LIVE DATA PROCESSING

Processing High-Dimensional Market Physics for Retail Investors.

AnomalyEngine tracks multi-digit variables across microeconomic indicators, structural corporate disclosures, and global macroeconomic data streams to isolate market anomalies.

THE PROBLEM SPACE

What you're fighting without us

Individual investors in India manage ₹28 lakh crore in equity portfolios. Yet the tools available to them were designed for the era of physical trading floors — not for a world where institutions run 40,000 data points per second before 9:15 AM.

5–10

Metrics in standard screeners

P/E, EPS, RSI, MACD. The same 8 numbers your neighbour is also looking at.

0.3s

Institutional reaction time

Algos process RBI policy PDF in under a second. You read it in tomorrow's paper.

₹72L Cr

FII capital vs retail

Foreign institutions move markets before retail traders even open their terminals.

83%

Options traders lose money

SEBI data. Not because they lack courage — because they lack structured data.

₹25L

Bloomberg terminal cost per year

A Bloomberg terminal costs ₹25 lakh/year. Nobody told you about the free tier. Because there wasn't one.

1 tip

Average research depth in groups

"Bhai iska chart achha lag raha hai." That's the full thesis in most groups.

HOW WE POSITION

Them vs AnomalyEngine

STANDARD SCREENERS

✕5–10 generic metrics

✕No macro correlation

✕No historical cycle context

✕No structural disclosure parsing

✕Opinion-based signals

✕Delayed data feeds

VS

ANOMALYENGINE

✓Multi-hundred variable processing

✓Global macro-micro correlation

✓Historical cycle pattern matching

✓Automated filing & disclosure analysis

✓Zero opinion — pure computation

✓Real-time data stream processing

$

AE

HOW IT WORKS — SIMPLE VERSION

4 steps

From raw public data to structured anomaly signals — without opinions, without bias, without someone trying to sell you something.

01 · INGEST

All public data enters the engine simultaneously

BSE/NSE filings, RBI bulletins, SEBI disclosures, quarterly results, corporate announcements, global macro indices, commodity prices, currency pairs, FII/DII flows. All feeds normalized into a unified structured format — no manual curation, no editorial filter. If it's public data, we process it.

02 · CORRELATE

Variables cross-referenced against historical cycles

The engine maps current variable states against decades of market cycles — 2008 financial stress, 2013 taper tantrum, 2020 pandemic data, 2022 rate shock. When current readings resemble prior anomalous periods, the pattern is flagged — not interpreted, just mapped.

03 · ISOLATE

Statistical anomalies separated from market noise

Not every unusual data point is meaningful. The engine filters standard deviation outliers against multi-variable baselines. An earnings surprise means nothing without the context of sector-wide margin compression, FII positioning, and macro headwinds happening simultaneously.

04 · DELIVER

Structured data output, zero opinions

You receive structured, verifiable data outputs. Not a buy/sell call. Not a "multibagger pick." A mathematical verification layer — so when you make a decision, you know what the data says across 100+ variables, not just what one analyst or one Telegram admin says.

FREQUENTLY ASKED

Questions individual investors ask

Is this for beginners or experienced investors?+

Both. If you are new, the engine shows you what data actually drives markets versus what YouTube channels say drives markets. If you are experienced, it gives you a systematic way to verify your existing thesis using a broader data set than you currently have access to.

Will it tell me which stocks to buy?+

No. We build data verification engines — not investment advisors. The output tells you what the data shows. The decision remains entirely yours. This is intentional: our purpose is to make your research objective, not to replace it.

How is this different from Tickertape or Screener.in?+

Those tools show company-level fundamentals — mostly standard financial ratios from balance sheets. AnomalyEngine cross-correlates those same fundamentals against macro indicators, sector cycles, FII positioning, global events, and historical stress patterns simultaneously. The difference is dimension count, not data type.

Do I need to understand quant finance to use this?+

No. The engine handles the multi-variable computation. What you need is the ability to read structured data objectively and apply it to your own strategy. We make complex data readable — not magic, not hidden signals. Just a larger, cleaner view of what's already publicly available.

