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Shine Solutions Group

LLM Agents & RAG · MLOps & Infrastructure · Natural Language ProcessingMelbourne, AustraliaFounded 1998

Shine Solutions Group is based in Melbourne, Australia and works in Large Language Models for General Retail, with further work in MLOps & Infrastructure and Natural Language Processing.

Average rating
—
Reviews
0
Profile coverage
70%
Evidence percentile
P51

Profile updated · Request a correction

Company & commercials

Primary category
LLM Agents & RAG
Team size
Not disclosed
Typical budget
Not disclosed
Primary industry
Retail, Wholesale & Consumer Goods
Contact provider →Visit website ↗
Overview

What Shine Solutions Group does best.

About

LLM Agents & RAG provider for Retail, Wholesale & Consumer Goods

Shine Solutions Group is a leading Australian technology consultancy delivering technical excellence in cloud solutions, generative AI engineering, data analytics, and digital transformation for enterprise and government partners across Australia. Its own website shows its strongest capability in Large Language Models within LLM Agents & RAG, alongside Retrieval-Augmented Generation. The industry it describes most is General Retail.

Service model·Service
Primary AI categoryLLM Agents & RAG
Benchmarked against 1,860 providers in this category.
Primary industryRetail, Wholesale & Consumer Goods
Technology stack

11 platforms & methods

Bars show how many mapped capabilities use each one.

  • AWS1 capability
  • Google Cloud1 capability
  • GitHub Copilot1 capability
  • ReactProfile only
  • React NativeProfile only
  • Spring BootProfile only
  • Node.jsProfile only
  • LambdaProfile only
  • TypeScriptProfile only
  • JavaProfile only
  • PythonProfile only
RankGlobal provider intelligence

Evidence report

How Shine Solutions Group compares with peers on evidence, reviews and coverage.

Analyst brief · Published
CategoryLLM Agents & RAG
Compared with1,860 providers
Signals3 signals
Status● Published
Evidence score
67/100
Moderate evidence51st percentile of 1,860 peers · peer median 70
Profile coverage70
Taxonomy density100
Review signal0
Peer benchmarkHow the profile comparesLLM Agents & RAG among 1,860 published providers
Average rating0.00 · median 4.89
Independent reviews0 · median 0
Profile completeness70% · median 70%
Taxonomy breadth16 · median 20
This profile Peer median
Signal radarMulti-dimensional evidence
Independent reviewsCoverageBreadth
This profile (percentile) Peer median
Industries5 industries
Transportation, Logistics & Supply Chain33%
Financial Services & Insurance17%
Government & Public Sector17%
Media, Entertainment, Gaming & Sports17%
Retail, Wholesale & Consumer Goods17%
Share of mapped industries, not share of work or revenue.
Evidence mixMapping grades
81%Direct · 13 mappings
19%Supported · 3 mappings
Grades across 16 mappings. Not a search ranking.
Analyst summary

What the evidence says

Shine Solutions Group presents as a moderate evidence profile for LLM Agents & RAG. It ranks in the 51st percentile of 1,860 published providers in LLM Agents & RAG, and no reviews on the profile yet.

Current positioning: P51 evidence quality · P37 industry breadth
Strongest signalsEvidence-backed strength in LLM Agents & RAG is the profile's clearest signal in the mapped taxonomy.
Best user fitRetail, Wholesale & Consumer Goods buyers evaluating LLM Agents & RAG across engagement sizes.
Confirm before engagementConfirm current delivery capacity directly — mapped signals reflect profile evidence, not live availability.
How this report is calculated →
Capabilities

AI capabilities.

Primary AI category · 1 / 10

LLM Agents & RAG

—
DirectSupportedRelatedAdjacentOne of 1,861 providers in this category
Compare LLM Agents & RAG providers →
Technology usedGitHub Copilot

Mapping source · https://shinesolutions.com/ — “"/> Building a Lightweight RAG System with the AWS S3 Vector Buckets Large language models (LLMs) can be used to help engineers analyze design documents and ver”

Featured 10 of 10 capabilities, ranked by mapping grade then confidence.

Industry experience · 5 industries · 6 subindustries

Industries served.

5 Core0 Adjacent · discovery only
Retail, Wholesale & Consumer GoodsOther providers in Retail, Wholesale & Consumer Goods →
  • General RetailDirect · Primary
    95%

    https://shinesolutions.com/portfolio_page/myer-unlocks-fresh-business-insights-with-google-analytics-360-migration-from-usa-to-australia — “ith GCP’s BigQuery Eliminating need of 24/7 compute instance Industry Retail Geography Australia Myer is one of Australia’s most iconic department”

Client feedback

What clients say.

No independent reviews found for Shine Solutions Group yet.

Worked with Shine Solutions Group? Review them → Every reviewer is verified by RankGlobal.

Methodology

How RankGlobal maps this profile.

RankGlobal maps this profile against a controlled taxonomy. Mapping grades on capability and industry cards describe how the profile is classified. Source strength for ranking decisions follows the hierarchy published on Research — a mapping grade is not a claim of discoverability weight.

  1. T1AuthoritativeTypical evidenceRegulators, registries, certifications, signed client evidence.Scoring useHighest evidentiary weight
  2. T2IndependentTypical evidenceCredible media, industry bodies, partner directories, third-party datasets.Scoring useStrong with attribution and recency
  3. T3Provider-controlledTypical evidenceCompany site, case studies, press releases, structured submissions.Scoring useAccepted as a claim; verification raises weight
  4. T4Discovery-onlyTypical evidenceDirectory listings, aggregations, and early discovery signals.Scoring useUsed for discovery; weighted accordingly in ranking
Direct, Supported, Related and Adjacent appear on mapped cards as classification grades. They do not rank how discoverable a provider should be.RankGlobal trust center →
Ready to evaluate this provider

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Before you reach outKey facts, and three things to confirm once you're in touch.
Primary category
LLM Agents & RAG
Primary industry
Retail, Wholesale & Consumer Goods
Typical budget
Not disclosed
Team size
Not disclosed
  1. 1Name the use caseSay which LLM Agents & RAG problem you are evaluating, so the research team can route your message accurately.
  2. 2Pressure-test the budget bandNo budget band is on file. Ask what a scope like yours typically lands at.
  3. 3Ask for a referenceRequest a client reference in Retail, Wholesale & Consumer Goods — the strongest industry signal on this profile.
Still comparing? Re-read the mapping evidence or go back to all providers.

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Three fields. Anything longer belongs on the full contact page, linked below.
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