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We build AI/ML solutions that go beyond demos. Custom models trained on your data, integrated into your workflows, and delivering measurable results.
Technologies and Tools
Our Process
We evaluate your historical data for quality, volume, and bias. Good AI requires pristine data, and we help you clean it.
We choose the right architecture (Transformers, CNNs, Random Forests) and train the model using your proprietary datasets.
We rigorously test the model against holdout data, tuning hyperparameters to maximize accuracy and minimize false positives.
We deploy the model as a scalable API API, setting up monitoring to detect model drift over time.
Use Cases
Predicting inventory needs and sales trends for retail and manufacturing based on historical and external data.
Real-time anomaly detection models for financial institutions to flag suspicious transactions instantly.
Recommendation algorithms that increase average order value by showing users products they are highly likely to buy.
Analyzing sensor data to predict when industrial machinery will fail, preventing costly unplanned downtime.
Deliverables
Every AI / ML Development project comes with clear, tangible deliverables. No vague promises — just concrete output you can use, deploy, and build upon.
Why Zanvis
We don’t just implement generic APIs; we build custom mathematical models that solve specific, complex business problems.
Your data never leaves your environment. We train models securely on your infrastructure.
We optimize models using TensorRT and ONNX so they return predictions in milliseconds, not seconds.
AI models degrade over time. We build automated systems that alert you when the model needs retraining.
We don’t just chase accuracy scores; we optimize the model to maximize your actual business ROI.
We handle everything from data engineering to the final UI integration—you don’t need a separate team.
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Learn more →Tell us about your project and we will get back to you within 24 hours with a scope proposal and timeline.