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AI & Big Data Services and Solutions

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Recognization Systems

Include image, sound, text and behavior recognization


Recommendation Systems

Include product, service, person and place recommendation


detection system
Pattern Detection Systems

Include but not limit to fault and risk pattern such as anti-money laundering and financial risk predicting 


Industry-Standard Technologies

Deliver your ideas into impactful and scalable products.

Tesseract always applies proven and production-grade technologies and frameworks to build AI-based systems

How we Help you Succeed

Build AI Models & Software Systems

There are always two separate stages involved in an AI system: 1. Build AI models based on the training & test data 2. Deploy them to a scalable software system for production ready

Data Collection

Data preparation is one of the most important aspects of creating a useful AI/ML project. Various forms of data: image, sound, text, statistics data

Data Labeling

This may include but is not limited to tagging a picture, identifying a name in a sentence, or summarizing the sentiment in a body of text.

Feature Extraction

Based on the categories within your dataset, you can choose which features are best suited to train your model

Model Building

After building a feature set using neural network architecture (deep learning), you can train and validate your model

Model Deployment

Getting models into production can be difficult and challenging. After a model is trained, it will be deploy to an AI infrastructure such as AWS or GCP.

Model Monitoring

Once a model has made it into production, it must be monitored in order to ensure that everything is working properly