Handit.AI Documentation

AI model deployment and management often fall short of delivering the expected business outcomes, with up to 80% of AI projects never scaling beyond pilot stages. To address this challenge, Handit.AI provides a comprehensive AI Lifecycle Management Platform that ensures AI models are continuously aligned with business goals and KPIs.

Handit.AI includes a robust tracking system that enables businesses to effectively monitor and optimize AI models in production. With seamless integration into your existing workflows, the platform automates the tracking of AI inputs and outputs, ensuring that models are continuously optimized and their performance remains aligned with key business objectives.

What Handit.AI Offers:

1. Continuous Monitoring of AI Models
   Detect performance degradation and data drift in real-time, ensuring your models remain accurate and reliable.
2. Automated Data Capture
   Handit.AI intercepts HTTP requests (via Axios and Fetch) to automatically track model inputs and outputs, streamlining the tracking process without requiring manual intervention.
3. Business KPI Alignment
   By capturing AI model inputs and outputs, Handit.AI provides the critical data needed to align model performance with your business’s strategic objectives.
4. Seamless Integration
   The platform easily integrates into your existing AI infrastructure, supporting popular tools such as Amazon SageMaker and TensorFlow, reducing complexity and accelerating time to value.
5. Custom AI Model Tracking
   Manually capture AI model events when required, ensuring that no critical data is missed, and that all aspects of your AI systems are monitored effectively.

Why Use Handit.AI?

Handit.AI is designed to solve the fundamental issues AI projects face—disconnection between models and business goals, performance degradation, and lack of continuous optimization. By integrating our tracking tools, your AI models become transparent and measurable, allowing you to fine-tune them to your specific business needs and drive long-term success.

Key benefits include:

• Improved AI ROI: Directly connect model performance to business outcomes, ensuring that your AI initiatives deliver the value they promise.
• Proactive Issue Prevention: Identify performance issues and data drift before they escalate, allowing for rapid optimization.
• Reduced Time to Market: Automate much of the manual work required to monitor and optimize AI models, accelerating the deployment process.