From Data Lake to Claude-ready: Building enterprise context on AWS and Databricks
Claude is only as useful as the data around it, and most data lakes weren't built for that. Here's how to structure context on AWS and Databricks without creating a…
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Claude is only as useful as the data around it, and most data lakes weren't built for that. Here's how to structure context on AWS and Databricks without creating a…
The model-selection conversation often starts with the wrong question:
The first version of an enterprise copilot usually begins with a familiar request:
By now, almost every leadership team has said some version of the same thing:
Over the past year, enterprise engineering teams have rapidly transitioned from single-turn Retrieval-Augmented Generation (RAG) pipelines to background multi-agent orchestrations. Rather than simply answering single-turn user queries, autonomous agents plan…
For fintech and healthtech organizations, governance is not a “nice to have.” It is embedded in laws, supervisory expectations, and customer trust. Financial institutions must prove who accessed which transaction…
Every business wants real‑time intelligence. In fintech, fraud needs to be stopped before authorization completes. In adtech, bids must be priced in milliseconds. In supply chains, routing decisions have to…
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Most enterprise AI initiatives begin with an impressive demo. A developer hooks a hosted SaaS model API up to an internal document store over a weekend.
Across the industry, AI budgets are growing fast. Finance teams are approving significant spend on:
If you have ever used an AI coding assistant like Claude Code, Cursor, or GitHub Copilot, you have probably noticed something annoying.
The old debate of ETL vs. ELT made sense when the main constraint was warehouse compute. Today, the constraints look very different - AI systems that demand messy, high‑granularity history…