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ENTRY NO. 01Restaurant review intelligenceDemo availableAWS Bedrock / OpenSearch / source-linked answersRAG POC / DEMO AVAILABLE

TasteTrend Analytics

Identity · Client-demo RAG proof of concept

AI RAG over restaurant reviews. Ask a question, inspect the evidence, open the demo.

AWS Bedrock / OpenSearch / source-linked answers

Evidence boundary

What is demonstrated, and where the claim stops.

Repository fact

What this proves

  • /A heterogeneous review dataset can be normalised, indexed, queried, and surfaced through a working web interface.
  • /The response contract can return supporting review records alongside a generated answer.
  • /The repository contains deployable AWS infrastructure and a documented ingestion run.

What this does not prove

  • /Production reliability, monitored uptime, or a service-level agreement.
  • /Retrieval quality or grounding scores without a saved evaluation artifact.
  • /Measured client time savings or business outcomes.

Data boundary

A documented proof-of-concept run over four heterogeneous review inputs. The repository records 1,660 indexed review records; it is not a production client corpus.

Last verified

2026-07-06

Inspect evidence source →

Evidence type

repository fact

PoC dataset and run; no production SLA or client outcome claimed.

Known limitations

  • /The documented dataset is PoC-sized and its validation artifact records source-quality warnings.
  • /The evaluation harness exists, but no current result is published.
  • /End-to-end behavior depends on configured AWS services and credentials.

What production would require

  • /A governed ingestion schedule, tenant isolation, and stronger authentication.
  • /Repeatable retrieval and grounding evaluation with versioned artifacts.
  • /Monitoring, alarms, cost controls, retries, and operational ownership.
Problem

Heterogeneous review files need one queryable, source-linked interface without hiding the underlying evidence.

System Flow
5 stages · click to inspect
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Click any stage to inspect
Signature Module · Client-demo RAG proof of concept

Inspect the PoC flow

AWS Bedrock / OpenSearch / source-linked answers

Follow review inputs through normalisation, Titan embeddings, OpenSearch retrieval, and a source-linked answer.

TasteTrend · documented PoC flowinspectable
INPUTfour heterogeneous review files
ETLnormalise · validate · record warnings
EMBEDAmazon Titan Embed Text v2configuration
INDEXOpenSearch KNN · review records
AGENTBedrock Agent invokes search action
OUTPUTanswer + supporting review records

Demonstrated Change

Demo scope
Before

Separate review files with inconsistent schemas and manual inspection.

->
Demonstrated build

One inspectable PoC flow from normalisation to source-linked answers.

The PoC demonstrates a complete path from review ingestion to a source-linked answer in a browser demo.

PoC dataset and run; no production SLA or client outcome claimed.

Proof Signals

Classified evidence
1,660
review records indexed
Repository fact
4
review sources normalised
Repository fact
0
indexing failures
Repository fact

Every signal is classified as a repository fact, recorded test, configuration, or disclosed data boundary.

Why This Is Hard

3 engineering challenges
Challenge · 01

Schema normalisation

source files use different column names, scales, and missing-value patterns.

Challenge · 02

Evidence preservation

generated answers must retain a path to supporting review records.

Challenge · 03

Managed-service boundaries

the browser, API, agent, Lambda functions, and index must share a stable contract.

Engineering Depth

3 topics · click to expand

The active PoC uses Titan embeddings, OpenSearch KNN retrieval, a Bedrock Agent, Lambda functions, and API Gateway.

Key numbers
1,024-dimTitan embedding configuration
12questions defined in the evaluation harness
Built withAWS BedrockOpenSearchLambdaAPI GatewayPythonReact
Open demoInspect repository