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Amperity vibe coding AI agent connects directly to the customer’s Databricks environment via native compute and LLM endpoints to quickly execute complex tasks such as identity resolution

June 10, 2025 //  by Finnovate

Customer data cloud startup Amperity Inc. is joining the agentic AI party, launching Chuck Data, an AI agent that specializes in customer data engineering. Chuck Data is trained on massive volumes of customer data from more than 400 enterprise brands. This “critical knowledge” base allows it to execute tasks such as identity resolution and personally identifiable information tagging autonomously and instantly resolve customer identities, with minimal input from human developers. The agent is designed to help companies dig up customer insights much faster. Chuck Data makes it possible for data engineers to embrace “vibe coding,” so they can use natural language prompts to delegate these manual coding tasks to an autonomous AI assistant. The company said Chuck Data connects directly to the customer’s Databricks environment via native compute and large language model endpoints. Then it can quickly execute complex tasks such as identity resolution – which involves pulling data from multiple profiles into one – as well as compliance tagging and data profiling. One of Chuck Data’s core features is Amperity’s patented identity resolution algorithm, which is based on the proprietary Stitch technology that’s used within its flagship cloud data platform. The company said users can run Stitch on up to 1 million customer records for free, and for those with bigger records, they can sign up to Chuck Data’s research preview program to access free credits. It’s also offering paid plans that unlock unlimited access to Stitch, enabling companies to create millions of accurate, scalable customer profiles. huck Data provides yet more evidence of how CDPs are evolving from activation tools into embedded intelligence layers for the customer engagement data value chain.

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Category: AI & Machine Economy, Innovation Topics

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