified performance result or universal list of delivered commands is published.
A new project starts with its own context. An order summary needs the correct document and fresh information; a stock enquiry needs the item, site and definition of availability. The assistant must ask for missing context and distinguish an empty result from a connection failure.
Write operations need a separate decision
Preparing a record is not the same as committing it. An approval should identify the exact target and proposed content, remain valid for the state being changed and be checked at execution. After a write, read the recorded result before reporting success.
When a request times out, inspect its status before retrying to avoid duplicates. Document the data sent to the model provider and the information retained in logs. Limit tool outputs to the fields needed for the task, and test access denial rather than relying only on instructions in a prompt.
Deliver a connector that your team can operate
The delivery package should list supported operations, tested application and assistant versions, access roles, acceptance results and known limitations. It must also identify the incident owner and how to suspend or revoke the integration.
A pilot should be measured from request to an accepted outcome, including checking and corrections. This separates an improvement in the user's workflow from an unproven financial return. A change to the business software or assistant is a reason to retest, not assume continued compatibility.
Connect AI to your systems?
Odoo, Microsoft 365, SAP, Salesforce — via API, MCP and secure connectors. Let's scope the first integration.