RAG / Retrieval-Augmented Generation
This category describes an approach where an AI model receives additional context from external sources before answering, including documents, knowledge bases, on-chain data, indexes, graphs, or search systems.
Market indicators
What RAG / Retrieval-Augmented Generation means
RAG is important for practical AI applications because it lets models use current information rather than relying only on training memory. In crypto, it is useful for analytics, dApp interfaces, on-chain search, research tools, and AI assistants.
How this segment differs
RAG / Retrieval-Augmented Generation is the technique of producing an answer with added external context. Indexing, Search & Retrieval is the infrastructure that prepares, stores, and finds that context.
What to watch
RAG is a technique, not merely a search feature. There must be a clear connection between a retrieval layer and AI responses, indexes, context, or developer infrastructure.
Segment health and breadth
Market cap structure
Movement within the segment Click a ticker to highlight the coin in the table below Expand
Segment overlap map 3 vocabularies, 6 overlaps Expand
| # | Coin | Price | 1h | 24h | 7d | 30d | 60d | 90d | 24h volume | Market cap | AI Score |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 |
TRAC
|
$0.4774 | 0.34% | 24.96% | 25.99% | 48.39% | 78.57% | 81.68% | $44.82M | $238.68M |
62
|
| 2 |
ARC
|
$0.0704 | -0.44% | -4.60% | -10.76% | 1.16% | 33.84% | -14.49% | $2.66M | $70.38M |
45
|
| 3 |
SKYAI
|
$0.0422 | -0.26% | 5.32% | -9.38% | -21.50% | 60.45% | -46.76% | $4.74M | $42.22M |
47
|
| 4 |
SQD
|
$0.03 | -0.16% | 0.47% | 2.05% | -11.93% | -2.28% | -10.75% | $1.57M | $34.2M |
62
|
| 5 |
PROMPT
|
$0.0207 | -1.00% | 0.66% | -1.28% | -15.05% | 0.83% | -8.49% | $5.08M | $10.73M |
52
|
| 6 |
SQT
|
$0.05603 | 0.00% | 7.39% | -15.57% | -48.09% | -95.61% | -96.78% | No data | $22.85K |
58
|
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