Inspiration
Group plans often reflect the loudest voice. TasteBridge asks a different question: what can everyone reasonably enjoy, while respecting each person's budget, access needs and vetoes?
What it does
TasteBridge is a live Qloo-powered group decision tool. A host reviews one cultural preference for each of 2–6 guests, reviews 2–5 real places, and supplies current price and accessibility facts. Hard constraints and vetoes are applied before Qloo affinity ranking. The tool compares within-query midranks, prioritizes the lowest guest rank and then the mean, and makes ties explicit. People make the final decision; the application does not book or pay.
Try the live app: https://tastebridge-carlosjv.zrm7tv2zmj.chatgpt.site
For a walkthrough without consuming API calls, open the clearly labelled recorded case. Its dated Qloo evidence is real; its test preferences and prices are synthetic operator inputs. It is not a fresh recommendation.
How we built it
The public implementation uses React/Vinext, TypeScript, Cloudflare Workers and D1. Server-side Qloo Search resolves cultural titles and places; Qloo Insights supplies cross-domain affinity evidence. Address and description support explicit entity review. Signed selections expire after one hour, host-reported facts after 24 hours, and edits invalidate previous proposals.
TasteBridge is a bounded deterministic agentic decision tool with search/evaluate actions. It does not include a separately deployed LLM agent. Scores from separate queries are not assumed comparable: the declared ranking policy uses ordinal ranks within each guest's common shortlist. Missing, incomplete or constant evidence triggers abstention.
Challenges we addressed
Live testing exposed identically named museums in different countries, incomplete affinity coverage and a hosted transport incompatibility. We expose place details, preserve abstention and reject redirects. We also bound request/response sizes, use timeouts, keep the Qloo key server-side, and prevent stale asynchronous responses from appearing after input edits.
Verification and trade-offs
A hosted HTTP workflow completed four real Qloo searches and two real Insights requests. The two test profiles disagreed, producing an explicitly tied shortlist rather than false consensus. Anonymous homepage/API access was verified. Ten hosted policy checks and 52 Python regression tests passed.
An exhaustive synthetic policy comparison covers 216 strict ordinal profiles with three guests and three options. Max-min improves the minimum rank in 27 cases versus mean-only, with an average mean-rank sacrifice of 0.013889. This illustrates a policy trade-off; it does not demonstrate higher actual satisfaction or superiority over LLM recommendations. Desktop browser checks also verified the recorded example, correct tie handling, proposal invalidation after a veto, and abstention when only one option remains. Mobile and complete live interactive browser testing remain pending.
What we learned
Cultural intelligence is most useful when a decision process can explain uncertainty and disagreement. Qloo affinity does not establish venue price, accessibility or personal enjoyment. Those boundaries must remain visible.
Availability and next steps
The experimental public demo enforces a durable total allowance of 60 provider calls with a one-hour cache and no automatic retries. This is our application cap, not a statement of Qloo's provider quota. Live requests can exhaust the allowance; the recorded evidence walkthrough remains available without live calls. Provider credential expiry and judging-period allowance still require confirmation.
Next steps are usability testing with real groups, broader venue coverage and comparative recommendation evaluation. No customers, revenue or measured satisfaction gains are claimed.
Open source and development disclosure
Developed by Carlosjv with AI assistance. Complete version 0.3.2 source, assets, tests, retained vendor notices and redacted integration evidence are published under MIT at https://github.com/carlosjunquerovila-afk/tastebridge. Download TasteBridge-0.3.2-source.zip and follow the repository extraction/build instructions. No credentials are included. Earlier synthetic and Python prototypes remain clearly separated from the current hosted implementation.
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