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Isahit Features

Isahit's Core Features

Human-driven LLM fine-tuning

RAG optimization

Quality data processing (data entry, cleaning, management, PIM, CRM optimization)

Image, video, speech & audio annotation

Natural Language Processing (NLP)

Agentic AI Solutions

Ethical managed workforce (Human-in-the-Loop)

Active Learning Workflows and Workforce Management for RLHF

Proprietary and client-tool compatible labeling solutions

AI bias correction and quality assurance

Localization and customization of AI responses

Isahit's Use Cases

Training computer vision models for autonomous cars, drones, or flight simulators using image and video annotation.

Extracting specific information from text for Natural Language Processing models.

Outsourcing repetitive back-office tasks such as KYC/KYB verification and data entry.

Improving user experience for e-commerce through product categorization, product sheet enrichment, and product reviews moderation.

Developing Generative AI Models and Language Models (LLMs) with Reinforcement Learning from Human Feedback (RLHF).

Data cleansing and annotation for computer vision algorithms.

Content management tasks like writing product sheets, articles, subtitling, and translating texts.

Transcribing information on CVs/resumes, enriching and cleaning databases, or monitoring information for legal, financial, and human resources sectors.

FAQ from Isahit

What is data labeling?

What is impact sourcing?

What types of companies do you work with?

Why do you only recruit women?

From which country do your HITers come from?

What are the concrete benefits of isahit for the HITers?

Why do you call them 'HITers'?

How do you measure your social impact?

In which languages do you work?

How can we be sure of the identity of the HITers?

How is the quality of the output data measured?

How do you pay the HITers?

What types of professional projects are developed by the HITers?

How is your structure organized?

What is isahit's objective for the next 5 years?

What is isahit help?

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