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Why It Matters

Thematic investing requires systematic identification of companies aligned with structural trends, but manually tracking exposure across thousands of documents is inefficient and inconsistent. As mega-trends like AI and decarbonization reshape markets, investors need scalable ways to quantify which companies are genuinely positioned to benefit.

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What It Does

The Thematic_Screener_CLI cookbook combines the Bigdata.com REST API, bigdata-smart-batching, and OpenAI to screen a CSV company universe against an investment theme. Designed for analysts, PMs, and strategists, it systematically connects companies to themes using unstructured data from news, earnings calls, and filings.
The legacy Thematic_Screener notebook used the removed bigdata-research-tools SDK and platform watchlists. Use Thematic_Screener_CLI for new work.

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How It Works

The CLI runs a four-stage pipeline:
  1. Generate labels — LLM builds a theme taxonomy (mindmap) from your main theme and optional focus
  2. Build search plans — one plan_search per sub-theme over your company universe
  3. Execute search — retrieve and deduplicate documents via bigdata-smart-batching
  4. Label sentences — classify relevance, summarize company exposure, export JSON/Excel/HTML
Each run is isolated under runs/<run_name>/.

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A Real-World Use Case

This workflow screens a company universe for Supply Chain Reshaping exposure — logistics automation, nearshoring, and supply-chain digitalization — and ranks companies by thematic score. Ready to get started? Let’s dive in!
Open in GitHub

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Prerequisites

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Setup

Load credentials from .env and define your universe as a CSV with RP_ENTITY_ID and COMPANY_NAME columns (see 40_companies.csv in Thematic_Screener_CLI or Thematic_Screener_CLI/40_companies.csv). Default LLM: gpt-5.6-luna (luna models omit temperature / top_p).

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Quick start

Use summarize-plans to preview chunk counts before retrieval, and bigdata-approx-cost to estimate cost presets.

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Notebook walkthrough

For a guided derivatives example (TSX Top 150, oil-price theme chain):
Notebook runs write to the same runs/ layout as the CLI.

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Example output

After labeling and scoring, the pipeline produces company- and industry-level exposure tables and interactive charts:
thematic exposure heatmap
thematic exposure score
top thematics
thematics scores
Industry-level thematic exposure heatmap

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Extract Key Insights

The visualizations reveal key insights about how companies are positioning themselves within the supply chain reshaping theme:

AI and Machine Learning Emerges as the Core Enabler

With the highest cumulative score across all companies, AI and Machine Learning is the most dominant theme, highlighting its foundational role in predictive analytics, automation, and optimization within modern supply chains.

Automation and Robotics Drive Operational Efficiency

Automation and Robotics rank highly, underscoring the push toward warehouse automation, autonomous logistics, and process optimization as companies seek to reduce costs and improve resilience.

IoT Enables Real-Time Supply Chain Visibility

IoT’s high ranking shows its critical role in connecting assets, enabling real-time visibility, and facilitating advanced automation, especially for manufacturers and hardware-driven firms.

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Industry Polarisation

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Sector Engagement

  • Semiconductors and Computer Services industries show the strongest average exposure, reflecting their integral role in enabling supply chain tech (e.g., sensors, connectivity, software).
  • Traditional Sectors like Diversified Industrials show broader but shallower engagement, suggesting they are still in earlier phases of thematic adoption.

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Strategic Focus

Concentration vs. Diversification in Exposure Most companies exhibit thematic concentration, focusing efforts on a few high-impact areas rather than spreading across all themes—likely reflecting strategic prioritization rather than lack of alignment.

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Conclusion

Thematic screening provides a powerful way to identify companies most aligned with or exposed to specific investment themes. By combining Bigdata.com REST search, smart-batching, and LLM-based classification, you can:
  1. Discover thematic leaders — Find companies with the strongest strategic alignment to emerging trends
  2. Compare across industries — Identify which sectors are most proactive in addressing thematic challenges and opportunities
  3. Identify investment opportunities — Spot companies that may be undervalued relative to their thematic positioning
  4. Monitor thematic evolution — Track how themes gain or lose prominence across your universe over time
Whether you’re building thematic portfolios, conducting sector research, or seeking alpha through theme-based strategies, the Thematic Screener CLI transforms unstructured data into structured, decision-ready intelligence.