CASE 162 · KRAIT · 2025
Internal docs that the new engineer can actually find.
An engineering org had documentation across Notion, Backstage, GitHub READMEs, and a dozen old Confluence pages nobody had migrated. Searching for an answer meant guessing where it might live. We deployed Amazon Kendra against all four sources with a unified search interface.
Engineering org (internal)
PLATFORM
2025
RESULTS
What changed, by the numbers.
TIME-TO-FIND-ANSWER
−68%
SOURCES UNIFIED
4
RELEVANCE TUNING
KENDRA ML
SUPPORT QUERIES IN #ENG-HELP
−42%
HOW IT WENT
The Slack channel #eng-help was the de facto answer system, because the canonical search across systems didn’t work. New engineers asked questions whose answers were technically documented somewhere — they just couldn’t find them.
Kendra’s pre-built connectors ingested Notion, GitHub, Backstage, and the Confluence archive. A small Lambda fronted the Kendra index with a Cognito-authenticated UI that engineers could open from any browser. Kendra’s relevance ML tunes itself from click-through signals over time.
Time-to-find-an-answer dropped 68% in the new-hire survey three months after rollout. Support queries in #eng-help dropped 42% — the questions still come, but they’re harder ones that genuinely need a human. The first 58% of "where is this documented?" answered itself.
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