AI Integration & Data Access
Integrate AI features into existing software without losing control over data, security or business rules.
- Connect ERP, CRM and custom databases to LLM-based assistants
- Develop MCP servers for structured and secure system access
- Build APIs and orchestration layers for agent-driven workflows
- Define guardrails for data access, permissions and auditability
Example problem: your support team wants an internal AI assistant, but data is spread across multiple systems with inconsistent APIs.
From AI Prototype to Production
Turn promising prototypes or vibe-coded tools into software that meets production standards.
- Codebase and architecture assessments
- Security, reliability and performance improvements
- Automated testing and release pipelines
- Operational support and maintenance planning
Example problem: a prototype demonstrates value, but it lacks testing, observability and deployment discipline.
Legacy Software Modernization
Modernize legacy applications step by step, reducing risk while improving development velocity.
- Incremental migration roadmaps
- Refactoring and modularization of critical components
- Stack upgrades and dependency stabilization
- AI-assisted code transformation with manual quality control
Example problem: core revenue workflows still run on outdated code that is expensive and risky to change.
Dedicated Software Engineering
Strengthen your team with senior engineers who can contribute immediately and take ownership.
- Senior full-stack engineering capacity
- DevOps, CI/CD and deployment engineering
- Test automation and QA collaboration
- Long-term support for business-critical platforms
Example problem: your roadmap is clear, but internal capacity is too limited to deliver safely and on time.
