Knowledge Graph Data Pipelines
for Deterministic AI

The future of AI are developers and domain experts injecting structured context and determinism into their RAG pipelines, so you can build accurate, and explainable RAG solutions.

Be the first to experience WhyHow.AI in our Closed Beta. Sign up for early access and updates.

Check out progress of our work on our Blog.
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Knowledge Graphs for RAG and Agentic Memory

Structure your data and answers

  • Structured knowledge grounding to reduce wrong answers
  • Collect the information you want

Deterministic Information Retrieval

  • Tie Chunk Access Rules to specific questions / scenarios

Multi-KG management

  • Manage schemas for each of your use cases
  • Create workflows for automatically building and updating KGs with your data

The WhyHow developer advantage

WhyHow is a platform for building and managing knowledge graphs to support complex data retrieval. We give developers the building blocks they need to organize, contextualize, and reliably retrieve unstructured data to perform complex RAG.

Integrate WhyHow directly into your existing RAG pipelines to bring structure, consistency, and control to your AI solutions


Maximizing Accuracy with Knowledge Graphs

By implementing knowledge graphs, you unlock powerful benefits for your RAG systems.

Manage Small-KGs

Modern use cases demand many small, specialized KGs. We give you the tools you need to easily build, integrate, and manage as many graphs as you need.

Rule Sets

Build guardrails for data retrieval, ensuring RAG systems operate as expected and users access only the data  they’re supposed to see.

Deterministic Workflows

Build and manage highly customizable graph-based retrieval workflows  to ensure consistent execution of complex, multi-hop queries.

Graph Creation from your Opinion

Create a schema based on what you want to see captured and saved in a Knowledge Graph for more deterministic referencing

Modern APIs

We offer robust APIs and simple SDKs to enable modern developer workflows. Implement WhyHow directly into your existing pipelines.

from whyhow import Client

client = Client()



Hybrid: Graphs & Vectors

We embrace a hybrid approach that enables developers to leverage the best of both knowledge graphs and vector databases.

Create knowledge graphs from your own data.

With WhyHow, developers can automatically create knowledge graphs and integrate with their existing workflows. No need to learn new languages. Query, explore, and modify graph data using developer friendly SDKs.

Add rules to your RAG to control retrieval.

Customize your retrieval workflows to control the data being sent to your RAG pipelines. Use rules to bring stronger determinism to your RAG solutions.

Get your RAG systems to production with graph structures.

Contact us today for more information and to get into our closed Beta program