KNOWLEDGE GRAPH

An innovative approach to knowledge retrieval

Knowledge Graph, our graph-based retrieval-augmented generation (RAG), achieves higher accuracy than traditional RAG approaches that use vector retrieval.

HOW IT WORKS
Geometric image showing a constellation pattern connecting circles and lines in shades of purple
1

Richer semantic understanding

Knowledge Graph draws on a specialized LLM that’s trained to process data at scale and build valuable semantic relationships between data points. It stores data in a cost-effective, easy-to-update graph structure.

What’s the alternative approach?

The alternative approach

By converting data into vector embeddings, traditional RAG can only define similarity by distance between data points but has no context on their semantic relationships. Vector databases are also difficult and costly to maintain and update.

Digram showing relationships between topics as an example of retrieval methodology
2

Accurate retrieval methodology

Because graph structures retain semantic relationships, Knowledge Graph accurately retrieves relevant data for each query. Our retrieval-aware compression technique condenses data and indexes it with metadata, which gives it rich context.

What’s the alternative approach?

The alternative approach

Traditional RAG converts the query into a vector embedding and uses a rough algorithm to find the closest data points to the query, without any understanding of the relationship between the data points. When data is dense, this method fails to return the most relevant data consistently.

Palmyra LLM's output using Knowledge Graph
3

State-of-the-art LLMs

To generate a response, Knowledge Graph sends relevant data to our Palmyra LLMs, which are top-ranked and trained with 1 trillion tokens of quality data. We apply advanced techniques to enhance performance and minimize hallucinations.

What’s the alternative approach?

The alternative approach

The quality of the answer depends on the quality of the retrieval, and the level of hallucination depends on the quality of the underlying LLM and the techniques you employ.

PERFORMANCE

Knowledge Graph achieves unmatched accuracy

In a benchmarking study, Writer Knowledge Graph achieved top scores on RobustQA, which measures accuracy in open-domain question-answering, outperforming seven popular RAG approaches that use vector retrieval.

USE CASES

Build digital assistants you can trust

Knowledge Graph anchors your generative AI solutions in your company knowledge. Create expert assistants for any use case and be confident that your people are getting the correct information.

Q: How much is the deductible for the Insure First PPO Gold Plan?

A: The deductible for PPO Gold is $250 for individuals and $1000 for families. This means you need to pay all costs from providers up to the deductible before the plan starts to pay for covered services.
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Chat-messaging conversation with AI comparing mobile phone models
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Chat-messaging conversation with AI discussing reference customers at a technology company
Man softly smiling in black and white

“With Knowledge Graph, we’ve built digital assistants that enable salespeople in real time, giving them accurate, on-brand insights on objection handling, competitive differentiation, personas, and more.”

Anna Griffin

Anna Griffin
Chief Market Officer

“Writer is onto something amazing. Their full-stack platform, deep customer-centricity, and high-touch approach to services truly sets them apart. Post our due diligence, partnering with Writer was an easy decision for us.”

Ajay Dhaul

Ajay Dhaul
SVP of Data & Applied AI

“Writer enables my technology team to provide high quality generative AI applications, without compromising on our security needs or responsible AI guidelines. From digital assistants to editorial content, we’ve been able to build powerful, secure applications on the Writer full-stack platform.”

Nitin Tandon

Nitin Tandon
CIO of Vanguard

DIFFERENTIATORS

Designed to meet enterprise requirements

Excels at advanced tasks

Excels at advanced tasks

Knowledge Graph supports multi-hop questions, handles complex data formats, and produces fewer hallucinations.

Scales with enterprise data

Scales with enterprise data

Unlike traditional RAG, Knowledge Graph excels at retrieval with concentrated data, and updating data is fast, easy, and inexpensive.

Provides explainable AI

Provides explainable AI

Knowledge Graph shows thought process, decomposes broad question into subquestions, and provides specific source citations.

Supports your file types

Supports your file types

Knowledge Graph handles structured and unstructured data, including spreadsheets, docs, charts, presentations, PDFs, and more.

BENEFITS

Deploy with confidence with integrated RAG

Rather than stitch together your own RAG, Writer Knowledge Graph makes it easy to build high-quality applications.

Maintain
efficient costs

67%
LOWER COST

when you use Writer instead of traditional RAG, with savings increasing as you scale.

Increase
your speed

Integrate data sources quickly. Our full-stack platform of LLMs, Knowledge Graph, AI guardrails, and a flexible application layer makes it easy to deploy in days.

Stay secure
and compliant

Secure your data and meet your compliance obligations. Our full-stack platform maximizes security, and we do not train on or retain your data.

Accelerate growth, increase productivity, and ensure compliance