Get Your Data AI Ready
Unstructured
Unstructured data is difficult to process and interpret without careful preparation.
Structured
AI benefits greatly from structured data, as it is organized and digestible by AI.
Get structured, clean, and usable for AI.
Strategies for preparing your data:
Data Collection
Collect large amounts of high-quality, relevant data that can be used to train your AI model. Ensure that your data is representative of your target population or industry.
Data Cleaning
Remove any errors, inconsistencies, or missing values from your data. This will help to boost the performance of your AI model.
Data Preprocessing
Transform your data into a format that is suitable for AI models. This may involve normalizing your data, encoding categorical variables, or converting into a suitable data structure.
Feature Engineering
Select and extract relevant features from your data that can be used to train your AI model. This may involve creating new features or combining existing ones.
Data Partitioning
Split your data into training, validation, and testing sets. This will help you to evaluate the performance of your AI model and make adjustments as needed.
Data Augmentation
Expand your dataset by creating new training samples using techniques such as image flipping, rotation, or cropping. This can help to improve the performance of your AI model.
Applications
Analyze data how and where you want. From local files to our powerful enterprise API.
Text →
Files →
Databases →
HTML →
Better Understand Your Data
- Save Time
The Future Of Data Is Here
- Understand
Magnify the Emotion
Our sentiment analysis sandbox delves deep into customer emotions providing invaluable insights that enable you to craft more personalized and compelling campaigns.
See the Model Flow architecture in action