Is this SEBI compliant?+

Yes. We are an analytics and data processing platform — not an investment adviser. We do not give directional calls, manage portfolios, or charge for trading tips. We build computation infrastructure. SEBI registration applies to advisers; we are a software engine that processes publicly available data.

What if I already use a paid research service?+

AnomalyEngine is a verification layer, not a replacement for research. Use it to objectively check whether the data supports the thesis you are being sold. If the macro, micro, and filing signals align with the recommendation — great. If they don't, you now know before you invest.

DATA ENGINE · SPECIFICATION

What the engine actually processes

Every variable below is sourced from public filings, government releases, and exchange feeds. No proprietary data, no black box. You can verify every input independently.

148+VARIABLES TRACKED

4DATA CATEGORIES

30yrHISTORICAL DEPTH

Δ0OPINIONS ADDED

MACROECONOMIC

MICROECONOMIC

CORPORATE FILINGS

TECHNICAL FLOWS

RBI Repo Rate EBITDA Margin FII Net Position Working Capital Cycle CPI Inflation YoY Promoter Pledging % Put-Call Ratio Current Account Deficit Inventory Turnover Annual Report Disclosures USD/INR Volatility Delivery Volume % Receivables Days Related Party Transactions Brent Crude $/bbl India VIX Level Debt/Equity Trend Auditor Change Flags US Fed Funds Rate DII Contra Flow Cash Conversion Cycle CAPEX vs Depreciation Yield Curve Shape Options OI Skew Gross Margin Compression Management Guidance Deltas Global PMI Composite Sector Rotation Signal Revenue Concentration Risk SEBI Filing Anomalies China Trade Data Breadth Thrust Indicator

DATA SOURCES · VERIFIED

SOURCE	TYPE	FREQUENCY	STATUS
BSE / NSE Filings	Corporate disclosures	Intraday	LIVE
RBI Data Warehouse	Monetary & macro	Daily / Monthly	LIVE
SEBI Public Disclosures	Regulatory filings	Real-time	LIVE
MoSPI Economic Data	Microeconomic indices	Monthly	LIVE
NSDL / CDSL Flow Data	FII/DII positions	Daily EOD	LIVE
World Bank / IMF	Global macro	Monthly	LIVE
Fed Reserve H.4.1 / FRED	US monetary data	Weekly	LIVE

AU · 995

Why we use only public data

Gold is valuable because it is verifiable — weight, purity, and price are independently auditable. We apply the same standard to data. Every variable in our engine can be traced back to an official government or exchange source. You will never see a signal you cannot verify yourself. We are a computation layer on top of public truth — not a proprietary black box.

SECTION · FOUNDERS

Behind the Engine

Two builders — one obsessed with systems architecture, one with quantitative data models. Both convinced that retail investors deserve better infrastructure.

NP

Nishant Parwani

CO-FOUNDER · STRATEGIST & BUSINESS LEAD

Drives the strategic and financial direction of AnomalyEngine. Focused on market positioning, investor relations, and translating complex quantitative research into a product framework that serves retail participants. Bridges the gap between financial domain knowledge and what the engine needs to solve.

DJ

Dayaan Jain

CO-FOUNDER · TECH LEAD & ENGINE ARCHITECT

Leads all technical development — building the data ingestion pipelines, processing infrastructure, and anomaly detection algorithms that power the engine. Responsible for architecture decisions, system performance, and turning quantitative research requirements into functional, scalable software.

CAREERS · OPEN POSITIONS

Join the Build

We're expanding

We are expanding our engineering and analytical capabilities. If you are passionate about building heavy data processing infrastructure, optimizing distributed databases, or refining financial econometric models, we want to hear from you.

We do not care about your college. We care about what you have built, what data you have processed, and how you think about systems under load. Send us proof of work.

DISTRIBUTED SYSTEMS ECONOMETRICS DATABASE OPTIMIZATION QUANT RESEARCH DATA PIPELINES FINANCIAL MODELLING STATISTICAL ANALYSIS PYTHON / RUST / C++ KAFKA / FLINK TIMESERIES DBs

contact@nishantparwani.com ATTACH PORTFOLIO OR GITHUB