Challenge · 01
Evidence separation
synthetic business context must not be confused with retrieved public evidence.
<- AI Systems Dossier
ENTRY NO. 02Hackathon market-intelligence workflowHackathon demoStructured analysis / Qdrant evidence / workflow traceDECISION SUPPORT / HACKATHON DEMO
PiacRadar
Identity · Hackathon case study
LLM market-intelligence workflow. One question becomes hypotheses, evidence, and an action plan.
Structured analysis / Qdrant evidence / workflow trace
Evidence boundary
What is demonstrated, and where the claim stops.
Synthetic dataRepository fact
What this proves
- /One strategic question can be transformed into a structured decision package.
- /Hypotheses, evidence references, actions, and validation tasks can share one typed workflow.
- /A cached demo path can remain inspectable when live services are unavailable.
What this does not prove
- /Causal attribution or a validated business recommendation.
- /Production evidence quality across all public sources.
- /Measured executive time savings or commercial impact.
Data boundary
Core company and market data for the FreshCart scenario is synthetic/generated. Retrieved public evidence is kept separate and varies in quality.
Evidence type
synthetic data / repository fact
Core company and market data is synthetic/generated; public evidence quality varies. Decision support, not causal proof.
Known limitations
- /The core FreshCart scenario uses synthetic/generated data.
- /Public evidence quality and scrape success vary.
- /The deterministic path is directional and the optional LLM path may not be active.
What production would require
- /Governed client connectors, identity, access control, and data isolation.
- /Human review, evidence-quality scoring, and persisted analysis history.
- /Monitoring for the API, retrieval layer, orchestration, and model calls.
Problem
A strategic market question needs to become an auditable decision workflow rather than a one-shot answer.
System Flow
5 stages · click to inspect
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Click any stage to inspect
Signature Module · Hackathon case study
Inspect the decision package
Follow one strategic question through context assembly, evidence retrieval, hypothesis ranking, actions, and validation tasks.
PiacRadar · decision packageinspectable
INPUTone strategic market question
CONTEXTsynthetic company data + public evidence
RETRIEVEQdrant evidence when configured
REASONrank hypotheses + validation tasks
OUTPUTbrief · actions · sources · workflow trace
BOUNDdecision support · not causal proof
Demonstrated Change
Demo scopeBefore
A strategic question spread across disconnected signals and ad-hoc analysis.
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Demonstrated build
A structured demo package with hypotheses, evidence, actions, and validation tasks.
The hackathon build produces a structured decision package with ranked hypotheses, an executive brief, actions, evidence references, and a workflow trace.
Core company and market data is synthetic/generated; public evidence quality varies. Decision support, not causal proof.
Proof Signals
Classified evidence8
validated demo artifacts
Repository fact
60
companies in source list
Synthetic data
1
decision package per request
Repository fact
Every signal is classified as a repository fact, recorded test, configuration, or disclosed data boundary.
Why This Is Hard
3 engineering challengesChallenge · 02
Structured reasoning
hypotheses, actions, and validation tasks need a stable contract.
Challenge · 03
Demo resilience
cached analysis must remain transparent when live integrations are unavailable.
Engineering Depth
3 topics · click to expandThe analysis orchestrator stages refinement, aggregation, retrieval, hypothesis generation, scoring, executive briefing, and trace assembly.
Key numbers
3request modes defined: demo, enriched, live
8cached artifacts required by validator
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