GDPR
GDPR for AI startups: the launch decisions that matter early
A practical overview of where data enters the system, which workflows need explicit decisions, and how to avoid compliance debt before product-market fit.
Read guideAI feature build
AI data flow: where features quietly get complicated
A guide to implementation decisions around prompts, inputs, outputs, logging, and ownership when shipping an AI-assisted feature.
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What this guide helps you map before shipping an AI feature
This is a flow-first pass for AI-assisted features where input, handoff, logging, and reuse can quietly become hard to explain once the product starts moving.
Input to output
Know where the flow starts, where it hands off, and where the response comes back.
Boundary to provider
Check what leaves your system, which vendor sees it, and what it is allowed to keep.
Logging and reuse
If logs, retries, or debug copies exist, they need a reason and an owner.
Stop the launch
If the team cannot explain the path clearly, someone should be able to pause it.
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Read guideNext step
If the data path is already spreading, map it before the next release.
A structured pre-launch blueprint or audit helps turn unclear data handling into a system the team can still reason about as the feature grows.