Connected business systems
Connect the sources that matter, including AFAS, SAP and other business applications. Select the required data and actions for each integration.
AILTITUDE ATLAS
Trusted data. Your rules. Your expertise. Atlas brings them together in your own private cloud, ready for the AI environments your team and customers use.
ONE FOUNDATION. MORE CONNECTIONS.
Your business, made ready for AI.
YOUR PRIVATE ATLAS ENVIRONMENT
Feedback → review → better knowledge
You decide who can access which data and tools.
YOUR CHOSEN PLATFORMS
ChatGPT
Gemini
Meta Muse
Kimi
Claude
Mistral
ChatGPTGeminiMeta MuseKimiClaudeMistral01 / 06
Trusted data
Start with the sources you trust. Choose the records, documents and business tools your agentplugin is allowed to use.
A simplified view of Atlas. Connections and publishing routes are selected per use case and depend on platform support.
THE VALUE OF ATLAS
Your finance team needs a protected view of internal numbers. Your customers need current product information and useful advice. Business Plugins support employees. Customer Plugins serve business customers and consumers. Both draw on Atlas, with separate permissions and approved data and actions.
An agentplugin connects an AI application to your business data, expertise and services. Atlas is the platform that keeps the context, policies and expertise together. Connect additional AI platforms through the same business foundation.
INSIDE ATLAS
The connection is the visible part. These are the capabilities that make it work for your business.
Knowledge & skills
Maintain approved instructions, source context and reusable expertise. Organise ownership and access by team or department.
Policies & tone of voice
Define the rules, escalation points and language your agentplugin should use. Test them against realistic situations.
Users & permissions
Manage user and service identities, department access and the tools each identity may use.
A private cloud foundation
Run Atlas in a dedicated environment. Keep the business foundation separate from the model or AI application you choose.
Monitoring & registry
Keep track of active tools, connector and MCP versions, permissions and usage. Make activity visible for operational review.
Feedback & improvement
Collect feedback, identify weak answers and improve the underlying instructions. Review changes before they become the new standard.
Cost visibility
Understand usage and the cost of the selected services. Set operational limits and agree how consumption is reviewed.
Modular & portable
Add capabilities as your needs grow. Agree export formats for your data, knowledge and configuration so you retain a practical exit route.
Atlas uses established integration standards, including MCP where appropriate. The technical connection sits inside the wider controls, knowledge and operating model.
FROM SETUP TO LAUNCH
You bring the business goal. We connect the sources, configure access, prepare the knowledge and build the platform-specific experience.
- Connect & configure. Select sources, users, policies and the AI environment.
- Build & test. Check the answers, actions, permissions and user experience.
- Submit & launch. We manage submission and review responses where a platform offers a publishing route. The platform makes the final approval decision.
- Maintain & improve. Keep the integration and knowledge aligned as your business and the platforms change.
Start with one useful application. Build on the same foundation.
Contact usGOOD QUESTIONS
Is Atlas just an MCP connector?
Atlas combines connectivity with a private environment, business context, policies, reusable expertise, access controls and an operating process.
Do we share an Atlas environment with other customers?
Atlas is designed around a dedicated private cloud environment for your business, separate from other customers’ Atlas environments. We agree the hosting, access and operational responsibilities during setup.
Do we need a different backend for every AI platform?
Atlas is the common business foundation. Each selected platform may need its own adapter, interface and publishing process, but the company knowledge and controls are managed together.
Which AI platforms can we connect to?
We assess the platform against your use case, security requirements and the integration routes it supports. The logos illustrate the platform landscape. Available functionality and publishing routes vary by platform.
Do you handle publishing and approval?
We prepare and submit the agentplugin where submission is supported, handle review feedback and support launch. Approval and availability are controlled by the platform.
How does learning work?
Feedback and usage reveal where instructions, sources or workflows need improvement. Changes are reviewed and tested before release. Training external models on company data requires separate permission.