System and data analysis
We review available APIs, data structures and system limitations, and agree which data and operations to expose to AI.
AI services
AI integration with ERP and CRM
We deliver AI integration with ERP, CRM, WMS and your other business systems. We connect models such as ChatGPT and Claude to your data via APIs and the Model Context Protocol – without replacing software, with permission control and data security.
Why AI needs to be integrated with your business systems
Access to ChatGPT alone is not enough for AI to genuinely support your processes. The model does not know your stock levels, customer history, price lists or order statuses. So employees copy data between windows, and AI answers stay generic and hard to verify.
Integrating AI with ERP and CRM means artificial intelligence works on up-to-date company data and can act in your systems – within the permissions it is given. AI in CRM suggests next steps to sales reps, while AI in ERP prepares documents, analyses orders and spots irregularities.
Your existing systems stay where they are. AI becomes an additional layer that automates and supports day-to-day processes.
What your company gains
- AI answers based on up-to-date ERP and CRM data.
- Less retyping of data between systems.
- Automatic preparation of documents, quotes and reports.
- Control over which data AI can access.
- No need to replace your existing software.
Integrating ChatGPT with your business system – scope of work
We integrate AI models with off-the-shelf and custom systems – via APIs, databases, event queues or file exchange.
Connectors and APIs
We build secure connectors to ERP, CRM, WMS and other systems, plus a middleware layer that controls access.
Model Context Protocol (MCP)
We expose company data and tools to AI models via the MCP standard, making it easier to evolve and swap models in the future.
AI in CRM
Customer history summaries, next-step suggestions, drafting messages and quotes, and lead classification.
AI in ERP
Document entry, order and stock analysis, anomaly detection and natural-language reports.
Security and audit
Role-based permissions, query and operation logging, masking of sensitive data and GDPR compliance.
How AI integration with ERP and CRM works
We deliver the integration in stages, starting with a use case that brings quick results and lets us validate the architecture.
Consultation and use case selection
We agree in which process AI should work on ERP or CRM data and what outcome we want to achieve.
Technical analysis
We verify APIs, data access, security and performance requirements.
Connectors and prototype
We build the connectors and an integration prototype and test it on real data.
Rollout
We launch the integration in production, with monitoring, logging and an error-handling procedure.
Growth
We add further AI use cases, reusing the connectors already built.
Technologies
Integration technologies
We build integrations in Python, Java and Node.js using REST APIs, event queues and the Model Context Protocol. We work with PostgreSQL, MariaDB and MS SQL Server databases and with OpenAI and Anthropic models running on Microsoft Azure, AWS or Google Cloud.
- Model Context Protocol
- REST API
- OpenAI
- Anthropic
- Python
- Java
- Node.js
- PostgreSQL
- MariaDB
- MS SQL Server
- Microsoft Azure
- AWS
Example use case
An AI assistant for sales reps integrated with CRM and ERP
Before every meeting, sales reps at a manufacturing company review the customer’s history in the CRM, orders and receivables in the ERP, and notes from previous meetings.
After the integration, an AI assistant prepares a short customer summary: recent orders, open issues, payment terms and suggested discussion topics. On request it drafts a message or creates a CRM task. Data access is limited to the customers assigned to each sales rep.
An illustrative scenario showing the typical course and scope of such a project.
Frequently asked questions
Can ChatGPT be integrated with our ERP system?
Yes, if the system provides an API, a database or another way of exchanging data. We build a middleware layer that controls which data and operations the AI model can access.
What is the Model Context Protocol (MCP)?
It is an open standard for giving AI models access to data and tools. With MCP, connectors built once can work with different AI models and agents.
Does AI integration require changes to our existing systems?
Usually not. We use existing interfaces. If a system has none, we propose a secure alternative, such as a read-only data replica.
How do you protect data when integrating AI with CRM?
We use role-based permissions, masking of sensitive data, query logging, and models running in the cloud under a data processing agreement or on your own infrastructure.
Which systems have you integrated?
We integrate off-the-shelf and custom systems – ERP, CRM, WMS, TMS, online stores, banking systems and document workflows. We agree the details during the technical analysis.
Experience since 2009, now powered by AI
Since 2009
17 years of building enterprise-class web applications, custom business systems and mobile apps.
Industry know-how
Many projects for automotive, logistics, healthcare, food service and catering, construction and finance.
From idea to maintenance
Consulting, design, development, integrations, rollout, training and ongoing growth in one place.
Data security
Solutions designed in line with GDPR and the EU AI Act, with access control and transparent costs.