In my previous article, I built an AI-powered resume screening and job matching solution in Snowflake. That version followed a more structured and deterministic approach: resumes were parsed from PDF candidate details were extracted candidate seniority was classified resumes and job descriptions were embedded candidates were ranked against jobs using […]
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PDF Resumes to AI-Powered Hiring Decisions: Recruitment teams often work with two very different types of data at the same time: Unstructured data like resumes in PDF format Structured data like job postings, roles, and required skills Traditionally, this kind of use case would require multiple systems: a document parser, […]
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Cost Intelligence in Snowflake using Cortex Code Custom Skills enables automated, consistent analysis of warehouse usage by turning AI into a domain-specific FinOps investigator. Why we Built This In most Snowflake environments, one question comes up repeatedly: 💡 The Recurring Question “Why did warehouse cost suddenly spike?” The problem is […]
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A Cortex Agent is an AI reasoning engine that lives entirely inside your Snowflake account. It is not just a chatbot. It is an autonomous orchestrator that: Understands natural language questions Classifies intent — structured data query? document lookup? or both? Routes to the right tools — Cortex Analyst for […]
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If you have been working with Snowflake’s Document AI for PDF extraction, there is an important update you need to know about. Snowflake has officially deprecated Document AI and the model-build PREDICT method. In its place, Snowflake has introduced a far simpler, more powerful, and production-ready alternative: AI_PARSE_DOCUMENT. This blog […]
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Every data engineer who has worked with Snowflake Tasks config has faced this scenario: your pipeline runs perfectly in production on a daily schedule. Then someone walks up and says: “We need a one-time full reload for January data — something went wrong at source.” “Can you run the pipeline […]
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