The Valye Score Explained: Measuring Research Confidence (Not Stock Picks)

First: what the Valye Score is not

Let’s get this out of the way:

The Valye Score is not a buy/sell rating.
It’s not a promise of performance.
It’s not a substitute for professional advice.

Disclaimer: Research-only. Not investment advice.

The Valye Score is designed to answer a different question:
“How confident can I be in the research view I’m looking at—based on coverage and source quality?”

In a world flooded with content, “what should I trust” matters as much as “what should I read.”

Why scores exist in research at all

When you research companies, you constantly make invisible decisions:

Most tools dump information. Valye AI tries to organize it, then help you prioritize it.

That’s the role of a score: not to replace judgment, but to guide attention.

A simple definition

The Valye Score is a research confidence indicator.

It reflects how strong the underlying information base is for a given company/topic at the time of analysis, based on:

Think of it like a flashlight in a crowded room:
It doesn’t tell you what to believe—it helps you see where to look first.

What goes into a research confidence score

While exact scoring methods can evolve over time, a research confidence system typically considers factors like these:

1) Source quality

Not all information is equal.

2) Source diversity

One source can be misleading or incomplete.
Confidence increases when multiple independent sources reinforce key facts.

3) Document completeness for the question being asked

A company might have strong coverage on:

A good score doesn’t just say “high or low.” It should imply where the gaps are.

4) Consistency and contradiction handling

Sometimes sources conflict:

Valye AI is designed to surface contradictions rather than bury them.

5) Freshness (recency)

Even excellent research becomes stale. Scores should account for whether the most relevant inputs are recent enough for the decision you’re making.

How to interpret the Valye Score in practice

Here’s a practical way to use it:

Use it to prioritize reading

Use it to identify “verification needed”

A lower score is not “bad.” It often means:

In research, “low confidence” is a signal to slow down—not to dismiss.

Use it to build better internal workflows

If you’re researching multiple companies:

Why Valye focuses on confidence instead of prediction

Prediction scores create two problems:

  1. They imply certainty where none exists
  2. They blur the line between research and advice

Valye is built to stay on the research side of that line.

Confidence scoring is helpful because it’s about inputs, not outcomes:

That’s a safer, more honest foundation.

A quick example (generic)

Imagine you’re researching a company that claims:

A research confidence system would ask:

If the answers are “yes” with traceable sources, confidence rises.
If the answers are mostly “unclear” or “single-source,” confidence drops.

How to increase confidence in your own research

Valye can help, but your workflow matters too. A few habits that dramatically improve research quality:

Keep a “claim vs evidence” list

For each important claim, write:

Favor primary documents for risks and constraints

Risks are rarely emphasized in marketing copy. Filings and official disclosures are where constraints live.

Always ask “what changed?”

Research value is driven by deltas:

Scores are most useful when paired with change detection.

The point of the Valye Score: better research hygiene

The Valye Score exists to support a simple goal:
make research more disciplined.

Not faster reading—better thinking:

If a score helps you ask those questions sooner, it’s doing its job.

Try it on your next company deep dive

If you’re building a watchlist or researching a sector, use Valye to:

Explore Free Reports → https://www.valye.com/app/reports
Footer disclaimer: Research-only. Not investment advice.