What makes Automorphic different from standard RAG?

Unlike RAG (Retrieval-Augmented Generation) which stuffs context into a prompt, Automorphic infuses knowledge directly into the model's weights via efficient fine-tuning, reducing latency and bypassing context window limits.

Is Automorphic compatible with existing AI apps?

Yes, it is designed to be OpenAI API compatible, allowing developers to swap their existing LLM provider for an Automorphic-tuned model with minimal code changes.

What is the TREX feature?

TREX is a specialized tool within the Automorphic suite that converts unstructured data into structured formats like JSON or XML using context-free grammars or regular expressions.

How does the Aegis firewall protect my models?

Aegis acts as a security layer that detects and blocks prompt injections, PII (Personally Identifiable Information) leakage, and toxic language in real-time.

Can I use Automorphic for free?

Automorphic primarily offers a paid subscription starting at $49/month, though they have previously offered private beta access for developers.

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Database Q&A

Paid

Automorphic

Infuse domain knowledge into LLMs with minimal samples using advanced fine-tuning and adapters. Build secure, self-improving models for complex Database Q&A and data structuring.

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Rating

Reviews

Upvotes

3 months ago

Listed

Database Q&A

LLM Fine-tuning

Data Structuring

AI Firewall

Model Adapters

Developer Tools

Knowledge Infusion

Data Privacy

Machine Learning

Enterprise AI

Tool information

Provider

Automorphic, Inc.

Platforms

Web

Languages

English

API Available

Yes

Added to directory

3 months ago

Last updated

about 2 months ago

Rating

Not available

Pricing

Paid

About Automorphic

What the tool does and who it's for

Automorphic is an AI framework and platform designed to streamline the process of infusing specific knowledge into large language models (LLMs). It utilizes a novel fine-tuning approach that requires as few as 10 samples to adapt a model to a particular domain, effectively overcoming the memory and cost limitations of traditional RAG (Retrieval-Augmented Generation) and context-window stuffing. The suite includes 'Conduit' for knowledge infusion, 'TREX' for unstructured-to-structured data conversion, and 'Aegis'—a specialized AI firewall that protects against prompt injections and PII leakage. The platform is designed for rapid iteration, allowing developers to build self-improving models that learn from human-in-the-loop feedback and production data in real-time.

Key capabilities

Minimal Data Fine-tuning: Infuse specific domain knowledge into models using as few as 10 samples.

Conduit Engine: Dynamically stack and load fine-tuned adapters for high-performance inference.

TREX Data Converter: Transform unstructured text into JSON, XML, or YAML based on custom schemas.

Aegis Firewall: Protects models from adversarial attacks, prompt injections, and data leakage.

Self-Improving Feedback Loop: Enhances model performance continuously based on human-in-the-loop inputs.

OpenAI API Compatibility: Seamlessly integrate with existing codebases using standard API protocols.

Raw Corpus Training: Minimize information loss by training directly on raw text data.

Automorphic Hub: Access and share specialized models trained by the community for varied use cases.

Pricing

Paid — plans below

Standard

Enterprise

Contact sales

High-volume data processing
Custom adapter development
Dedicated infrastructure
SLA guarantees
Advanced security features

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