AI Integration & Deployment

Whether you’re integrating a language model into a customer support platform, embedding machine learning into decision-making processes, or deploying computer vision for real-time data extraction, we ensure your AI solution is production-ready, scalable, and aligned with business goals.

From planning and architecture to deployment and monitoring, we make AI real — not just a concept.

Understanding AI Integration & Deployment

AI isn’t useful in isolation — it needs to be embedded where it can drive real outcomes. That’s where integration and deployment come in. A powerful model is only valuable when it’s connected to the right data, triggered by the right events, and surfaced through intuitive interfaces.

At 6B, we specialise in integrating AI solutions into the systems your teams already use — CRMs, ERPs, internal tools, cloud platforms, and customer-facing applications. We connect models to live data sources, build APIs and orchestration layers, and ensure AI is deployed in a secure, compliant, and monitored environment.

We work across a wide range of AI capabilities, including natural language processing (NLP), predictive analytics, computer vision, recommendation engines, and process automation. Our goal is always the same: seamless AI integration that delivers immediate business value and long-term operational resilience.

Whether you’re experimenting with generative AI or scaling an existing ML model into production, our team provides the technical leadership and delivery expertise to get it done — the right way.

Our AI Integration & Deployment Approach

Our work begins with clarity. We collaborate with your team to understand the systems you already have, the data they generate, and the business processes you want to enhance with AI.

From there, we design an integration architecture that fits your environment — whether cloud-native, hybrid, or on-premise. We evaluate the best tools and models for the job, manage environment setup, and connect AI capabilities to your internal systems through secure APIs, automation workflows, or user-facing components.

Our engineers handle model packaging, containerisation (e.g. using Docker or Kubernetes), and CI/CD pipeline integration to support ongoing model updates. We build robust monitoring and observability into every deployment — tracking performance, usage, and drift over time so your AI continues to improve.

Deployment is not the end — it’s the beginning of value delivery. We ensure your solution is not only functional, but maintainable, testable, and aligned with your broader infrastructure strategy. And if your team needs support scaling or optimising post-launch, we’re right there with you.