Does EdgeNGram autocomplete_filter make sense with prefix search?

i have Elastic Search Index with around 1 million records.
I want to do multi prefix search against 2 fields in the Elastic Search Index, Name and ID (there are around 10 total).
Does creating EdgeNGram autocomplete filter make sense at all?
Or i am missing the point of the EdgeNGram.
Here is the code i have for creation of the index:

    index: 'testing',
    // type: 'text',
    body: {
     settings: {
      analysis: {
        filter: {
          autocomplete_filter: {
            type: 'edge_ngram',
            min_gram: 3,
            max_gram: 20
        analyzer: {
          autocomplete: {
            type: 'custom',
            tokenizer: 'standard',
            filter: [
},function(err,resp,status) {
  if(err) {
  else {

Code for searching{  
  index: 'testing',
  type: 'article',
  body: {
    query: {
        multi_match : {
          query:    "brow",
          fields: [ "name", "id" ],
          type: "phrase_prefix"
},function (error, response,status) {
    if (error){
      console.log("search error: "+error)
    else {
      console.log("--- Response ---");
      console.log("--- Hits ---");

The search returns the correct results even without creating the index above (1st code snippet), so my question being does creating the edgengram filter and analyzer make sense in this case?
Or this prefix functionality would be given out of the box?
From what i can see, if the name is "Brown fox", even if i search for terms "brow", "bro", "fo" it brings the correct results.
Important to note: I dont want autocomplete to help me with suggestions - for example if i type "Borw" - to suggest me the term "Brown Fox"
Thanks a lot for your info

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