Selected work
Applied AI · Intelligence

Lurkee

A monitoring system that turns website changes into prioritized business intelligence through scheduled collection, deterministic diffing, structured LLM analysis, and reports.

StatusPre-launch
Period2025–26
My scopeSystem design · FastAPI backend · AI analysis pipeline · Product UI
01 / Context

The system behind the interface.

A changed page is not automatically useful intelligence. The product needs to separate noise from meaningful signals without hiding the source evidence from the operator.

02 / Decisions

Architecture choices that shaped the product.

Deterministic before probabilistic

Hashing and diffs establish what changed before an LLM is asked to explain why the change may matter.

Structured model output

Severity and findings use typed schemas so the result can drive alerts, reports, and filters instead of becoming an unbounded paragraph.

Route cost by importance

Routine analysis can use a lower-cost model while stronger reasoning is reserved for findings that cross a severity threshold.

03 / Evidence

What exists beyond the concept.

  • Scheduled collection with content hashing and unified change detection
  • Structured severity classification before reporting and alerts
  • Operator-facing history, report, billing, and system-health workflows
FastAPIPythonOpenAIPostgreSQLNext.jsStripeResend
04 / Outcome

A production-minded result.

A working end-to-end monitoring pipeline and dashboard foundation. The current implementation is described as multi-stage, not as a LangGraph system.

Have a system like this to build?

Let’s turn the hard parts into a dependable product.

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