One Putt Pro: AI-Powered Golf Putting Device

We do both. For complex, domain-specific challenges, we build models from scratch. For faster deployments, we adapt pre-trained models using transfer learning or fine-tuning, depending on your data and goals.

AI projects require structured or unstructured data relevant to the problem—this could include sensor data, images, audio, videos, text logs, or tabular datasets. We assist with data assessment, cleaning and augmentation if needed.

Yes, we can deploy AI on both. For real-time or offline use cases, we optimize models to run on edge devices like mobile phones, embedded boards, or wearables. We also offer cloud-based options for heavy computing or centralized access.

Yes, our chatbots are designed for seamless integration with your current systems, including CRM, ERP, and other business tools, ensuring a unified and efficient workflow.

We use industry-standard evaluation metrics (e.g., precision, recall, F1-score) and iterative validation to ensure high accuracy. We also run stress tests in real-world environments and continuously improve models based on live data.

Yes, integration is a core part of our delivery. We build flexible APIs, SDKs, or direct software connectors to seamlessly plug AI into your existing platforms or devices.

Absolutely. We offer post-deployment support, including model monitoring, performance tuning and retraining if new data trends emerge. Our goal is to keep your AI solution relevant and effective over time.

That’s something we help evaluate. If rule-based systems or automation can solve the problem, we say so. But if the problem involves patterns, predictions, or personalization at scale, AI is often the best fit.

We follow industry best practices for data security and adhere to regulations like GDPR and HIPAA where applicable. We also offer anonymization and on-premise deployments for sensitive data scenarios.