Frequently Asked Questions

Legacy system modernization is the process of updating older software systems to modern standards while preserving their core functionality and data. This can include adding API layers to C/C++ applications, modernizing database architectures, enabling cloud capabilities, or integrating AI.

The goal is to extend the life and capabilities of mission-critical systems without the risks of complete replacement.

According to industry research, 70% of rip-and-replace IT projects fail or significantly exceed budget. Legacy systems often contain decades of embedded business logic that is difficult to replicate.

Modernization preserves this institutional knowledge while adding new capabilities. It's typically 40-60% less expensive than full replacement, carries lower risk, and can be done incrementally without disrupting operations.

Project timelines vary based on system complexity:

• API wrapper for legacy database: 2-4 weeks
• Mid-size enterprise system: 3-6 months
• Large-scale system migration: 12-24 months

We use an incremental approach, delivering value in phases rather than waiting for a big-bang deployment.

Core legacy expertise: C, C++, Assembly—the languages that power critical infrastructure worldwide.

Legacy databases: Oracle, DB2, Microsoft Access, SQL Server, custom flat-file systems

Modern stack: Python, Node.js, AWS, Azure, GCP, LangChain, vector databases, LLM integrations

That's often exactly why clients call us. We've spent 35 years working with systems that:

• The original developers have long since retired
• Have minimal or no documentation
• Other consultants have given up on
• Contain databases with millions of records spanning 15+ years

We dig deep into C, C++, and Assembly to understand what's really happening and find solutions.

Yes. We specialize in bridging legacy systems with modern AI. This typically involves:

• Creating API middleware layers for legacy-AI communication
• Adding natural language interfaces to legacy databases
• Implementing intelligent automation for existing workflows
• Deploying AI-powered analytics without modifying core legacy code

According to Gartner, 85% of enterprise AI projects fail to reach production. The main reasons:

• Poor integration with existing systems
• Lack of quality data
• Unrealistic expectations
• Insufficient focus on compliance and governance

We address these by focusing on robust, compliant AI that integrates seamlessly with your existing infrastructure.

We focus on responsible, robust AI integration. This means:

• AI that works with existing systems and people, not against them
• Explainable AI solutions with clear decision trails
• Regulatory compliance (especially Quebec's Law 25)
• Proper guardrails, monitoring, and graceful degradation
• Enhancement of human decision-making, not replacement of human oversight

We work primarily with enterprises that rely on critical C/C++ infrastructure:

• Financial services & banking
• Insurance
• Healthcare
• Manufacturing
• Government & public sector
• Utilities & energy

These sectors often have mission-critical systems built over decades that need to evolve without disruption.

Security is paramount. We implement:

• Strict NDAs and enterprise-grade security practices
• Encryption for data in transit and at rest
• Detailed audit logs
• Isolated development environments
• Industry compliance (SOC 2, HIPAA, PCI-DSS as applicable)

We never store or retain client data beyond project requirements.

BJPR Internet Technologies is headquartered in Montreal, Quebec, Canada. We serve clients across Canada and can work remotely with enterprises worldwide.

For local Quebec clients, we provide on-site support when required for sensitive systems.