File size: 6,329 Bytes
13cff1e
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
---
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)