Guaranteed sovereignty
Complete confidentiality
Agility & Customization
DigDash AI
Unlock the intelligence at the heart of your business and your data
Whether you’re in the public sector or at the heart of a private organization, get a head start with AI that complies with your security policies. Accelerate the implementation of AI in your day-to-day operations and boost your performance tenfold. What sets DigDash AI apart: our solution doesn’t just answer your questions—it understands and adapts to your business context.
Custom Demo
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Excel with cutting-edge AI
Provide your employees with the best AI for results that are both fast and high-quality. Our AI is customizable and adaptable to your business lines and operations. It integrates easily with your existing tools and can be deployed at scale. Whether you have 10 or 10,000 users, our architecture is designed to handle massive scalability without any loss in performance.
Expert Discussion
Search your document collection.
Fluid Generation
Create your content and reports in the blink of an eye.
Augmented Analysis
Uncover the hidden trends in your data.
Delegated Execution
Automate your workflows and repetitive tasks.
Solutions to Your Business Challenges
Powerful, intuitive, and easy to use, DigDash AI integrates seamlessly with your existing suite of tools. More than just a conversational assistant, it also enables you to move from information to decision-making with complete reliability.
Specialized Chatbot
Get reliable answers based on your own knowledge bases (RAG).
From strategic emails to report summaries, produce high-quality documents instantly.
Instantly create and edit the visuals you need.
Automation
Create smart workflows by delegating time-consuming tasks.
Provide your employees with an intuitive interface, regardless of their level of experience.
Create autonomous AI agents to allow your “human agents” to focus on strategic or high-value-added tasks.
The DigDash AI Agent
Data visualization and key metrics generator. Ask a question about your data (“Why is my revenue declining in the PACA region?”) and let the agent extract the relevant metrics and turn them into an appropriate visualization.
AI isn't just a gimmick—it's the intelligent engine behind your DigDash BI platform.
Generic Chatbot
Summarize reports or instantly translate your content while maintaining the appropriate tone.
Generate ideas, develop action plans, or get reliable answers to questions.
Generate, correct, or optimize code (SQL, Python, JavaScript, etc.) to speed up your projects safely.
Automated Workflow
Highly secure hosting
DigDash AI adapts to your strategic constraints through flexible deployment options designed to meet the most stringent requirements for security, performance, and compliance.
On-Premise - Full Control Over Your Infrastructure
Deploy DigDash AI directly on your infrastructure to maintain complete control over your data assets. This solution allows you to optimize your hardware resources (CPU/GPU) while ensuring total confidentiality of your information and full compliance with your internal security policies.
Sovereign Cloud - Agility, Power, and Compliance
Take advantage of a scalable infrastructure without the need for significant hardware investment by choosing to deploy with our French cloud partners (OVHcloud, Cloud Temple). This option ensures that your data is hosted within the European jurisdiction, offering you complete protection against extraterritorial laws while allowing you to take advantage of the latest technological innovations.
Hybrid: The Balance Between Performance and Safety
Combine the computing power of the cloud with the privacy of on-premises solutions. This custom architecture allows you to distribute your processing tasks based on their sensitivity: use the sovereign cloud for the scalability of AI models and keep your most critical data in your own digital “vault.”
Our strengths aren't just words—they're concrete actions
The AI market is full of promise, but few solutions combine power, reliability, and rigorous security. DigDash AI was built on a solid foundation and strong commitments.
Sovereignty and Compliance
- Legal safeguards and sovereign cloud: Hosting in Europe isn’t enough. Take advantage of infrastructure operated by French or European entities for complete protection against extraterritorial laws.
- Compliance and Sensitive Data: Choose DigDash AI with confidence—a GDPR-compliant solution available on SecNumCloud- and HDS-certified environments.
Total flexibility
- Flexible infrastructure options: Deploy your solution on-premises, in a trusted cloud, or in a hybrid environment, depending on your security requirements and technical constraints.
- Customized Business AI: Create specialized assistants for each department (Finance, HR, Sales, etc.) that are seamlessly integrated with your existing software and tools.
Smart Data Access
- DigDash AI Agent: Query your data assets using natural language—regardless of your line of work—to get immediate and reliable answers.
- Actionable Visualizations: Generate accurate analyses and real-time charts without requiring technical skills or complex queries.
Performance and Continuous Improvement
- Rigorous Selection of LLMs: Benefit from continuous monitoring that incorporates the highest-performing, most stable models specifically tailored to each business use case.
- Industrial scalability: Rely on a robust, optimized architecture capable of supporting large-scale deployments without any loss of performance.
Expertise and Close Relationships with Software Vendors
- Collaborative Roadmap: Play an active role in shaping the solution's evolution alongside an R&D team that listens to your strategic challenges and specific needs.
- Direct Support: Take advantage of local, responsive, and expert assistance through a direct connection with the French software publisher’s teams.
Digital Responsibility
- Efficiency and technological simplicity: While an LLM consumes billions of clock cycles for a single operation, we prioritize CPU-based computation optimized for common tasks in order to limit intensive use of GPU resources.
