A leading decentralised finance protocol came to us with an expensive distraction. Their senior engineers were spending 15 to 20 hours a week answering repetitive technical questions in Discord and Telegram, and general-purpose assistants were giving answers that were confidently wrong because they had no access to the protocol's latest documentation. We built a retrieval-augmented knowledge engine that answers developer and investor questions directly from their whitepapers, audit reports, and GitHub docs, citing the exact source section behind every response.
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In this domain a wrong answer about a smart contract carries real financial risk, so grounding mattered more than fluency. We delivered a retrieval pipeline with source attribution on every answer, semantic grounding in DeFi concepts such as yield farming and gas optimisation, and multi-file synthesis that combines a PDF whitepaper with a living GitHub document into one coherent response.
Senior engineers were spending 15 to 20 hours a week answering repetitive technical questions about slippage calculations and audit validity. General-purpose assistants gave outdated or subtly wrong answers because they had no access to the protocol's latest unindexed updates, and a wrong answer about a smart contract carries real financial risk.
A recursive parser ingested over 500 pages of audits and whitepapers into a Pinecone vector store while preserving the hierarchy of code blocks, tables, and footnotes. Hybrid search pairs vector similarity with keyword matching so specific function names resolve precisely, a guardrail layer blocks financial advice, and every GitHub docs change refreshes the knowledge base within seconds.
Over 68 percent of technical support queries are now resolved entirely by the AI with no human involvement, at a 99 percent factual accuracy rate on protocol-specific details. The team reclaimed more than 50 engineering hours per week and pulled its next mainnet release forward by three weeks.
View Impact
In this domain a wrong answer about a smart contract carries real financial risk, so grounding mattered more than fluency. We delivered a retrieval pipeline with source attribution on every answer, semantic grounding in DeFi concepts such as yield farming and gas optimisation, and multi-file synthesis that combines a PDF whitepaper with a living GitHub document into one coherent response.
Senior engineers were spending 15 to 20 hours a week answering repetitive technical questions about slippage calculations and audit validity. General-purpose assistants gave outdated or subtly wrong answers because they had no access to the protocol's latest unindexed updates, and a wrong answer about a smart contract carries real financial risk.
A recursive parser ingested over 500 pages of audits and whitepapers into a Pinecone vector store while preserving the hierarchy of code blocks, tables, and footnotes. Hybrid search pairs vector similarity with keyword matching so specific function names resolve precisely, a guardrail layer blocks financial advice, and every GitHub docs change refreshes the knowledge base within seconds.
Over 68 percent of technical support queries are now resolved entirely by the AI with no human involvement, at a 99 percent factual accuracy rate on protocol-specific details. The team reclaimed more than 50 engineering hours per week and pulled its next mainnet release forward by three weeks.
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