Technical problem
The previous-generation ERP, CRM, mainframe or bespoke database systems a business has run for years — the ones at the centre of its workflows — cannot technically accommodate AI integration.
Legacy system modernisation and intelligent API layers
Architectural solution
Without disturbing the core architecture of the existing systems or stopping them, we weave modern RESTful or gRPC-based API services and adapter layers on top. Event-driven architectures (Kafka, RabbitMQ) turn data flow real-time, and the irregular data coming out of legacy systems is transformed into AI-ready schemas the models can work with.
Operational outcome
Modern AI capability added to systems already running, at zero risk and with no interruption, and without having to replace software infrastructure worth millions.
II
Software adaptation, legacy systems and microservice architecture
Two-way AI integration across departments and business softwareAI stays a static chat window that only produces text, and never turns into action inside the business software already in use — HR, sales, operations, finance.AI-ready microservice and distributed system architectureMonolithic AI applications collapse under heavy user load or sudden traffic spikes, cannot scale, and take the rest of the system into deadlock with them.
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Which one shall we start with?
See it on your own data in one session, or write first and ask what we do.