Suggest a Purchase ...And More!

A new in-house capability — demonstrated by Suggest-a-Purchase

Ray Voelker
Cincinnati & Hamilton County Public Library
ray.voelker@chpl.org

The opportunity

  • A whole class of software is specific to how CHPL works — our workflows, our systems, our customers.
  • Too specific for an outside product to build for us; too big a lift for our in-house capacity to take on.
  • That math just changed. Agentic coding makes production-quality, CHPL-specific software practical for one staff person to build — fast.

Suggest-a-Purchase

A customer recommends something for the collection.

Patron to web app to bot to staff flow

Built entirely on tools CHPL already owns — Sierra, existing servers, public APIs.

Live demo

The live app — ↓ to walk the flow if needed.

Live app · 2-minute recording embedded as the safety net

Sign in

Customer login with library card

library card login

Suggest

Submit a purchase suggestion

plain-language request — no forms

Track

My Requests with status

your suggestions + status

Staff review

Bot-enriched staff queue in Datasette

a bot-enriched queue in Datasette

Auto-enriched

Request enriched from Open Library

matched & enriched from Open Library

How it got built

Built in-house, in weeks — and built to last:

  • Open-source, non-proprietary tools — no vendor lock-in.
  • Fully documented — design-doc first.
  • Rigorously tested — 340 automated tests.
  • Built to be picked up and extended by whoever comes next.

The capability is the story — not just this one app.

The capability compounds

The real goal: less friction between a customer and the item they want.

  • Suggest-a-Purchase: we don’t own it → the customer asks → we can act.
  • The same tool could surface more — e.g. subscribe to a favorite author, and a match becomes a one-click hold.
  • Never auto-placed — the customer stays in control.

Same Sierra integration. Same Datasette pattern. Same audit trail.

Where this goes next

  • Partner with MSA (Materials Selection & Acquisition) to dog-food it internally first.
  • Smooth the workflow, work out the bugs — then put it in front of customers.
  • Reusable patterns — each next tool of this shape goes faster.

The capability compounds. That’s the story.

Resources

Built with — open tools, public data:

↓ data sources & directions explored

Data & directions explored

Appendix

Q&A backup — ↓ for screenshots.

Full architecture

Full architecture · ↓ My Requests · staff queue · enrichment

My Requests

Customer — My Requests

what the customer sees after submitting

Staff queue

Staff — completed queue

completed & bot-enriched, in Datasette

Open Library enrichment

Open Library enrichment detail

matched edition + metadata (JSON)

Thank you

Questions, ideas, or CHPL-specific tools you'd want built next?

Ray Voelker
ray.voelker@chpl.org