AI Interfaces
Confidence Meter
A multi-signal confidence card for grounded AI answers, eval reviews, and release checks.
Installation
Copy and paste the code into your project.
Accessibility notes
Each signal includes a text value, so progress bars are not the only source of meaning.
Confidence
readyPreview accent
const signals = [
{ label: "Grounded", value: "91%", width: "w-[91%]" },
{ label: "Coverage", value: "84%", width: "w-[84%]" },
{ label: "Risk", value: "12%", width: "w-[12%]" },
];
export function ConfidenceMeter() {
return (
<section className="w-full max-w-sm rounded-lg border border-[#40E0D0]/20 bg-white/[0.06] p-5 shadow-2xl backdrop-blur">
<div className="flex items-center justify-between">
<p className="text-xs font-semibold uppercase tracking-[0.18em] text-[#40E0D0]">Confidence</p>
<span className="rounded-full bg-[#40E0D0]/12 px-2.5 py-1 text-xs font-semibold text-[#d8fffb]">ready</span>
</div>
<div className="mt-4 space-y-3">
{signals.map((signal) => (
<div key={signal.label}>
<div className="flex justify-between text-xs font-semibold text-slate-300">
<span>{signal.label}</span>
<span>{signal.value}</span>
</div>
<div className="mt-1.5 h-2 overflow-hidden rounded-full bg-[#1b1b1d]">
<div className={`${signal.width} h-full rounded-full bg-gradient-to-r from-[#40E0D0] to-[#a78bfa]`} />
</div>
</div>
))}
</div>
</section>
);
}<ConfidenceMeter />Related components
Answer evidence
3 claims supported
- 98%
Release date
Launch brief
- 91%
Plan limits
Pricing notes
- 86%
Migration path
Support guide
AI Interfaces
Answer Evidence Card
A claim-level evidence summary that connects generated answers to sources and confidence scores.
Decision boundary
Review before answering
- Source agreement
- 84%
- Policy clarity
- 62%
- Answer stability
- 71%
Escalation triggered
Policy clarity is below the 70% automatic-answer threshold.
AI Interfaces
Confidence Escalation Panel
A decision boundary that converts uncertainty signals into request-context or human-review actions.
Dataset slices
Eval performance
- 96%
English · Enterprise
184 cases
- 82%
Spanish · SMB
91 cases
- 74%
Complex queries
63 cases
Largest gap: complex queries trail the average by 14 points.
AI Interfaces
Dataset Slice Explorer
A slice-level evaluation view revealing performance gaps across language, customer tier, and query complexity.