Document search
Semantic search and source-grounded answers from SharePoint, PDFs or knowledge bases.
AI should fit the business, not the other way around
We focus on targeted use cases: find information, help a user, summarize a case, trigger a process or make a knowledge base easier to use. Access rights and system constraints must remain explicit.
What we can handle
From initial assessment through production and continuous improvement.
Business assistant
Contextual answers, guidance, data-entry assistance and case summaries.
Automation
Trigger workflows, generate meeting notes, classify content or prepare business actions.
Analysis
Extract information, compare documents, summarize and highlight important points.
Security
Respect access rights, source boundaries, auditability and defined scope.
Integration
Connect SharePoint, Microsoft 365, APIs, SQL databases and internal tools.
DEPLOYMENT OPTIONS
An AI architecture aligned with your constraints
Your agent can run in the Cloud, inside your own infrastructure, or combine both approaches depending on data sensitivity, security requirements and performance needs.
Fast deployment
GED365 AI Cloud
A fast-to-deploy solution using Cloud AI services to access powerful models without maintaining dedicated GPU infrastructure.
- Rapid implementation
- Powerful and scalable AI models
- Microsoft 365, SharePoint and API integrations
- Usage-based operating model
Best for: SMEs, business teams, prototypes and automation
Data control
GED365 Private AI
Your agent and model can run within your environment, giving you greater control over infrastructure, access and processed data.
- Hosted in the customer's environment
- Open-weight models or private infrastructure
- Integration with internal data sources
- Architecture designed for confidentiality requirements
Best for: public sector, sensitive information systems and sovereignty requirements
Balance & flexibility
GED365 Hybrid AI
Sensitive data can be processed locally while selected tasks use Cloud services when additional capacity or specialized models are needed.
- Routing based on data sensitivity
- Private AI + Cloud services
- Fine-grained usage and permission controls
- Scalable architecture without a single-provider dependency
Best for: organizations combining strict security with advanced AI needs
Not sure which architecture fits?We start with your data, security constraints and use case before selecting the technology.
Discuss my AI project →How we work
A clear, pragmatic approach adapted to your project and maturity level.
01
Use case
Identify a repetitive task or difficult information-access problem.
02
Data & rights
Define authorized sources, data quality and access rules.
03
Prototype
Build a small real-world scope that users can test.
04
Industrialization
Secure, measure, integrate, document and evolve the agent.
Typical use cases
Concrete needs commonly encountered in Microsoft environments.
SharePoint document assistant
Users ask questions and the agent searches only authorized documents, returns a concise answer and points to the sources.
Internal support
An agent answers recurring questions about tools, policies, procedures and internal documentation.
Case analysis
Extract key data, validate documents, compare content and generate a structured summary.
Workflow automation
The agent prepares an action or triggers a workflow after approval instead of only replying with text.
AI AgentsRAGSharePointMicrosoft 365Copilot StudioAzureAPIsPower AutomateDocument Search
Frequently asked questions
Can the agent see every document?
It should not. Scope and permissions must be explicitly designed according to the architecture.
Can an AI agent connect to SharePoint?
Yes. It is one of the most relevant use cases for document search and business assistance.
Can AI run without sending data to a public Cloud service?
Yes. A Private AI architecture can use models and infrastructure hosted in the customer's environment. The right design depends on required performance, data sensitivity and security constraints.
Cloud, Private or Hybrid: which should we choose?
Cloud prioritizes speed and access to powerful models, Private maximizes infrastructure control, and Hybrid combines both depending on the data and use case.
Do we need to start with a large project?
No. A focused prototype on a measurable use case is usually the best starting point.
Planning a project?
A short first discussion is usually enough to clarify context, priorities and realistic options.