When Microsoft Copilot first launched, the promise was clear: unlock the power of generative AI within the Microsoft 365 ecosystem to improve productivity, accelerate work, and help users find the right information faster. But for many early adopters—especially before the advent of Copilot Studio—the reality didn’t quite match the hype.
One of the most common complaints? Copilot often returned irrelevant, outdated, or inaccurate content. It wasn’t that the AI was faulty—it was simply working with what it had access to. Many organizations discovered that their information was scattered, inconsistently tagged (if at all), and lacked a coherent structure. As a result, Copilot struggled to identify the most relevant content when answering user queries.
Copilot Studio improves targeting—but not relevancy
With the introduction of Copilot Studio, organizations gained more control. It became easier to build task-specific agents and limit them to more targeted sets of content. This has been a step in the right direction, allowing firms to reduce noise and focus Copilot on specific knowledge areas.
However, even with a more focused content scope, Copilot still depends on the quality and clarity of the underlying data. Without proper enrichment—especially consistent metadata—irrelevant or less accurate content can still make its way into Copilot's answers, leading to user frustration and diminished trust in the tool.
This is where Atlas makes a meaningful difference.
Atlas enables firms to organize their content using a common information architecture—a structured way of classifying and managing knowledge across the entire organization. This foundation brings consistency to how information is stored, described, and accessed. Whether it’s documents, pages, or communications, everything fits into a well-defined structure that Copilot can more easily understand and navigate.
But Atlas doesn’t stop there.
It also automatically enriches content with intelligent metadata, without requiring users to manually tag everything. This means every piece of content—new or legacy—is contextualized and described in a way that makes it easier for Copilot to surface the most relevant, authoritative results.
Why does this matter for Copilot? Because metadata drives discoverability and relevance. When Copilot is trying to decide which document to pull from when answering a query, metadata is a key signal. Content enriched by Atlas rises to the top—not because it’s newer or more popular, but because it’s more relevant to the question being asked.
With Atlas, firms can be confident that Copilot is pulling from the right sources, improving trust in AI-generated answers and delivering a better user experience.
Early Copilot users struggled with poor results due to disorganized and outdated content. Copilot Studio helps by narrowing the scope, but without metadata enrichment, even targeted agents can surface irrelevant content. Atlas by ClearPeople solves this by:
In short, Atlas transforms Copilot from a promising tool into a powerful, reliable assistant—one that users can actually trust.
| Atlas capability | What it solves for Copilot |
| Common Information Architecture | Ensures content is structured and findable |
| Automatic Metadata Enrichment | Increases content discoverability and relevance |
| Intelligent Taxonomy and Contextual Tags | Surfaces the most accurate results |
| Seamless Microsoft 365 Integration | Copilot pulls from the best internal knowledge sources |