Deployable AI/ML models come from accurate data preparation
Owning your data pipeline is easier than ever, with Innotescus’ comprehensive toolkit of advanced features
Learn how Innotescus optimizes MLOps at every stage of the process
1 | Collection
Access current datasets and collect new data points.
2 | Cleaning
Import, aggregate, discard, and manage existing data.
3 | Annotation
Structure datasets with labels, classes, and objects.
4 | Visualization
Understand statistical distribution and data significance.
5 | Enrichment
Create new data points, enhance, and transform datasets.
6 | Feature Engineering
Learn about feature correlations, redundancy, and efficiency.
7 | Training & Validation
Train and validate model performance on labeled datasets.
8 | Deployment
Deploy performing models for production.
9 | Improvement
Boost performance through process iteration.
A collaborative platform for each team player
From data scientists to product managers, our user community provides resources, toolkits, and learning for every role within the artificial intelligence and machine learning space.
Catch insights from your data early, even as data is being prepared. Our intuitive visualization tools allow statistical analyses on data at every stage – raw, annotated, as its being prepared, and as it fuels your algorithm. Seek out data imbalances early. Iterate annotation specs more often without disrupting the process.
Faster, more accurate annotation with fewer clicks. Annotators can now collaborate, build consensus, and consult with subject matter experts in real-time. Having a ‘human-in-the-loop’ was never this easy.
Get access to well-annotated, prepared, accurate data early. Iterate early and often. Study data properties with powerful statistical visualizations, and achieve higher accuracy through data enhancement and feature engineering. Understand performance bottlenecks early for effective deployment readiness planning.
One collaborative platform with data organized, stored, and secured over the cloud. Have multiple annotators, scientists, and developers work collaboratively on a single platform without data contamination nightmares.
Manage teams, timelines, and model development activities more effectively. Own end-to-end data annotation processes for better accuracy. Catch data imbalances, model biases, and performance shortfalls early to shorten development cycles.
Subject Matter Experts
Be an efficient human-in-the loop to ensure annotation accuracy, without getting stuck in tedious time-consuming annotation activities yourself. Collaborate with annotators to iterate and evolve annotation specifications efficiently. Oversee the complete data preparation process to gather model design insights early.