![Dave A.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Dave A.")
DA

Dave A.

Director of Business Value Consulting

Mid-Market (51-1000 emp.)

7/22/2026

"A practical Enterprise AI partner for Microsoft Copilot and SharePoint knowledge base optimization"

5/5

What do you like best about Valere Labs?

What stood out was that Valere looked at more than just the prompt.

They helped improve the Copilot agent, but they also understood that the quality of the SharePoint content, metadata, retrieval, testing, and rollout process all mattered.

I also appreciated their structured approach. The Golden Dataset gave us a more objective way to test accuracy and consistency across different types of questions.

They communicated clearly, identified the real retrieval issue, and gave us practical recommendations around file naming, metadata, outdated content, and image-heavy documents.

They felt like a practical partner, not just a vendor completing tasks. Review collected by and hosted on G2.com.

What do you dislike about Valere Labs?

There was not anything significant that I would call a negative.

The main area for continued improvement is that this type of AI knowledge management work depends on the underlying content being fully indexed, consistently tagged, and maintained over time. At the time of early rollout, around 85 of 200 documents had been indexed, so there was still work to do on the knowledge base side.

I would also continue expanding the Golden Dataset as usage grows, especially as more real-world questions come in from different user groups. That is less a weakness of Valere and more a natural next step for improving any agent or Microsoft Copilot experience after launch. Review collected by and hosted on G2.com.

Recommendations to others considering Valere Labs:

I would recommend Valere if you need help making an Enterprise AI or Copilot experience work better in the real world, not just in a demo.

They are a good fit when the work involves Copilot agent behavior, prompt structure, SharePoint content, retrieval quality, testing, and rollout feedback.

I would bring them in early enough to look at both the agent and the content behind it. In our case, a lot of the value came from understanding how SharePoint structure, metadata, and document quality were affecting the answers.

If you want practical help making AI performance more measurable and easier to improve over time, they are worth considering. Review collected by and hosted on G2.com.

What problems is Valere Labs solving and how is that benefiting you?

Valere helped my customer to improve the reliability, consistency, and usability of a Microsoft Copilot agent in an enterprise setting.

The challenge was not just writing better prompts. We needed the agent to respond more consistently, pull the right information from SharePoint, handle unclear questions better, and give users answers they could trust during rollout.

Valere helped bring the scattered instructions and guardrails into one clearer prompt structure. They also improved escalation handling and gave the agent better guidance around tone, formatting, and complete answers. One of the most helpful pieces was identifying that the steady 4.3-second latency was coming from the SharePoint retrieval layer, not the prompt or the model itself.

That was useful because it pointed us to the right work: improving the SharePoint knowledge base, tightening metadata, cleaning up document naming, managing outdated content, and making image-heavy procedural documents easier for the agent to use.

The results were practical and measurable. During early rollout, we saw 78% user engagement, an 88% successful answer rate, 82.4% of answers rated as good quality, and almost no escalations or abandonments. The optimized SharePoint knowledge base also handled about 80% of incoming questions, with a 90% response quality score.

Overall, Valere helped make the Copilot experience more reliable, easier to measure, and easier to keep improving over time. Review collected by and hosted on G2.com.

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