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Feature Stores for LLMs

Define, Manage, and Deploy Your RAG Pipelines
LLMs
PROMPT CONSTRUCTION
Given a user who is {{AGE}} years old that spends {{AVG_SPEND_PER_MONTH}} their top three categories are {{TOP_3_SPEND_CATEGORIES}}. Here are some snippets from our content that are relevant to this question, that you should try to stay true to {{NEAREST_NEIGHBOR_CONTENT}}. They asked “{{param.query}}”
INFRASTRUCTURE PROVIDERS
COMPUTE
VECTOR DATABASES
STREAMING
EMBEDDINGS
RESOURCE
REPOSITORY
MONITORING
& ALERTING
GOVERNANCE
COLLABORATION
ORCHESTRATION
DECLARATIVE API
DASHBOARD
ENGINEER
DATA SCIENTIST
ADMIN

Feature Stores for LLMs

PROMPT CONSTRUCTION
Given a user who is {{AGE}} years old that spends {{AVG_SPEND_PER_MONTH}} their top three categories are {{TOP_3_SPEND_CATEGORIES}}. Here are some snippets from our content that are relevant to this question, that you should try to stay true to {{NEAREST_NEIGHBOR_CONTENT}}. They asked “{{param.query}}”
LLMs
EMBEDDINGS

Leverage Your Data to Boost LLM Performance and Reliability

Elevate your LLM-powered applications using Retrieval-Augmented Generation (RAG) to incorporate your unique data directly into prompts. This approach tailors generative outputs to your business needs, and uses your data to increase reliability and decrease hallucinations. RAG leverages the specific nuances of your data, transforming LLM outputs into more relevant, context-aware tools for your industry.
orchestration
COMPUTE
VECTOR DATABASES
STREAMING

Integrate Embeddings, Vector DBs, and Key-Value Stores into your RAG Pipeline

Featureform simplifies the creation of complex RAG pipelines by offering native support for embeddings, vector databases, key-value stores, and ETLs. This integration allows AI teams to efficiently build RAG systems that equip your LLMs with detailed context and depth. The result is highly relevant and accurate LLM outputs, customized to meet the specific needs of your use case.
RESOURCE REPOSITORY
MONITORING
& ALERTING
GOVERNANCE
COLLABORATION
ORCHESTRATION

Centralize, Version, and Monitor Your RAG Pipelines

Centralize your RAG pipeline definitions with Featureform's resource repository. This centralization establishes a single source of truth and fosters collaboration. Along with robust version control to track and manage changes, our platform also provides comprehensive monitoring for real-time performance insights. By creating this unified and dynamic management system, your team can swiftly adapt, refine, and iterate on your RAG pipelines.

Explore Our Documentation

Find more details on what the FeatureForm workflow can do for you, as well as what sets it apart from rival feature store platforms.

Request a Demo

Book time with our team to learn more about how Featureform can transform your ML workflow.

Github Repo

Ready to get started? Check out our GitHub Repository.

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See what a virtual feature store means for your organization.