Themes

Gildea classifies every signal into a two-axis theme system. Signals can have multiple themes per axis.

Value chain (`value_chain`)

Where in the AI value chain does this signal sit?

Theme	Description
Infrastructure	The compute layer: GPUs, TPUs, custom chips, and cloud infrastructure that make large-scale model training and inference possible.
Foundation Models	The core models that define capability: trained systems like GPT, Claude, Gemini, and Llama that serve as the base for downstream products.
Orchestration	The software layer that makes models usable: frameworks, agents, vector stores, and developer tools for building and managing model-powered systems.
Data & Labeling	The data layer: how models are trained, evaluated, and refined, from raw datasets to synthetic data and human feedback loops.
Applications	The product layer: AI features and experiences built for real users, from enterprise copilots to consumer agents.
Distribution	The delivery layer: how AI capabilities reach users, through APIs, platforms, partnerships, and ecosystems.

Market force (`market_force`)

What external pressure or catalyst is shaping the value chain?

Theme	Description
Capital & Investment	Tracks the allocation of financial resources: who’s funding whom, how capital moves across stages, and how valuations shape incentives.
Regulatory & Legal	Tracks how rules, policies, and court decisions set the boundaries for innovation and competition.
Competitive Dynamics	Examines how firms position themselves (via product strategy, data moats, or market timing) to gain or defend share.
Talent & Labor	Follows the human factor: hiring trends, executive shifts, skill shortages, and how automation reshapes work.
Geopolitical Strategy	Analyzes the interplay between national interests, technology policy, and access to compute and talent.
Trust & Societal Impact	Captures public sentiment, safety debates, and the ethics shaping adoption and regulation.

Interpretation fields

Each theme includes interpretation fields derived from the raw trend stats. These are discrete labels that agents can act on without statistical expertise.

Field	Values	What it tells you
`direction`	`Rising`, `Stable`, `Declining`	Which way is this theme trending
`confidence`	`Significant`, `Insignificant`	Is the trend statistically reliable
`stability`	`Volatile`, `Steady`	How consistent is coverage week to week
`notability`	`High`, `Medium`, `Low`, `Negligible`	How much this theme warrants attention right now: foreground vs. background
`notability_reasoning`	Free text	Human-readable explanation of the notability assignment

Themes do not have a scale field; all 12 themes are always active. The interpretation labels are computed over a rolling 12-week window: the current week plus 11 prior weeks.

{
  "axis": "value_chain",
  "label": "Foundation Models",
  "direction": "Rising",
  "confidence": "Significant",
  "stability": "Steady",
  "notability": "High",
  "notability_reasoning": "Theme with confirmed upward trend and consistent coverage; notable upward shift reliably gaining traction.",
  "trend": { "..." : "..." }
}

Theme intelligence

Each theme has a rich profile including:

Signal count: total signals tagged with this theme
Trend stats: analytics across four dimensions (see below)
Related themes: themes that frequently co-occur across both axes

Trend analytics

Every theme includes a trend object:

Field	Description
`share_of_voice`	Theme’s share of total corpus over the trailing 4 weeks
`streak`	Consecutive weeks of growth
`current_week`	Signal count this week
`prior_week`	Signal count last week

The discrete interpretation labels above (direction, confidence, stability, notability) are derived from the underlying statistics so you can act on them without doing the statistics yourself.

Using themes as filters

Themes work as filters across the API. Use the exact theme labels above:

# Signals about Infrastructure
curl -H "X-API-Key: gld_your_key" \
  "https://api.gildea.ai/v1/signals?theme=Infrastructure"

# Entities in the Foundation Models space
curl -H "X-API-Key: gld_your_key" \
  "https://api.gildea.ai/v1/entities?theme=Foundation%20Models"

# Search within a theme
curl -H "X-API-Key: gld_your_key" \
  "https://api.gildea.ai/v1/search?q=chip+shortage&theme=Competitive%20Dynamics"

Theme detail

The theme detail endpoint returns co-occurring themes from both axes:

{
  "axis": "value_chain",
  "label": "Foundation Models",
  "signal_count": 45,
  "trend": { "share_of_voice": 0.22, "streak": 3, "current_week": 28, "prior_week": 24 },
  "related_themes": [
    {
      "axis": "market_force",
      "label": "Capital & Investment",
      "co_occurrence_count": 32
    }
  ]
}

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Integrations

API

Recipes

Changelog

Value chain (`value_chain`)

Market force (`market_force`)

Interpretation fields

Theme intelligence

Trend analytics

Using themes as filters

Theme detail

​Value chain (value_chain)

​Market force (market_force)

​Interpretation fields

​Theme intelligence

​Trend analytics

​Using themes as filters

​Theme detail

Value chain (`value_chain`)

Market force (`market_force`)

Interpretation fields

Theme intelligence

Trend analytics

Using themes as filters

Theme detail