You will get an AI-powered symptom checker and health risk tool for pets
Project details
AI-Powered Pet Care: Risk Assessment & AI Engine
Turn raw pet data into proactive health insights. In the pet-tech industry, tracking is no longer enough. This project offers a data-driven Risk Assessment Model designed to identify health vulnerabilities before they become emergencies. Whether for a vet portal, wearable integration, or nutrition app, this AI transforms biometrics into actionable, veterinary-informed insights.
What This Project Delivers:
Dynamic Risk Scoring: A logic engine calculating a 0–100% "Safety Score" based on age, breed, weight, and activity trends.
Intelligent Recommendations: Automated action plans—from "Optimize Diet" for healthy pets to "Urgent Vet Visit" for high-risk profiles.
Multi-Scenario Analysis: Calibrated for breed-specific risks and environmental stressors.
Tier Breakdown:
Starter: Foundational script for baseline health audits.
Standard: Multi-scenario testing, behavioral trends, and detailed reporting.
Advanced: Enterprise integration, real-time connectivity, and UI mockups.
Stop guessing and start predicting. Let’s build a safer future for pet care together.
Turn raw pet data into proactive health insights. In the pet-tech industry, tracking is no longer enough. This project offers a data-driven Risk Assessment Model designed to identify health vulnerabilities before they become emergencies. Whether for a vet portal, wearable integration, or nutrition app, this AI transforms biometrics into actionable, veterinary-informed insights.
What This Project Delivers:
Dynamic Risk Scoring: A logic engine calculating a 0–100% "Safety Score" based on age, breed, weight, and activity trends.
Intelligent Recommendations: Automated action plans—from "Optimize Diet" for healthy pets to "Urgent Vet Visit" for high-risk profiles.
Multi-Scenario Analysis: Calibrated for breed-specific risks and environmental stressors.
Tier Breakdown:
Starter: Foundational script for baseline health audits.
Standard: Multi-scenario testing, behavioral trends, and detailed reporting.
Advanced: Enterprise integration, real-time connectivity, and UI mockups.
Stop guessing and start predicting. Let’s build a safer future for pet care together.
Machine Learning Tools
BERT, GitHub Copilot, GPT-3, MATLAB, MLflow, NumPy, pandas, PyMC, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, Sonnet, SQL, Tableau, TensorFlow, Vertex AI, XGBoostWhat's included
| Service Tiers |
Starter
$350
|
Standard
$550
|
Advanced
$600
|
|---|---|---|---|
| Delivery Time | 2 days | 5 days | 11 days |
Number of Revisions | 1 | 3 | 7 |
Number of Model Variations | 1 | 2 | 7 |
Number of Scenarios | 1 | 3 | 8 |
Number of Graphs/Charts | 2 | 4 | 10 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code | - | - |
About Fatika
ML Engineer | Building Models for Veterinary and Agriculture
Zaria, Nigeria - 1:09 pm local time
My work sits at the intersection of data science and domain expertise. I've built predictive models for livestock yield forecasting using breed-specific parameters, survival analysis models for clinical risk scoring, and fine-tuned deep learning classifiers. Everything I build gets shipped not just notebooks.
What I work with:
- Supervised learning (regression, classification, survival analysis)
- Fine-tuning pretrained models (ResNet, LLMs via QLoRA)
- Python, scikit-learn, XGBoost, PyTorch, HuggingFace
- Deployment via Streamlit + HuggingFace Spaces
I bring veterinary and biological domain knowledge to projects where most data scientists don't. That means better feature engineering, more realistic synthetic data, and models that actually make sense for the problem.
Steps for completing your project
After purchasing the project, send requirements so Fatika can start the project.
Delivery time starts when Fatika receives requirements from you.
Fatika works on your project following the steps below.
Revisions may occur after the delivery date.
Step 1: Data Intake & Requirement Gathering Description:
Description: I will review the specific pet metrics and health parameters you provided. We will hop on a brief kickoff message to confirm the specific "Red Flag" triggers and breed-specific risks you want the model to prioritize.
Step 2: Core Logic Development & Scripting
Description: I build the Python-based logic engine (or Excel framework for Starter tiers). This involves setting up the scoring algorithms that weigh age, weight, and activity level to generate the 0–100% "Safety Score."