Entry Point AI

The modern AI optimization platform for proprietary and open-source language models.

Paid

Description

Entry Point AI serves as a comprehensive optimization platform for users working with both proprietary and open-source large language models (LLMs). It centralizes the management of prompts, fine-tuning processes, and model evaluations, simplifying workflows for individuals and teams. The platform aims to make advanced AI techniques like fine-tuning more accessible, moving beyond the limitations of basic prompt engineering.

By providing a unified interface for multiple LLM providers, Entry Point AI helps users avoid vendor lock-in and keep pace with the rapidly evolving AI landscape. It facilitates the fine-tuning process, enabling users to improve model quality, achieve faster generation speeds, ensure more predictable outputs, and scale AI applications effectively. The platform handles the complexities associated with different models and APIs, offering features for data management, collaboration, cost estimation, and model testing without requiring users to write code.

Key Features

Unified LLM Management: Manage prompts, fine-tuning jobs, and evaluations in one place.
Cross-Provider Fine-tuning: Train and optimize models from multiple leading LLM providers.
Simplified Fine-tuning Process: Makes fine-tuning accessible with dozens of examples, handling provider nuances.
Team Collaboration: Invite team members, track training data, jobs, and compare results.
Prompt & Data Templating Engine: Iterate rapidly on data structure and prompts for optimal outcomes.
Data Import & Export: Easily import data and export datasets as JSONL or CSV.
Model Sharing & Playground: Deploy frontends for fine-tuned models for testing and feedback.
Cost Estimation & Token Counting: Estimate training costs and count tokens to manage expenses.
No-Code Interface: Access provider APIs and hyperparameters through a user-friendly UI.
Unlimited Data Synthesis: Generate synthetic data to augment training datasets (included in plans).

Use Cases

Content generation (reports, articles, social media posts, emails)
Tagging & Classification
Data Extraction
Prioritization (support issues, bug reports, leads)
Product Recommendations
Fraud Detection
Content Moderation
Data Enrichment
Scoring & Ranking (for RAG)

Frequently Asked Questions

How many examples do I need to fine-tune a model?

You can start getting impressive results with as few as 50 examples. Adding more examples helps optimize for edge cases or allow a faster model to perform the task.

How does the training example limit work?

The limit applies across all your projects (e.g., a 1,000 limit could be one project with 1,000 examples or 10 projects with 100 each). Deleting examples or projects frees up the limit.

Can I keep my AI models if I cancel the plan?

Yes, models are trained on the platform of your choice (like OpenAI) and belong to you. You can revoke Entry Point AI's access anytime and export your data as JSONL or CSV.

Are there other costs besides the Entry Point AI subscription?

Yes, fine-tuning models and generating synthetic examples will incur costs directly from the AI platform providers (e.g., OpenAI) you connect to Entry Point AI. The tool helps estimate these external costs.

Do you offer volume or enterprise pricing?

Yes, custom quotes and plans for high volume requests are available by contacting their sales team.