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Integrate AI into Existing Software and Business Workflows

We integrate artificial intelligence into your existing business software – from ERP and CRM systems to custom enterprise applications. With secure APIs, clear access controls, and reliable workflows, we make AI capabilities useful in everyday operations.

AI IntegrationSystem IntegrationAI APIsERP IntegrationCRM IntegrationEnterprise Software
Discuss Your AI Integration
Two developers discuss integrating AI into existing ERP, CRM, and business systems
AI-generated
USE CASES

Where we can help

Typical challenges we can explore for your business.

01

Integrate AI into Existing Business Software

Employees should be able to use AI without switching between multiple applications. APIs can integrate AI capabilities into existing business software, for example to summarize information, prepare data entries, or support individual workflow steps.

02

Connect AI to Company Knowledge Securely

Important information is often distributed across documents, databases, and internal systems. AI-powered search can retrieve approved content and provide relevant context for responses while respecting existing access permissions.

03

Connect AI with ERP and CRM Systems

AI can prepare information from requests or documents for further processing in ERP or CRM systems. APIs, validation rules, and defined approval processes help prevent uncontrolled changes to business data.

Start with Your Existing Systems

An AI feature needs accessible data and a clearly defined place within an existing business workflow.

We analyze your current APIs, authentication mechanisms, data models, and operational requirements. The goal is to identify a focused use case with clearly assigned responsibilities.

Rather than introducing disconnected AI tools, we evaluate how artificial intelligence can become a useful part of your existing software environment.

Possible AI Integration Approaches

A dedicated API layer can manage AI model requests, validate access permissions, and deliver results to your existing business applications.

For AI-powered search across company knowledge, a separate search index may be appropriate. Document-level access permissions must also be enforced when retrieving information.

Depending on your requirements, AI capabilities can be connected to ERP systems, CRM platforms, or custom enterprise applications.

We evaluate the appropriate integration architecture individually for each project.

Quality Assurance Before Deployment

Together, we define representative test cases, requirements for information sources, and fallback procedures.

AI-generated responses are not automatically correct. Critical changes to business data require explicit approval.

After deployment, operating costs, response times, and output quality should be monitored continuously.

Reliable AI integration also requires clear responsibilities for handling errors and reviewing uncertain results.

A Step-by-Step Approach

  1. System assessment: Review existing software, interfaces, data sources, and technical requirements.
  2. Technical prototype: Validate the proposed integration approach.
  3. Business evaluation: Assess output quality, security requirements, and operational suitability.
  4. Integrated pilot: Test the AI functionality within an existing application or workflow.
  5. Production deployment: Establish monitoring, maintenance, and operational responsibilities.

We determine the specific requirements for your systems during an initial consultation.

For additional guidance, read our AI Integration Guide.

If your existing technical infrastructure needs to be updated first, our Software Modernization services may provide a suitable starting point.

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What would you like to move forward?

Improve an existing application, build something new or simplify processes with AI? Tell us about it.