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2-part series · Cross-industry · Builder Center

Building Data Lineage on AWS

Most enterprises can't say where the numbers in their regulatory reports come from without weeks of work. Two articles on lineage that AI builds and people confirm: the design principle, then the build on AWS.

How it's built

Why + how: the design principle, then the AWS build

Who it's for

Data platform & governance leads, CDOs, risk and compliance teams, data engineers

Reading paths

Leaders: Part 1 · Builders: Part 2

Start with Part 1: Data lineage you can defend, part 1: AI proposes, people decide →

Reading path

Start at Part 1, or jump to the part you need
01

Data lineage you can defend, part 1: AI proposes, people decide

Ask a bank's risk function where a figure in its regulatory return came from, and the honest answer is often "give us a few weeks."

Builder Center
02

Data lineage you can defend, part 2: AI-assisted lineage on AWS

How do you build lineage an auditor will accept without hand-tracing every pipeline?

Builder Center
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Other series

12-part series · Builder Center

The Autonomous NOC

47 alarms to one root cause in under 90 seconds, safely enough to act on a live network. Twelve articles on how, why, and what it costs.

Telco
4-part series · Builder Center

Bank Foundation Models

Why a bank should train a foundation model on its own event data, and how: from privacy-first data to production and Nova Forge.

Financial Services
2-part series · Builder Center

GAD-P: Governed data access

Let every business user ask your data questions in plain English, with governance enforced by code rather than by prompt.

Cross-industry
3-part series · Builder Center

Dark Web Fraud Signals

Catch fraud techniques on dark-web forums weeks before they hit your transaction monitoring.

Financial Services
2-part series · Builder Center

Real-time Fraud with TGNs

Graph-based fraud detection in under 100 ms that keeps working when you move to a new payment domain.

Financial Services
2-part series · Builder Center

The Fast Path

Cut bank loan decisions from about 10 days to minutes, in six weeks.

Financial Services
7-part series · LinkedIn

AI Value Strategy

95% of AI projects never reach production. A seven-part guide to making sure yours delivers value you can measure.

Cross-industry
2-part series · AWS Blog

Synthetic Data

How to trust synthetic data, and how to use it where real data is restricted.

Cross-industry
10-part series · LinkedIn

Startup AI Readiness

Every AI readiness framework was built for enterprises. This 10-part, research-grounded one is for startups and teams under 50: assess where you stand, decide build vs buy, ship your first agent, measure it, govern it and price it.

Cross-industry
9-part series · Builder Center

Containing the Agent, Counting the Value

By 2026, enterprise AI agents stopped advising and started acting. Eight articles on containment, plus a dashboard walkthrough: when an agent does the wrong thing, can you stop it, can you prove it, and is it even worth running, ending in a value-and-risk ledger that tests every workload six ways and never blends them into one comforting score.

Cross-industry
6-part series · Builder Center

FaultForge: Synthetic Failure Data for Robot Fleets

Robot fleets fail in ways single-robot datasets never show, and the benchmarks meant to catch those failures can be passed without any reasoning. FaultForge generates rare fleet-wide failures with known causes, then audits the data so no shortcut can pass.

Robotics
2-part series · Builder Center

Context Engineering for AI Coding Agents

AI coding agents repeat the mistakes you already corrected and lose context when they hand work to each other. Two companion articles: building a self-improving loop in Kiro from Amazon's Trace research, and how today's agents and research tackle both kinds of forgetting.

Cross-industry