DEV Community

Aion Analytics (India) profile image AION ANALYTICS
AION ANALYTICS for Aion Analytics (India)

Posted on

aion-indian-market-intelligence: The India Contextual Intelligence Layer for Your LLMs and SaaS Products

This is not another Indian market model.

It is the missing regional causal intelligence layer you plug into your existing LLM, agent, or SaaS product.

You bring the headlines (from any sources or circulars you already use).

It returns structured, time-lagged, signed sector impact + stakeholder context specifically calibrated for Indian markets.

Important Disclaimer

This service provides structured market-interpretation infrastructure for informational purposes.

It is not investment advice, not a trading signal, and not a recommendation. All decisions and regulatory compliance (including SEBI) remain with you.

Core Value Proposition

  • Signed sector_vector (positive/negative exposure per sector)
  • Time-lagged effects (e.g. Construction negative at lag 0, positive at lag 90 after a cyclone)
  • Stakeholder views (banks, borrowers, government, exporters, etc.)
  • VIX regime context
  • High-confidence event typing

This is exactly the kind of structured, India-specific context that generic LLMs are weakest at providing.

How to Use It (for Developers & Vibe Coders)

1. Basic (your source → structured India context) 

from aion_indian_market_intelligence import analyze

intel = analyze("RBI raises repo rate by 25 bps")
print(intel["sector_vector"])
Enter fullscreen mode Exit fullscreen mode

2. LLM / RAG Augmentation

Store the structured output next to your headlines in your vector store. When the LLM retrieves a document, also retrieve the sector impact data.

enriched = f"Headline: {headline}
Sector impact: {intel['sector_vector']}
Stakeholders: {intel.get('stakeholder_views')}"
# embed or store as metadata
Enter fullscreen mode Exit fullscreen mode

3. SaaS / Sales & Lead Intelligence (high-leverage pattern) 

flowchart TD
    Event[Macro / micro event] --> IMI[analyze → sector impact + severity]
    IMI --> YourCRM[Your customer / prospect list]
    YourCRM --> LLM[LLM gets real Indian regional causal context]
    LLM --> Action[Prioritized leads / risk flags / personalized messaging]
Enter fullscreen mode Exit fullscreen mode

Real example: A policy change or weather event lands. Instead of generic “this is negative”, your system knows:

  • Which specific sectors are affected
  • The severity and direction
  • The time-lagged second-order effects
  • How this maps to your actual customers in those sectors

This is extremely powerful for sales intelligence, account-based marketing, and risk products focused on India.

4. Batch from Your Existing Crawler 

from aion_indian_market_intelligence import analyze

for item in my_news_feed:
    intel = analyze(item["headline"])
    item["imi_sector_vector"] = intel["sector_vector"]
    item["imi_top_positive"] = intel["top_positive_sectors"]
    # store or act
Enter fullscreen mode Exit fullscreen mode

Mermaid Diagrams

Basic Integration

flowchart LR
    YourSources[Your news sources / circulars] --> Analyze[analyze()]
    Analyze --> AION[Hosted AION IMI]
    AION --> Structured[sector_vector + context]
    Structured --> YourLLM[Your LLM / Agent / Application]
Enter fullscreen mode Exit fullscreen mode

SaaS Sales / CRM Intelligence

flowchart TD
    ExternalEvent[Policy / Weather / Geopolitics / Commodity shock] 
        --> IMI[analyze → impact per sector]
    IMI --> YourData[Your CRM / lead list]
    YourData --> EnrichedLLM[LLM now understands India-specific impact on *your* accounts]
    EnrichedLLM --> Actionable[Prioritized actions]
Enter fullscreen mode Exit fullscreen mode

Sample Output (Realistic) 

{
  "headline": "Severe cyclone makes coastal landfall...",
  "event": "weather_disaster",
  "confidence": 0.84,
  "sector_vector": {
    "Construction": { "lag_0": -0.50, "lag_90": 0.55 },
    "Agriculture": { "lag_0": -0.65, "lag_90": -0.65 }
  },
  "stakeholder_views": { ... }
}
Enter fullscreen mode Exit fullscreen mode

Positioning for Different Users

  • Vibe coders / AI agents: Plug in via MCP (uvx aion-indian-market-intelligence-mcp) and give your agent real Indian market context.
  • SaaS builders: Add sector-impact awareness to any product that touches Indian companies or economy.
  • Internal tools: Enrich research, risk, or opportunity systems with calibrated causal vectors instead of raw sentiment.

Source: https://dashboard.aiondashboard.site/models/indian-market-intelligence

PyPI: pip install aion-indian-market-intelligence

MCP: uvx aion-indian-market-intelligence-mcp

This is infrastructure. You decide what to do with the intelligence.

Top comments (0)