Get AI to do what you actually want it to do.
Entry Point is the modern fine-tuning platform for proprietary and open-source large language models, including GPT, Llama-2, and Mistral.
Entry Point AI key features
**Fine-tuning**: Train task-specific models that outperform general models with reduced cost and latency.
**Transforms**: Add an AI column to data for tagging, extracting, or classifying information across multiple rows.
**Synthetic Data**: Generate additional training examples from existing data to enhance model performance.
**Quality Checks**: Test and validate prompts to ensure accuracy before deployment in production.
**Multi-provider Support**: Train models across various AI providers using a unified interface, allowing flexibility and control over costs.
Entry Point AI use cases
**Data Transformation**: Add an AI column to datasets for tagging, extracting, or classifying data across thousands of rows using prompts.
**Synthetic Data Generation**: Create additional labeled examples from a small set of existing data to enhance training datasets for classifiers.
**Model Fine-Tuning**: Train task-specific models that outperform general models, optimizing for speed and cost-effectiveness in production environments.
**Quality Assurance**: Implement quality checks on outputs to ensure accuracy before deploying models in production.
**Multi-Provider Integration**: Utilize various AI model providers (e.g., OpenAI, Google AI) with personal API keys for flexibility and cost control in model training and deployment.
Useful for
**Task-Specific Model Training**: Fine-tuning allows users to create models tailored to specific tasks, improving performance and relevance compared to general models.
**Data Transformation**: The application enables users to add AI-generated columns to datasets for tagging, extracting, and classifying data efficiently.
**Synthetic Data Generation**: Users can generate additional training examples from limited labeled data, enhancing the quality and diversity of their datasets.
**Quality Assurance**: The platform includes features for testing and validating outputs, ensuring that only high-quality results are deployed in production.
**Multi-Provider Flexibility**: Users can connect to various AI model providers, allowing for cost-effective and adaptable model training without being locked into a single service.
Price
**Starter Plan**: $49/month for up to 5,000 rows, includes 3 seats and the full toolkit.
**Growth Plan**: $99/month for up to 25,000 rows, includes 5 seats and everything in the Starter plan.
**Pro Plan**: $249/month for up to 100,000 rows, includes 10 seats, everything in the Growth plan, and premium support.
**Free Trial**: Try Entry Point free with up to 300 rows before selecting a plan.
**Enterprise Options**: Available for those needing more room beyond the Pro plan.
Task-Specific Model Training: Fine-tuning allows users to create models tailored to specific tasks, improving performance and relevance compared to general models.
Data Transformation: The application enables users to add AI-generated columns to datasets for tagging, extracting, and classifying data efficiently.
Synthetic Data Generation: Users can generate additional training examples from limited labeled data, enhancing the quality and diversity of their datasets.
Quality Assurance: The platform includes features for testing and validating outputs, ensuring that only high-quality results are deployed in production.
Multi-Provider Flexibility: Users can connect to various AI model providers, allowing for cost-effective and adaptable model training without being locked into a single service.
What are the main use cases for Entry Point AI?
Data Transformation: Add an AI column to datasets for tagging, extracting, or classifying data across thousands of rows using prompts.
Synthetic Data Generation: Create additional labeled examples from a small set of existing data to enhance training datasets for classifiers.
Model Fine-Tuning: Train task-specific models that outperform general models, optimizing for speed and cost-effectiveness in production environments.
Quality Assurance: Implement quality checks on outputs to ensure accuracy before deploying models in production.
Multi-Provider Integration: Utilize various AI model providers (e.g., OpenAI, Google AI) with personal API keys for flexibility and cost control in model training and deployment.
What are Entry Point AI's key features?
Fine-tuning: Train task-specific models that outperform general models with reduced cost and latency.
Transforms: Add an AI column to data for tagging, extracting, or classifying information across multiple rows.
Synthetic Data: Generate additional training examples from existing data to enhance model performance.
Quality Checks: Test and validate prompts to ensure accuracy before deployment in production.
Multi-provider Support: Train models across various AI providers using a unified interface, allowing flexibility and control over costs.
How much does Entry Point AI cost?
Starter Plan: $49/month for up to 5,000 rows, includes 3 seats and the full toolkit.
Growth Plan: $99/month for up to 25,000 rows, includes 5 seats and everything in the Starter plan.
Pro Plan: $249/month for up to 100,000 rows, includes 10 seats, everything in the Growth plan, and premium support.
Free Trial: Try Entry Point free with up to 300 rows before selecting a plan.
Enterprise Options: Available for those needing more room beyond the Pro plan.
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