- AI Without Overkill: We deploy a streamlined architecture that selects the model best suited to each business need, thereby avoiding energy waste and ensuring sustainable performance.
Ready to put DigDash AI and your team to work?
Contact us today. Our team will provide you with a personalized demonstration of DigDash AI tailored to your business needs.
Frequently Asked Questions
Find answers to the most common questions about DigDash AI.
To what extent is DigDash AI actually protected against the Cloud Act?
The Cloud Act and the FISA Act apply to U.S.-based companies (such as Google, Microsoft, Amazon, and Meta). These laws, known as extraterritorial laws, allow the U.S. government to access data held by U.S. hosting providers regardless of the location of their data centers. For its European customers, Digdash hosts all of its cloud services on infrastructure controlled by European companies (OVHCloud, CloudTemple, OutScale, etc.).
What legal safeguards do a 100% French publisher and web host offer?
The general framework of French law requires compliance with laws and regulations such as the GDPR, NIS2, and the Intellectual Property Code. This framework ensures compliance with personal data protection and intellectual property rights, as well as the resilience of information systems against cyberattacks and various incidents.
In addition, Digdash addresses more specialized requirements through its ISO 27001 certification, while also offering greater flexibility in data processing obligations through the implementation of a Data Processing Agreement (DPA).
Is my business data being used to train public AI models?
When using the DigDash AI platform, including the LLM and embedding model components “as a service,” no data is retained or used for model training.
What certifications (SecNumCloud, HDS) are available for sensitive data?
The servers used by the DigDash AI platform can be operated on SecNumCloud- and HDS-certified hosting platforms.
For the GPU infrastructure (used for LLM inference and embedding models), this can be done in a SecNumCloud environment.
What is the RAG, and what is it used for?
RAG (Retrieval-Augmented Generation) is a technique that allows an AI to consult external documents before responding. This is used to provide up-to-date information, avoid hallucinations, and specialize a conversational agent so that it can access information beyond what is contained in the knowledge base of the LLM being used.
What is the difference between an LLM and an AI agent?
An LLM (such as GPT-5.4, Gemini-Flash, or Mistral Small 3.1, etc.) is the “brain” capable of generating text and reasoning.
An AI agent is an autonomous system that uses LLMs to take action. The agent can use external tools (web searches, emails, code) to autonomously accomplish a complex task.
What is a "hallucination" in AI, and how does DigDash AI prevent them?
A hallucination is an error in which the AI generates false but credible information (often with a certain degree of confidence).
DigDash AI can avoid these issues thanks to RAG (Retrieval-Augmented Generation), the deployment of agents tailored to specific use cases (general-purpose conversational agents, specialized conversational agents, AI workflows), as well as through the engineering of system “prompts.”
Why does AI require GPU and CPU resources?
Part of the platform requires “traditional” CPU/RAM resources; these include the ChatBot/ChatAdmin components, the automation tool, and the vector databases.
LLMs and embedding models, on the other hand, require GPU infrastructure to run efficiently and quickly.
Is it possible to maintain a history and traceability of interactions with the AI?
Yes, it is possible to track activity—particularly within the chatbot—and grant administrators access to that data.
In some cases, users can manage their own conversation history.
What resources are required for an on-premises deployment?
You need to do both:
- Standard resources are required to run the ChatBot/ChatAdmin, the automation tool, and the vector databases. The minimum configuration is 12 vCPUs and 16 GB of RAM (subject to change depending on the complexity of the projects).
- and GPU infrastructure to perform inference on LLMs and embedding models.
In many cases, organizations will not have GPU infrastructure (too expensive, rapidly becoming obsolete); in such cases, they can install the DigDash AI platform on-premises and use “AI Endpoints” on a sovereign cloud platform, for example.
How does AI manage access rights and privacy based on user profiles?
User authentication will be required to access the ChatBot.
To access the DigDash AI Agent, the user will be prompted to generate and enter an access token once in the interface. This token will enable the DigDash AI Agent to determine the user’s permissions and scope within DigDash. Thus, the user will only be able to generate data visualizations and key insights from the data cubes for which they have read access (live security will apply by default).
Can the AI agent create real-time graphical visualizations?
Yes, or suggest a visualization that already exists and meets the user’s needs (saving tokens/resources).
The “freshness” of the data depends directly on the refresh rate of the data cube used in the rendering.
Can we customize specific assistants for each job role?
Yes, particularly thanks to vector-based data feeding with unstructured business data and the use of RAG.
What is the actual impact of AI on my infrastructure's energy consumption?
It’s difficult to answer, given the many factors to consider (number of users, prompts, quality of vector database input, LLM used, infrastructure, etc.).
By making full use of the DigDash AI platform, we will be able to provide information on token consumption (inputs/outputs). This can give us some idea of the impact (if we convert the token into energy consumption in Wh or CO₂ emissions, for example).
Can the AI integrate with my existing tools (ERP, CRM)?
Yes, thanks in part to the Digdash agent, which sets up access to your application data in advance, regardless of the source. This will allow you to query the data stored in your existing tools.