Explore how Shelf helps you get better, higher quality answers from your MS Copilot

Shelf helps you get better, higher quality answers from your MS Copilot

Shelf’s data quality platform makes Copilot better

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50% of companies polled grounded MS Copilot over data governance concerns

Source: The Register, August 21st, 2024

Copilot + Sharepoint expose companies to new risks

Failing to address SharePoint data issues means getting burned by Copilot

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Bad data in documents & files = bad answers
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Automatically fix or filter bad SharePoint data to deliver more trusted Copilot answers
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Shelf is the key to your Copilot success

Eliminate bad data in Sharepoint before it becomes bad Copilot answers.

Gain control over SharePoint data quality issues

Continuously improve your Copilot answers

Get Answer transparency for Responsible AI

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We’ve been helping customers with SharePoint quality problems since 2017
Microsoft Partner
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“No matter what data science teams tried thus far, they haven’t been able to reliably improve the answer quality of our GenAI POCs. Shelf’s platform is the piece we’ve been missing!”

– Head of Automation at Leading Manufacturing Company
Shelf x Copilot
Get Better Answers Now
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Three easy steps to get started
1

Connect
SharePoint &
Copilot conversation

2

Identify &
filter bad data

3

Get trusted
answers

Download IDC’s Report:
AI success depends on unstructured data quality
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[ Resources ]

Explore resources from Shelf

Get more resources
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The IT Leader’s Guide to Preparing Your Data for Generative AI

Businesses have long been increasingly inundated with an unprecedented volume of data. The challenge now is not just about storing ample data but managing, classifying, and transforming this structured and unstructured data into fuel for the engine of business. The critical role of data…

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Why Generative AI Elevates the Importance of Unstructured Data

Historically, we never cared much about unstructured data. While many organizations captured it, few managed it well or took steps to ensure its quality. Any process used to catalog or analyze unstructured data required too much cumbersome human interaction to be useful (except in rare…

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Six Data Enrichment Strategies That Optimize RAG Performance for GenAI Readiness

Large language models have an impressive ability to generate human-like content, but they also run the risk of generating confusing or inaccurate responses. In some cases, LLM responses can be harmful, biased, or even nonsensical. The cause? Poor data quality. According to a poll of IT leaders by…

Download our Free Guide to deploy GenAI with Confidence

What’s inside
3 immediately actionable RAG strategies for improving answer quality so you can deploy RAG with more answer transparency, confidence and impact.

Created by experts in unstructured data who have 40 years of experience and have processed over 100M pieces of content for some of the world’s best brands, including; Amazon, Lufthansa and the Mayo Clinic.

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