Insight, the Instant It Matters.
Real-time corporate & regulatory signals for Indian markets — distilled by AI into actionable intelligence.
What is Frism?
Frism tracks corporate filings, exchange announcements, and government policy updates that affect Indian companies and sectors. Powered by our AI engine, each update is analysed for asset-class impact, sector exposure, and causal drivers — turning raw filings into actionable intelligence within seconds.
Instant Delivery
Corporate announcements, regulatory filings, and government updates — delivered the moment they break, so you're never behind the market.
AI-Powered Analytics
Every article is enriched with Triple Lens Analysis — tracing cause, effect, and impact across asset classes, sectors, and geographies.
Indian Market Focus
Purpose-built for Indian equities and sectors. From SEBI circulars to RBI policy, we surface what moves your portfolio.
Verified & Ranked
Articles are verified for accuracy, ranked by market impact, and tagged with confidence scores — cutting noise so you act on signal.
The Problem We Solve
Staying ahead of Indian markets requires monitoring thousands of daily disclosures. Here's why that's broken today:
The Data Deluge
The Indian financial ecosystem generates thousands of exchange filings, regulatory circulars, and government updates every day. For the active investor, this creates a Bandwidth Gap — the volume of decision-critical text is scaling exponentially, while human cognitive capacity remains fixed.
The Analysis Gap
Traditional tools aggregate filings but do not analyze them. Humans cannot manually connect a new SEBI circular or an RBI policy update to its specific impact on a sector or stock fast enough to act.
Signal Decay
The window to act on information is shrinking. By the time you read, understand, and assess a 100-page annual report, the market has already moved. Manual correlation is no longer a competitive strategy.
How It Works: The 5-Minute Pipeline
From the moment an update is posted on an exchange, it takes us less than 5 minutes to deliver a verified, AI-analysed summary to your feed.
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Continuous Ingestion
Our systems monitor real-time feeds from stock exchanges, government portals, and trusted financial publishers. The moment a new document is published, our ingestion engine triggers immediately.
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High-Quality PDF Extraction
Financial disclosures often arrive as dense, complex PDFs loaded with tables and fine print. Frism instantly converts them into high-quality structured text, preserving the integrity of critical numbers and tables.
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Enterprise-Grade LLM Summarization
Extracted text is processed by our enterprise-grade Large Language Models, finely tuned to understand financial jargon and summarise the most important points — revenue growth, margin guidance, regulatory changes — with rigorous accuracy verification.
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Triple Lens Analysis
The summarised intelligence is passed to Frism's Analyzer engine, which identifies exact causal chains — linking each filing to specific asset classes, sectors, and geographies. You understand not just what happened, but why it matters and what it impacts.
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Instant Delivery
Verified, ranked intelligence is published instantly — complete with confidence scores and impact tags — all within an average of 5 minutes from the original publication on the exchange.
Who Are We?
Karthik
Principal Engineer & Founder
Software engineer with a passion for solving challenging problems. Working on transforming corporate filings and macroeconomic events into actionable intelligence for investors and analysts.
LinkedIn ProfileCurious to Know More?
Frism is a financial information and news discovery platform. We provide factual summaries and data correlations for educational and informational purposes only. Frism does not provide investment advice, buy/sell recommendations, or directional market outlooks. Users should consult a qualified financial advisor before making any investment decisions.
Frism Computing (OPC) Private Limited
#74, 15TH CROSS, JP Nagar III Phase, Bangalore South, Bangalore 560078, Karnataka