AIT Stock Trigger Intelligence methodology

1. Sources and update cycle

Recent official corporate announcements are requested during the scheduled market-data workflow. Upcoming corporate actions are merged from the existing local corporate-action dataset. Current price, volume, strength and momentum context is read from the website’s existing daily scanners.

Latest packaged status: NSE Corporate Announcements API · 11-Aug-2026 16:55 IST

2. Classification

Deterministic rules separate business events from low-information updates. Investor meetings and recording links are classified separately so they are not mistaken for institutional accumulation.

• Large Order / ContractORDER_WIN
• Quarterly / Financial ResultsRESULTS
• Guidance / Business OutlookGUIDANCE
• Capacity Expansion / New FacilityEXPANSION
• Acquisition / PartnershipACQUISITION_PARTNERSHIP
• Promoter / Insider ActivityPROMOTER_ACTIVITY
• Investor Meeting / Conference CallINVESTOR_MEETING
• Institutional / Fund ActivityINSTITUTIONAL_ACTIVITY
• Credit Rating ChangeCREDIT_RATING
• Fund Raise / DilutionFUND_RAISE
• Management / Auditor ChangeMANAGEMENT_CHANGE
• Regulatory / Legal DevelopmentREGULATORY_LEGAL
• Corporate ActionCORPORATE_ACTION
• Other Material UpdateOTHER_MATERIAL

3. Five-factor materiality score

The 0-100 score is the visible sum of business materiality (35), evidence specificity (20), financial magnitude (20), market confirmation (15), and recency or urgency (10). Every event page shows the points and reason for each factor.

4. Data confidence

A separate confidence score reflects filing detail, extracted facts and source availability. Low-confidence records can remain visible for monitoring, but the page clearly states what could not be verified.

5. Fallback protection

If the fresh request fails, recent previously generated records are preserved and corporate actions are rebuilt. Retained records are re-scored with the newest model so old static scores do not remain in the feed.

6. AI and corrections

AI may improve wording but cannot invent amounts or override the transparent scoring formula. Users should verify the original filing because automated extraction can misread units, dates or context.

7. Score boundary

The materiality score measures the importance and evidence quality of a disclosure. It does not forecast return, target price, probability of a rise or suitability for any investor.

8. Data-use boundary

Automation In Trade should review exchange data-sharing and commercial redistribution requirements before scaling paid redistribution, API access or bulk export.