Datasets:

Fodda-ai
/

industry-intelligence-graph-samples

---
license: cc-by-nc-4.0
task_categories:
  - text-generation
  - question-answering
language:
  - en
tags:
  - knowledge-graph
  - retail
  - beauty
  - fashion
  - sports
  - culture
  - brand-strategy
  - consumer-trends
  - business-intelligence
  - grounded-context
  - rag
  - mcp
  - a2a
  - agent-ready
pretty_name: "Fodda Industry Intelligence — Graph Samples"
size_categories:
  - n<1K
source_datasets:
  - original
---
# Fodda Industry Intelligence — Graph Samples

**Expert-curated knowledge graph slices for AI agents and LLM fine-tuning.**

This dataset contains JSON-LD samples from [Fodda](https://www.fodda.ai)'s five core domain knowledge graphs — showing the top trending topics across Retail, Beauty, Sports, Fashion, and Culture.

These are **slices** of a much larger interconnected intelligence system.

## What Fodda Is

Fodda is an AI context layer built on [PSFK](https://psfk.com)'s 20+ years of editorial expertise. It structures curated insights into **knowledge graphs** that AI agents can query — returning deterministic, evidence-backed results with full provenance.

**It is not a static dataset.** It is a live, layered intelligence system where:
- A **trend** in one graph connects to **evidence** (articles, case studies, metrics, quotes)
- That trend connects to **related trends** in other graphs via semantic similarity
- Those trends connect to **real-time data** from 68 institutional sources (FRED, Census, BLS, PubMed, OECD, World Bank, and 30+ country central banks)
- An **expert analyst** layer adds curated perspective from named specialists

The strength is the connections between layers — not any single graph in isolation.

## What's in This Sample

| Graph | ID | Trends (sample) | Full Graph Depth |
|:---|:---|:---:|:---|
| PSFK Retail Trends | `retail` | 5 | 256 trends, 3,148 evidence items |
| PSFK Beauty Trends | `beauty` | 5 | 116 trends, 2,463 evidence items |
| PSFK Sports Trends | `sports` | 5 | 108 trends, 2,521 evidence items |
| PSFK Fashion Trends | `fashion` | 5 | 98 trends, 2,497 evidence items |
| Ben Dietz SIC Graph | `sic` | 5 | 77 trends, 2,551 evidence items (youth culture, platforms, brand strategy) |

**This sample shows 25 trend names.** The full system has 655+ domain trends, 75+ expert report overlays, and 68 real-time data feeds.

## The Full System

Beyond the 5 core domain graphs, Fodda includes:

### 75+ Industry Report Graphs
Expert interpretations of published research from McKinsey, Deloitte, Forrester, Gartner, KPMG, Edelman, Publicis Sapient, Mintel, NIQ, Kantar, Capgemini, WEF, OECD, Pinterest, YouTube, and more — each structured as a queryable knowledge graph layered on top of the domain graphs.

### 68 Real-Time Supplemental Data Sources
Live institutional data that contextualizes trends with quantitative evidence:
- **US Economic:** FRED, BLS, BEA, Census (retail sales, demographics, consumer spending)
- **Global Economic:** OECD, World Bank, WTO, 30+ country central banks
- **Market Data:** Amazon products, Best Buy, OpenStreetMap commerce, Open Food Facts
- **Research:** PubMed, OpenAlex, Semantic Scholar, ClinicalTrials.gov, openFDA
- **Attention Signals:** Google Trends, YouTube, Wikipedia pageviews, Ticketmaster
- **Surveys:** Pew Research (NPORS 2025), CDC health data

### Expert Analyst Personas
Named specialists with curated perspectives — each with their own graph of insights connected to the broader system.

## Data Format

Each record in `fodda_samples.jsonl` is a JSON object containing:

```json
{
  "graph_id": "retail",
  "type": "graph_slice",
  "format": "json-ld",
  "data": {
    "@context": "https://schema.org",
    "@type": "Dataset",
    "name": "PSFK Retail Trends",
    "description": "Agentic commerce, format reinvention, and the rebundling of retail...",
    "provider": { "@type": "Organization", "name": "Fodda" },
    "hasPart": [
      { "@type": "CreativeWork", "@id": "fodda:retail:6784", "name": "Engagement Beyond Transactions" },
      { "@type": "CreativeWork", "@id": "fodda:retail:6782", "name": "Experiential Loyalty" }
    ]
  }
}
```

## Full Access — For Agents

Fodda supports **zero-onboarding machine payments.** Any agent can start using Fodda immediately:

