What is the best way to manage an index for exact search and normal search

Elastic Stack Elasticsearch
1

I have a use case where I need normal match_all search i.e it shows me related documents with fuzzy results also, however I need a specific search which needs to do a term query.
My mappings are mostly text type:

"project_title": {
        "type": "text",
        "fields": {
          "keyword": {
            "type": "keyword",
            "ignore_above": 256
          }
        }
      },
      "projectabstract": {
        "type": "text",
        "fields": {
          "keyword": {
            "type": "keyword",
            "ignore_above": 256
          }
        }
      },
"task_number": {
        "type": "keyword",
        "normalizer": "lowercase_normalizer"
      }

I did try exact search using lowercase normalizer by making task_number a keyword, but found out that I cant do a fuzzy search because it is a keyword. Since lowercase normalizer works only on keywords, if I convert the fields to keyword I cannot get search results I get from type: text. Should I maintain two indexes one with text and another of type keyword or is there a better alternative to it ?

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