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Detect
Market events enter the pipeline from supported exchanges, regulators, and financial news sources.
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How It Works
MarketRipple continuously processes market events, analyzes their potential impact, connects them across sectors and companies, and turns the resulting intelligence into searchable opportunities, risks, and market insights.
MarketRipple ingests market events and financial information from exchanges, regulators, and financial news. AI extracts the relevant entities and facts from each event, which is then classified and structured. Ripple relationships connect the event to affected sectors and companies, and historical context adds precedent where a genuinely similar past event exists. Opportunity Radar evaluates the resulting signals, and AI Search lets users explore the intelligence in natural language.
The Pipeline
Market events enter the pipeline from supported exchanges, regulators, and financial news sources.
AI extracts entities, facts, and potential market relevance from each event.
Each event becomes a queryable Market Event with type, sector, company, and impact metadata.
Ripple relationships connect the event to other companies, sectors, and market entities.
Potentially affected companies and sectors are identified, direct and indirect.
Similar historical events, where available, provide additional context.
Opportunity signals are evaluated using the Opportunity Radar's scoring engine.
Users receive structured, sourced intelligence through MarketRipple's products.
Trust
Market data and event information are used as real inputs — for company-impact analysis specifically, real per-company price-move data is fetched and fed into the same prompt, so the AI writes from an actual number rather than inventing a direction or magnitude.
Non-AI validators check every draft before publish for shared boilerplate reasons reused across companies, sentiment tags that contradict the real price move, and draft-vs-decided status mismatches.
Fact
What the source or data indicates — sources, historical outcomes, real price moves.
AI Interpretation
MarketRipple's model-generated analysis based on the available evidence, clearly labelled as such.
Every article on the AI Newsroom carries an Evidence section built on this exact split, alongside an AI Investment Verdict — an aggregate stance derived from real company and sector data, never a fabricated buy or sell rating.
Sources
Exchange filings provide company-level corporate disclosures — the ground-truth record of what a listed company has actually announced.
Regulatory releases provide policy and market-rule changes — the source of most market-wide, cross-sector events.
Financial news provides developing market narratives and context that regulatory filings alone don't carry.
Event Structure
Every event is structured with the same metadata: event type, sector exposure, company exposure, impact duration, geographic scope, and an impact/relevance score.
Explanatory example — not live data
Ripple Intelligence
MarketRipple traces cause-effect relationships from a market event across seven real relationship types — companies and sectors that may be affected, not always the obvious ones.
benefitshurtssuppliesdepends_oncompetes_withinfluencestriggered_byExample — illustrative, not a guaranteed chain
The Graph
Nodes
Companies, sectors, commodities, currencies, policy instruments.
Edges
Typed relationships between entities.
Confidence
How strongly the system supports a given relationship.
Explanatory diagram — not a live graph
EVENT — RBI rate change
↓ influences
BANKING
↓ affects
BANKS / NBFCs
↓ changes
FUNDING / MARGINS
Companies
Revenue, cost, or business exposure — the event affects this company's own operations or financials.
Sector or supply-chain spillover — the company isn't named in the event, but sits downstream or upstream of what is.
Longer-term structural implications — the event shifts a trend the company's business model depends on.
MarketRipple can combine these relationships with available market data and other signals to provide context around company exposure.
Browse companiesHistorical Context
MarketRipple can compare a current event with similar historical events where a genuinely similar precedent is available.
Historical patterns provide context, not a guarantee of future returns.
View historical patternsMarket Stories
One event isn't always enough to understand a developing market narrative. MarketRipple connects related events into a persistent, evolving Story.
Opportunity Radar
Opportunity Radar organizes potential opportunity signals by combining available event impact, corroborating events, and the breadth of companies and sectors involved in a developing situation.
An opportunity score is an intelligence signal, not a guaranteed return or investment recommendation.
Explore Opportunity RadarAI Search
Answers are grounded in MarketRipple's own event, company, and sector data — not every answer is guaranteed correct, and quality depends on how much real data exists on a topic.
Try AI SearchTechnology
Event analysis, entity extraction, and summarisation run on a multi-provider large language model fallback chain — the pipeline automatically moves to the next available provider rather than depending on a single vendor. Company-impact analysis is grounded in real per-company price-move data fed into the same prompt, not generated from headline text alone.
News and exchange sources are polled on a fixed schedule (every 15 minutes for NSE/BSE/RSS, hourly for RBI/SEBI/PIB), with deduplication and entity normalisation before an event is classified. AIPE's article-generation cycle then runs every 5 minutes over the newly classified backlog.
A market relationship graph spans 7 real dependency types — benefits, hurts, supplies, depends_on, competes_with, influences, triggered_by — connecting companies, sectors, and events. The graph grows as new events are processed and supports traversal for ripple analysis and exposure mapping.
Questions
MarketRipple polls exchange filings (NSE, BSE), regulatory and government sources (RBI, SEBI, PIB, Ministry of Finance), and financial news RSS feeds on a fixed schedule — every 15 minutes for exchange and news sources, hourly for regulatory sources. Each item is deduplicated and normalised before entering the analysis stage.
AI extracts entities (companies, sectors, commodities, currencies) from each event and assesses market relevance. For company-impact analysis specifically, real per-company price-move data is fetched and included in the same prompt, so the analysis is grounded in an actual number rather than inferred from headline text alone.
Events are matched to companies through the Ripple Engine's relationship graph — either directly named in the event, or connected through one of seven relationship types (supplies, depends_on, competes_with, and others) linking the event's sector or commodity to a company's real exposure.
Ripple Intelligence is MarketRipple's system for tracing how one market event may affect other companies and sectors beyond the obvious one, through 7 defined relationship types. It's presented as a relationship graph with a confidence indicator on each connection — not a guarantee that every traced effect will materialise.
Opportunity Radar scores potential opportunities using a transparent formula based on real signal density: how many corroborating events, companies, and sectors are involved in a developing situation. It's an intelligence signal for further research, not a guaranteed return or a recommendation to buy or sell.
Yes — MarketRipple compares current events against a set of verified historical market events (spanning 2008–2024) where a genuinely similar precedent exists. This adds context about how markets reacted to similar situations before. Historical patterns provide context, not a guarantee of future returns.
Company-impact analysis is grounded in real fetched price data before generation, and deterministic (non-AI) validators check every draft afterward for shared boilerplate reasons reused across companies, sentiment tags that contradict the real price move, and status mismatches — before anything publishes.
No. MarketRipple is a market research and intelligence tool. It does not replace the personalised advice of a SEBI-registered investment advisor, and all investment decisions remain the responsibility of the user. See the Legal page for the full disclaimer.
A natural-language question is matched against MarketRipple's own event, company, and sector data, and an AI model synthesises a sourced answer from what's retrieved — for example, 'Which sectors could benefit from rupee depreciation?' Answers cite the underlying events, and quality can vary with how much real data exists on a topic.
Every AI Newsroom article carries an Evidence section split into Fact — what happened, sources, historical outcomes — and AI Interpretation — the model's own read, clearly labelled as such. The two are never blended into one undifferentiated claim.
Go Deeper
Explore the AI reasoning, evidence standards, and confidence calibration that power every output on MarketRipple.