Building a Four-Tier Parallel RAG Pipeline with Gemini

The Problem When building BotForge, our AI no-code chatbot platform, we needed a retrieval system that could handle messy, real-world user queries — typos, partial phrases, semantically similar-but-differently-worded questions. A naive vector search alone wasn't good enough. It's powerful but brittle to out-of-vocabulary terms and exact keyword lookups. The Solution: Four-Tier Parallel Retrieval We ran four retrieval strategies simultaneously using Promise.all\ , then merged results with a weighted scoring function. \ javascript const [semanticResults, textResults, regexResults, fuzzyResults] = await Promise.all([ semanticSearch(query, embeddings), // weight 1.8x mongoFullTextSearch(query), // weight 1.5x regexKeywordSearch(query), // weight 1.0x fuzzyPerWordMatch(query), // weight 0.6x ]) \ \ Tier 1: Semantic Search (1.8× weight) Using Gemini gemini-embedding-2\ to produce 3072-dimensional vectors , we compute cosine similarity against stored document embeddings. This catches meaning — "how do I reset my login?" matches "account recovery options" even with no shared words. Tier 2: MongoDB Full-Text Search (1.5× weight) A native MongoDB Atlas text index for fast, exact keyword hits. Great for technical terms, product names, and precise phrases. Tier 3: Regex Keyword Matching (1.0× weight) Each significant word in the query is compiled to a case-insensitive regex. Catches partial matches and hyphenated variants. Tier 4: Fuzzy Per-Word Matching (0.6× weight) Levenshtein distance matching per query word — handles typos and misspellings like "configuraton" → "configuration". Weighted Score Merging Each result carries a base score from its retrieval strategy. We deduplicate by chunk ID, sum scores across strategies, and sort descending: \ javascript function mergeResults(tiers, weights) { const scoreMap = new Map() tiers.forEach((results, i) => { results.forEach(({ id, score, chunk }) => { const weighted = score * weights[i] scoreMap.set(id, { chunk, total: (scoreMap.get