AI-driven annotation is revolutionising data labelling. It achieves this by blending human intelligence with machine learning. Businesses have now reduced annotation time by as much as 40% while improving or even enhancing quality. This hybrid strategy shatters the conventional speed-vs-quality wall that has stunted AI development for decades.

How it works:

• Initial AI Pass

Smart systems make first-round annotations at unprecedented speed, processing thousands of items within hours rather than days. They even automate simple, repetitive cases and cleverly mark troublesome areas requiring human intervention.

• Human Expert Review

Trained annotators then spend their precious time only where necessary. This means spending time doing reviews, correcting, and fine-tuning the AI output. Accordingly, they devote their precious time to difficult cases rather than repetitive labelling.

• Continuous Improvement

The system improves with each human correction, learning with each interaction. Machine learning algorithms also recognise patterns in the corrections. They learn about your unique data types and annotation needs.

Key Business Benefits

• Focus on Complexity

Let AI do the easy, mundane work so your specialists can concentrate on challenging work. This saves you time and effort. It also keeps your top talent busy by assigning to them only the difficult cases where their expertise will really matter.

• Consistent Quality

AI treats every data point similarly. This eliminates errors and variances between people annotating it. It subsequently leads to a cleaner, more consistent dataset. Additionally, such consistency is quite necessary when teaching precise and reliable AI models to learn.

• True Scalability

With AI, you can work with much larger data sets very quickly. That means you don’t have to employ more people. Work that used to take months now takes weeks. This helps assist your teams in meeting deadlines and reaching for greater, more demanding AI objectives.

• Cost Efficiency

With AI, the number of hours spent on mundane tasks is less. This slashes project expenses in the long run by a big margin. Despite an initial setup, your savings start accumulating rapidly. Up to 50% cost savings on big data annotation projects are quite common for most teams.

• Real-World Results

We at AIPersonic apply this hybrid methodology in actual client projects. In healthcare, cities, retail, and so on, because it succeeds. Our platform assists teams to complete 40% quicker than ever before. Further, you have precise results, faster delivery, and no compromise on quality.

Take the Next Step

Ready to escape the annotation bottleneck? Get in touch with us for a consultation, or give our pilot program a go and discover how AI-aided annotation can accelerate your project without compromising the quality of your AI program.

Don’t let sluggish annotation slow your innovation down anymore.