Brand Intelligence

Cross-graph brand profiling and competitive footprint audits.

What it does

Audit a brand's footprint across expert knowledge graphs. Uncover real-time trend signals, competitor contexts, and category share-of-voice with verifiable evidence paths.

Orchestration pipeline

  1. Cross-graph vector search for brand mentions
  2. Contextual mapping of brand attributes to consumer behaviors
  3. Competitive positioning relative to category-defining trends
  4. Grounding of brand claims against historical case studies

Example

Query: "Nike"

Returns trend matches across knowledge graphs with relevance scores, contextual analysis, and source graph attribution. Example output includes trend matches like "Nervous-System Tech" (relevance 0.88, source: psfk-sports) and "Aspirational Humanity" (relevance 0.82, source: sic).

Integration

MCP Tool: brand_cross_graph()

REST Endpoint: POST /v1/copilot/search_insights

Add Fodda as an MCP server. Once configured, your AI model can dynamically trigger brand_cross_graph() whenever the context warrants.

Unauthenticated requests will trigger an MPP challenge (HTTP 402), allowing inline agent-wallet settlement.

Zero-Onboarding via MPP

Consuming agents do not require pre-provisioned keys. Endpoints challenge unauthenticated bots with HTTP 402, allowing automatic Stripe link settlement.