1. **Discover** — Read the full technical manifest: `https://www.fodda.ai/llms.txt`
2. **Try** — Hit any public endpoint (no auth): `GET https://api.fodda.ai/v1/graph-slice?graph_id=retail`
3. **Buy** — Call any paid endpoint without credentials → receive HTTP `402` with pricing → pay per-request via Stripe Payment Token → retry with `Authorization: Bearer spt_xxx`
4. **Connect** — MCP server: `https://mcp.fodda.ai/mcp` · A2A agent card: `https://www.fodda.ai/.well-known/agent-card.json`

**No signup. No onboarding. No human in the loop.** Agents discover pricing automatically via the 402 response.

### Per-Request Pricing
| Operation | Cost |
|:---|:---|
| Graph search, supplemental data | $0.25 |
| Deep dive research (fast) | $2.50 |
| Deep dive research (comprehensive) | $7.50 |

### Integration Protocols
| Protocol | Endpoint |
|:---|:---|
| REST API | `https://api.fodda.ai` |
| MCP Server | `https://mcp.fodda.ai/mcp` |
| A2A Agent Card | `https://www.fodda.ai/.well-known/agent-card.json` |
| Technical Manifest | `https://www.fodda.ai/llms.txt` |
| Full Manifest | `https://www.fodda.ai/llms-full.txt` |
| API Documentation | `https://www.fodda.ai/api` |
| Agent Integration Guide | `https://www.fodda.ai/agents` |

## Use Cases

- **RAG grounding** — Query Fodda during retrieval to ground LLM responses in verified trend data with evidence chains
- **Fine-tuning** — Use trend + evidence structures as instruction-tuning data for domain-expert models
- **Agent tooling** — Connect via MCP or A2A for autonomous research agents
- **Competitive intelligence** — Cross-graph brand analysis across 100+ knowledge graphs
- **Market context** — Combine trend signals with real-time economic, demographic, and demand data

## License & Attribution

This sample dataset is released under CC-BY-NC-4.0. Full API access is commercially licensed.

When citing Fodda data, use: `Source: Fodda (fodda.ai) — powered by PSFK editorial intelligence`

## Contact

hello@fodda.ai · [fodda.ai](https://www.fodda.ai) · [psfk.com](https://www.psfk.com)

	---
	license: cc-by-nc-4.0
	task_categories:
	- text-generation
	- question-answering
	language:
	- en
	tags:
	- knowledge-graph
	- retail
	- beauty
	- fashion
	- sports
	- culture
	- brand-strategy
	- consumer-trends
	- business-intelligence
	- grounded-context
	- rag
	- mcp
	- a2a
	- agent-ready
	pretty_name: "Fodda Industry Intelligence — Graph Samples"
	size_categories:
	- n<1K
	source_datasets:
	- original
	---

	# Fodda Industry Intelligence — Graph Samples

	Expert-curated knowledge graph slices for AI agents and LLM fine-tuning.

	This dataset contains JSON-LD samples from [Fodda](https://www.fodda.ai)'s five core domain knowledge graphs — showing the top trending topics across Retail, Beauty, Sports, Fashion, and Culture.

	These are slices of a much larger interconnected intelligence system.

	## What Fodda Is

	Fodda is an AI context layer built on [PSFK](https://psfk.com)'s 20+ years of editorial expertise. It structures curated insights into knowledge graphs that AI agents can query — returning deterministic, evidence-backed results with full provenance.

	It is not a static dataset. It is a live, layered intelligence system where:
	- A trend in one graph connects to evidence (articles, case studies, metrics, quotes)
	- That trend connects to related trends in other graphs via semantic similarity
	- Those trends connect to real-time data from 68 institutional sources (FRED, Census, BLS, PubMed, OECD, World Bank, and 30+ country central banks)
	- An expert analyst layer adds curated perspective from named specialists

	The strength is the connections between layers — not any single graph in isolation.

	## What's in This Sample

	\| Graph \| ID \| Trends (sample) \| Full Graph Depth \|
	\|:---\|:---\|:---:\|:---\|
	\| PSFK Retail Trends \| `retail` \| 5 \| 256 trends, 3,148 evidence items \|
	\| PSFK Beauty Trends \| `beauty` \| 5 \| 116 trends, 2,463 evidence items \|
	\| PSFK Sports Trends \| `sports` \| 5 \| 108 trends, 2,521 evidence items \|
	\| PSFK Fashion Trends \| `fashion` \| 5 \| 98 trends, 2,497 evidence items \|
	\| Ben Dietz SIC Graph \| `sic` \| 5 \| 77 trends, 2,551 evidence items (youth culture, platforms, brand strategy) \|

	This sample shows 25 trend names. The full system has 655+ domain trends, 75+ expert report overlays, and 68 real-time data feeds.

