Integrating AI does not mean changing everything
The first mistake of AI projects in companies: believing that it is necessary to replace what exists. In reality, most business tools already in place are capable of accommodating an AI layer without major disruption. Microsoft 365 integrates Microsoft Copilot. Google Workspace is enriched with Gemini for Google Workspace. Salesforce offers Einstein AI. SAP integrates native AI capabilities.
Our role is not to sell you an additional platform - it's to help you activate and configure the AI capabilities already present in your tools, or to connect the most suitable model to your specific use case via API. A CRM that integrates Claude 3.5 Sonnet (Anthropic) to automatically qualify incoming leads. An ERP that uses GPT-4o (OpenAI) to read and categorize supplier invoices. A document database that Gemini 1.5 Pro (Google) transforms into a Q&A assistant for your teams.
This additive approach (AI layered on top of existing systems) minimizes risk, reduces deployment time and preserves your refined processes. For cases where your tools are insufficient, we design custom integrations with suitable models according to your GDPR and budget constraints.
Supported platforms and tools
Microsoft 365 & Teams
Activation and setup of Microsoft Copilot (integrated with Word, Excel, Teams, Outlook), connection to GPT-4o models via Azure OpenAI Service, customized assistants in Teams.
- Microsoft Copilot for M365
- Azure OpenAI Service (GPT-4o)
- Custom Copilot Agents
- Conformity EU Data Boundary
Google Workspace
Deployment of Gemini for Google Workspace (Gmail, Drive, Docs, Sheets), creation of customized agents in AppSheet, integration of Gemini 1.5 Pro via Vertex AI.
- Gemini for Google Workspace
- Vertex AI & Gemini 1.5 Pro
- NotebookLM for your internal documents
- Apps Script with AI for automation
CRM & ERP industry
AI Integration in Salesforce (Einstein AI), HubSpot, Pipedrive, SAP or Sage: lead qualification, account summary, contract data extraction, writing assistance.
- Salesforce Einstein + Claude API
- HubSpot + GPT-4o for lead scoring
- SAP + AI document extraction
- Custom APIs for any other tool
AI models selected according to your constraints
How an AI integration is conducted
Audit of existing connections
Inventory of your current tools, available APIs, data flows between systems. Identification of the least invasive and fastest AI entry points to activate.
Selection of adapted AI model
Benchmark on your specific use case: Claude for writing, GPT-4o Vision for heterogeneous documents, Gemini for Google Drive, Mistral for European compliance. The choice is dictated by your context, not by our commercial partnership.
Architecture & security
Design of the data flow: which data is transmitted, where, in what form. Implementation of DPAs with suppliers, API key management, environment isolation.
Development & testing
Development of integration on test environment. Functional tests, load tests, validation by your business teams on real cases before production.
Deployment & team training
Progressive deployment (by team or by feature). Training of end-users on new workflows. Documentation provided. Monitoring of the first few weeks.
Frequently Asked Questions about AI integration
Can we integrate AI without touching our infrastructure?
In most cases, yes. API integrations are non-invasive: they connect to your existing tools without modifying your infrastructure. The only exception concerns on-premise deployments (private LLM), which require dedicated server resources, which we fully size and configure.
What happens if an AI model becomes obsolete or changes its pricing ?
We build all our integrations with an abstraction layer between your business logic and the LLM model. Switching from Claude to GPT-4o (or to Mistral for sovereignty) only requires modifying the connector, not the entire integration. You are not locked into a provider.