Tim FinchProducts, systems, AI
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Open to product, platform, and AI work.

I build evidence-backed AI products and the systems needed to operate them responsibly, usually where product decisions and real workflows meet.

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Data & Analytics

TrendNest

A tool for turning messy trend signals into topic views that are easier to trust.

2025 / Data & Analytics / Python / FastAPI / PostgreSQL / Embeddings / Next.js

Quick read

A clear breakdown of the product, the reasoning behind it, and the implementation choices that matter.

Year
2025
Category
Data & Analytics
Status
In use

Overview

TrendNest is a trend discovery tool that gathers weak signals from multiple sources and organizes them into topic views for product, content, and campaign decisions. It keeps ingestion quality, clustering, and presentation aligned so the signal stays readable without pretending it is more certain than it is.

Why it exists

Trend research often ends up split across spreadsheets, screenshots, and intuition, which makes it hard to compare sources or explain why something matters.

How it works

I built a service that ingests mixed signals, groups related items into topic clusters, and presents them through a reviewable interface with source-level traceability.

Built with

Python / FastAPI / PostgreSQL / Embeddings / Next.js

What I focused on

  • Combined structured and unstructured source ingestion in one pipeline.
  • Used embedding-based grouping to reduce duplicate topic discovery.
  • Stored source references for each cluster to support manual review.
  • Scored velocity, recurrence, and cross-source agreement.

Where to look

GitHub ↗

Repository snapshot

Repo
trendnest
Language
Python
Updated
Feb 20, 2026