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Summary – Multiply the value of your data and accelerate internal processes with an AI assistant hosted under your control, compliant with ISO 27001, GDPR, and LPD. Accessible through a single portal, it generates content, summaries, development support, and context-aware business answers via RAG, while ensuring encryption, traceability, and fine-grained access governance. Native integration (CRM, ERP, CI/CD), pay-as-you-go pricing, and a POC sandbox guarantee cost control, scalability, and no vendor lock-in.
Solution: deploy an internal ChatGPT to turn AI into a driver of performance and innovation.
Companies today seek to multiply the value of their data and accelerate their internal processes. Deploying a self-hosted and self-governed “internal” AI assistant offers a pragmatic solution: a tool accessible through a simple interface, capable of generating content, assisting with code, summarizing documentation, and answering business-related questions.
With a model hosted on-premises or in a private cloud under your control, every interaction remains confidential, traceable, and compliant with GDPR, FADP, and ISO 27001 requirements. This investment paves the way for increased productivity while ensuring security and cost control for every team.
Boost Your Teams’ Productivity with an Internal AI Assistant
An internal AI assistant centralizes and accelerates content creation, summary writing, and development support. It’s accessible to everyone through a single portal, freeing your employees from repetitive tasks and improving deliverable quality.
Every department benefits from immediate time savings, whether it’s marketing, customer relations, IT projects, or document management.
Automating Content Creation and Summaries
The internal AI assistant understands your guidelines and corporate tone to produce product sheets, LinkedIn posts, or activity reports. It can extract key points from lengthy documents, providing your managers with a relevant summary in seconds.
The quality of this content improves over time through continuous learning based on your feedback. The tool learns your style and structure preferences, ensuring consistency with your external and internal communications.
Marketing teams report a 60% reduction in time spent on initial drafting, allowing them to focus on strategy and performance analysis.
Coding Assistance and Data Handling
The assistant, trained on your code repository, offers snippets, checks compliance with internal standards, and suggests fixes. It interfaces with your CI/CD environment to propose unit tests or ready-to-use snippets. Intelligently Document Your Code ensures optimal integration of this assistant into your development workflows.
In data science, it streamlines explorations by generating SQL queries, preparing ETL pipelines, and automatically visualizing trends from data samples. Your analysts save time on preparation and can focus on interpreting the results.
Thanks to these features, prototype delivery times are halved, accelerating innovation and concept validation.
Intelligent Search and Q&A on Your Internal Documents
By deploying a RAG (Retrieval-Augmented Generation) system, your AI assistant taps directly into your document repositories (SharePoint, Confluence, CRM) to answer business queries precisely. LLM API enables you to connect your assistant to powerful language models.
Employees ask questions in natural language and receive contextualized answers based on your up-to-date documentation. No more tedious searches or outdated information risks.
Example: A Swiss insurer integrated an internal AI assistant into its procedures repository. Client service agents saw a 40% reduction in request processing time, demonstrating the effectiveness of RAG in accelerating decision-making while ensuring response consistency.
Enhanced Security, Compliance, and Governance
Hosting your AI assistant on-premises or in a private cloud ensures your data will not be used for public model training. Every interaction is logged, encrypted, and subject to strict access controls.
A comprehensive governance policy defines roles and permissions, ensures prompt traceability, and integrates content filters to prevent inappropriate use.
Access Control Mechanisms and Roles
To limit exposure of sensitive information, it’s essential to set granular permissions based on departments and hierarchy levels. Administrators must be able to grant or revoke rights at any time. Two-factor authentication (2FA) enhances access security.
A strong authentication system (SSO, MFA) locks down access and accurately identifies the user for each request. Permissions can be segmented by project or data type.
This granularity ensures that only authorized personnel can access critical features or document repositories, reducing the risk of leaks or misuse.
Logging, Encryption, and Audit Logs
All interactions are timestamped and stored in immutable logs. Requests, responses, and metadata (user, context) are retained to facilitate security and compliance audits. ACID Transactions guarantee the integrity of your critical data.
Data encryption at rest and in transit is secured by keys managed internally or via a Hardware Security Module (HSM). This prevents unauthorized access, even in the event of physical server compromise.
In the event of an incident, you have full traceability to reconstruct usage scenarios, assess impact, and implement corrective measures.
ISO 27001, GDPR, and FADP Alignment
The assistant’s architecture must meet ISO 27001 requirements for information security management. Internal processes include periodic reviews and penetration testing.
Regarding GDPR and the FADP, data localization in Switzerland or the EU ensures compliance with personal data protection obligations. Access, rectification, and deletion rights are managed directly within your platform.
Example: A Swiss public institution approved the implementation of an internal AI assistant aligned with GDPR, demonstrating that rigorous governance can reconcile AI innovation and citizen protection without compromising processing traceability.
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Control Your Costs and Integrate the Assistant into Your IT Ecosystem
Pay-as-you-go billing combined with team-based quotas offers immediate financial visibility and control. You can manage consumption by project and avoid unexpected expenses.
Native connectors (CRM, ERP, SharePoint, Confluence) and a universal API ensure seamless integration into your existing workflows, from document management to CI/CD.
Pay-as-You-Go Model and Quota Management
Deploying an internal AI assistant with usage-based pricing allows you to finely tune your budget according to each team’s actual needs. Costs are directly tied to the number of requests or volume of processed tokens.
You can set monthly or weekly consumption caps that trigger alerts or automatic suspensions if exceeded. This encourages responsible usage and helps you plan expenditures.
Real-time consumption monitoring provides visibility into usage, facilitates cost allocation across departments, and prevents end-of-period surprises.
Interoperability and RAG on Your Repositories
Dedicated connectors synchronize the AI assistant with your internal systems (ERP, CRM, DMS). They feed the knowledge base and ensure contextualized responses via RAG. To choose the best technical approach, see Webhooks vs API.
Every new document uploaded to your shared spaces is indexed and available for instant queries. Existing workflows (helpdesk tickets, CRM tickets) can trigger automatic prompts to accelerate request handling.
Example: A Swiss manufacturer integrated the assistant into its ERP to provide production data extracts in natural language. This demonstrated RAG’s impact in simplifying key indicator retrieval without custom report development.
Scalability, Sandbox Environments, and Rapid POCs
To test new use cases, a dedicated sandbox environment allows experimentation with different models (text, vision, voice) without affecting the production platform. You can measure result relevance before committing to a global deployment.
The modular architecture guarantees the ability to switch AI providers or adopt new algorithms as technological advances emerge, avoiding vendor lock-in.
Support for multilingual and multimodal models paves the way for advanced use cases (image analysis, voice transcriptions), enhancing the solution’s adaptability to your evolving business needs.
Make Your Internal AI Assistant a Secure Performance Lever
A well-designed and governed internal AI assistant combines productivity gains, risk control, and cost management. It integrates seamlessly into your ecosystem, is built on proven security principles, and evolves with your needs.
Your teams have access to a simple, 24/7 tool that automates repetitive tasks, improves response relevance, and secures interactions. You thus benefit from a contextualized AI solution that meets standards and adapts to future challenges.
Our experts can help you frame the architecture, define governance, oversee your MVP, and industrialize business use cases. Together, let’s transform your internal AI assistant into a performance and innovation engine for your organization.
