Proprietary

AI Architecture

We don't just "connect APIs." We build custom Computer Vision and LLM pipelines, from raw data annotation to production ready deployment.

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OUR PROCESS

Strategy, Train and Deploy as an effective complete solution.

Multi modal data ingestion and high precision labeling for niche industries.

Fine tuning architectures like YOLO, SAM, and DINO for object detection. We have further tools for different detections.

Integrating AI outputs with complex codes (IRS Tax, Engineering Standards).

Building the Flask/React infrastructure to deliver AI insights to your users.

Our latest Case Study

I’M A SUNGLASSES INFLUENCER

This is a Cost Segregation Detection tool project. It shows We can deliver $50k+ value

The Challenge:
An STR (Short Term Rental) specialist spent 10+ hours per property manually identifying assets from photos for tax depreciation.

 

The HusQuay Solution

  • Vision: YOLOv8 + Segment Anything (SAM) for granular classification of property assets (Appliances, Flooring, HVAC).

  • Intelligence: GPT-4o Vision for metadata validation and quality control.

  • Engine: Custom Python engine mapping identified assets to 5, 7, and 15-year IRS depreciation life cycles.

 

The Result

  • 98% Reduction in processing time.

  • 96% Accuracy in automated classification.

  • Audit-Ready reports generated in minutes.

Why "Custom Built" Over "Generic AI"?

Important roles

  • Domain Specificity → General AI (like ChatGPT) cannot identify a specific serial number or a tax eligible "15-year land improvement." Our models are trained for it.
  • Data Sovereignty → You own the weights, the model, and the training data. No third party dependency.
  • Zero Hallucinations → Built for high stakes industries where accuracy is a legal requirement.

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