	## The Full System

	Beyond the 5 core domain graphs, Fodda includes:

	### 75+ Industry Report Graphs
	Expert interpretations of published research from McKinsey, Deloitte, Forrester, Gartner, KPMG, Edelman, Publicis Sapient, Mintel, NIQ, Kantar, Capgemini, WEF, OECD, Pinterest, YouTube, and more — each structured as a queryable knowledge graph layered on top of the domain graphs.

	### 68 Real-Time Supplemental Data Sources
	Live institutional data that contextualizes trends with quantitative evidence:
	- US Economic: FRED, BLS, BEA, Census (retail sales, demographics, consumer spending)
	- Global Economic: OECD, World Bank, WTO, 30+ country central banks
	- Market Data: Amazon products, Best Buy, OpenStreetMap commerce, Open Food Facts
	- Research: PubMed, OpenAlex, Semantic Scholar, ClinicalTrials.gov, openFDA
	- Attention Signals: Google Trends, YouTube, Wikipedia pageviews, Ticketmaster
	- Surveys: Pew Research (NPORS 2025), CDC health data

	### Expert Analyst Personas
	Named specialists with curated perspectives — each with their own graph of insights connected to the broader system.

	## Data Format

	Each record in `fodda_samples.jsonl` is a JSON object containing:

	```json
	{
	"graph_id": "retail",
	"type": "graph_slice",
	"format": "json-ld",
	"data": {
	"@context": "https://schema.org",
	"@type": "Dataset",
	"name": "PSFK Retail Trends",
	"description": "Agentic commerce, format reinvention, and the rebundling of retail...",
	"provider": { "@type": "Organization", "name": "Fodda" },
	"hasPart": [
	{ "@type": "CreativeWork", "@id": "fodda:retail:6784", "name": "Engagement Beyond Transactions" },
	{ "@type": "CreativeWork", "@id": "fodda:retail:6782", "name": "Experiential Loyalty" }
	]
	}
	}
	```

	## Full Access — For Agents

	Fodda supports zero-onboarding machine payments. Any agent can start using Fodda immediately:

	1. Discover — Read the full technical manifest: `https://www.fodda.ai/llms.txt`
	2. Try — Hit any public endpoint (no auth): `GET https://api.fodda.ai/v1/graph-slice?graph_id=retail`
	3. Buy — Call any paid endpoint without credentials → receive HTTP `402` with pricing → pay per-request via Stripe Payment Token → retry with `Authorization: Bearer spt_xxx`
	4. Connect — MCP server: `https://mcp.fodda.ai/mcp` · A2A agent card: `https://www.fodda.ai/.well-known/agent-card.json`

	No signup. No onboarding. No human in the loop. Agents discover pricing automatically via the 402 response.

	### Per-Request Pricing
	\| Operation \| Cost \|
	\|:---\|:---\|
	\| Graph search, supplemental data \| $0.25 \|
	\| Deep dive research (fast) \| $2.50 \|
	\| Deep dive research (comprehensive) \| $7.50 \|

	### Integration Protocols
	\| Protocol \| Endpoint \|
	\|:---\|:---\|
	\| REST API \| `https://api.fodda.ai` \|
	\| MCP Server \| `https://mcp.fodda.ai/mcp` \|
	\| A2A Agent Card \| `https://www.fodda.ai/.well-known/agent-card.json` \|
	\| Technical Manifest \| `https://www.fodda.ai/llms.txt` \|
	\| Full Manifest \| `https://www.fodda.ai/llms-full.txt` \|
	\| API Documentation \| `https://www.fodda.ai/api` \|
	\| Agent Integration Guide \| `https://www.fodda.ai/agents` \|

	## Use Cases

	- RAG grounding — Query Fodda during retrieval to ground LLM responses in verified trend data with evidence chains
	- Fine-tuning — Use trend + evidence structures as instruction-tuning data for domain-expert models
	- Agent tooling — Connect via MCP or A2A for autonomous research agents
	- Competitive intelligence — Cross-graph brand analysis across 100+ knowledge graphs
	- Market context — Combine trend signals with real-time economic, demographic, and demand data

	## License & Attribution

	This sample dataset is released under CC-BY-NC-4.0. Full API access is commercially licensed.

	When citing Fodda data, use: `Source: Fodda (fodda.ai) — powered by PSFK editorial intelligence`

	## Contact

	hello@fodda.ai · [fodda.ai](https://www.fodda.ai) · [psfk.com](https://www.psfk.com)