DoCoreAI: LLM Observability, AI Prompt Optimization & ROI vs Magika
Overview
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CLI (Node.js)
Manual
Detailed Comparison
It leverages the power of cutting-edge deep learning to enhance the world of file type detection. It provides increased accuracy and support for a comprehensive range of content types, outperforming traditional tools with 99%+ average precision and recall. | LLM observability without data leaving your company network. AI Prompt Optimization, cost analysis & ROI (15 reports). Pro-version Free for 4 months. |
Available as a Python command line, a Python API, and an experimental TFJS version;
Trained on a dataset of over 25M files across more than 100 content types;
Achieves 99%+ average precision and recall, outperforming existing approaches;
After the model is loaded (this is a one-off overhead), the inference time is about 5ms per file | Save on AI Costs: Reduce waste and cut token expenses., Easy-to-Read Reports: Visual dashboards to track usage, savings, and trends., No Coding Needed: Simple web interface—connect your token key., Prompt Improvement Tips: Get clear suggestions to write better prompts., Plan Your Budget: Forecast future AI expenses with confidence. |
Statistics | |
GitHub Stars 8.9K | GitHub Stars - |
GitHub Forks 454 | GitHub Forks - |
Stacks 0 | Stacks 0 |
Followers 2 | Followers 1 |
Votes 0 | Votes 1 |
Integrations | |
| No integrations available | |
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