We first dig into your real venture problem as opposed to jumping directly to model selection. Then we clean your data, fashion and develop, merge everything into your current systems, and stick with post-launch support so nothing falls apart during the build.

Smaller focused builds ship in six to eight weeks if the data is clean and the scope is tight. Bigger enterprise projects with multiple models and deep integrations take anywhere from three to five months and that timeline shifts based on how ready your data actually is when we start.

Healthcare and medical diagnostics platforms

• Fintech and fraud detection systems
• Retail and eCommerce personalisation engines
• Logistics and supply chain forecasting tools
• Construction and temporary maintenance operations

Honestly, it depends on what you are actually building. We sit down with you first, understand the data you have, the models you need, and how deep the integration goes before putting a number on it. That way the quote reflects your project and not someone else's.

We work with both high-growth startups and large-scale enterprises

• Startup builds focus on lean and fast-to-deploy ML systems
• Enterprise projects cover complex multi-model deployments
• We scale the team size and infrastructure to match your stage
• Both get the same level of engineering quality and post-launch support

Direct integration into CRMs, ERPs, and mobile applications

• No full infrastructure rebuild required on your end
• API based connectors for web and third-party platforms
• Zero disruption to your current workflows during integration
• Full testing across edge cases before any go-live handover

What tools and technologies are you running to improve ML?

• TensorFlow, PyTorch, Keras, and Scikit-learn for publication
• AWS SageMaker, Azure ML and Google AI Platform for Cloud Deployment
• Apache Spark and BigQuery for Large Record Processing

We do not use generic model templates or hand off work between disconnected teams. Every system is built around your specific data, your industry requirements, and your actual business goals from the first discovery call through to long-term post-launch support and scheduled retraining.