Eliminate bad data in SharePoint becomes bad Copilot answer
Gain control over SharePoint data quality issues
Continuously improve your Copilot answers
Get Answer transparency for Responsible AI
Shelf helps you get better, higher quality answers from your MS Copilot
Shelf’s data quality platform makes Copilot better
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
Bad data in documents & files = bad answers
Automatically fix or filter bad SharePoint data to deliver more trusted Copilot answers
Shelf is the key to your Copilot success
We’ve been helping customers with SharePoint quality problems since 2017
“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
Get Better Answers Now
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
AI success depends on unstructured data quality
[ Resources ]
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…
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…
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…
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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.
