Enhance Search Result Relevance with Fuzzy Matching

The search functionality relies on exact matching via the data aggregator’s multisearch endpoint, leading to poor results for misspelled queries. Adding fuzzy search or typo tolerance would greatly improve user experience.

Sample:
```json
// Example Elasticsearch fuzziness parameter
{
"query": {
"multi_match": {
"query": "Monetn",
"fields": ["title^2", "description"],
"fuzziness": "AUTO"
}
}
}
```

No files, tests, or entry points are named. Start by locating the Swift search integration and checking how the data aggregator's multisearch endpoint handles the Elasticsearch-style fuzziness example. Done means misspelled queries return relevant results without breaking exact-match search.

Written by the indexing model from the issue text.