We collect the market data.
You run your strategy.

Altys Labs is an AI-assisted, human-governed equity research platform for Indian investment teams. Bring together filings, concalls, guidance, financial and alternative data, strategy testing, scorecards and monitoring while people retain the assumptions, exceptions and capital-allocation decisions.

For India's PMS firms, AIFs, family offices, and MFDs.

Request access Start a pilot
Company Board Reports Strategy Builder Research Grid Backtester Alerting
Financial AI reliability

AI that shows its work.

Financial numbers are calculated from company filings, not generated by a language model. Material claims carry citations. Core research outputs can be exported to Excel or Excel-ready CSV so your team can inspect the inputs and reproduce the work.

Calculated, not generated
Code calculates ratios, factors, growth and strategy scores from identified financial inputs.
Cited at the claim
Material research statements carry the evidence needed to inspect and verify them.
No evidence, no answer
Unsupported research answers fail closed as error or unavailable instead of guessing.
Point-in-time, not hindsight
Historical research uses only the information that was available by the date.
Export the audit trail
Do not trust the black box. Open the workbook.

Strategy screens and scorecards compile to formula-native Excel with the inputs, eligible universe, weights, calculations and provenance intact. GenGrid and analytical tables export as Excel-ready CSV. Alerts preserve their rule version, fired-by context and historical replay.

See the reliability architecture
Explore Altys before a pilot
Public Indian-market research. Professional research system.

Anyone can open our company research, market trackers, mutual-fund pages and educational analysis without an Altys platform login. The complete strategy, research, modelling and monitoring system is evaluated through a guided professional pilot.

You run the analysis. We prep the data, tools, and AI underneath.

Above the surface is your work: the strategy, the screen, the call, the report on the table. Below it is everything we collect and build so you can trust them.

Sources · point-in-time
Filings & XBRL
Concalls & Guidance
Shareholding
Macros & FII/DII
Funds & Factors
Broker Research
altys.ai
One sealed
point-in-time ledger
StrategyV10
Quality Compounders
NSE 500QC score48 names
ForensicsFLAG
92▲ from 61
Receivable days · +51% YoY
ReportsEXPORTED
IC Memo12 pages
AR26 · p.42Q3 · 14:20
Alerting5 RULES LIVE
WATCHthe thesis
FIREDvaluation above history
01Altys Company Board

One board per company. It learns how you read.

Price and events, financials, valuation history, cash quality, ownership, factors and the street's view, laid out as panels on a single canvas instead of buried in tabs. Ask the company a question and the answer comes out of its own filings and calls, cited. Model the scenario in Python right next to it.

No tabs. One canvas.

Every panel side by side, so the price move, the margin bridge and the cash quality are one glance apart.

It reorders itself

The panels you open first move to the top. The board arranges itself around how you actually read a company.

Ask the company

Answers are read out of its filings, transcripts and disclosures, with each claim traced to the document behind it.

Model it live

An attached notebook runs Python on the same point-in-time data: scenarios, exhibits, and a working model you can export.

02Institutional Reports

Analyst-grade reports, on demand.

Full research reports: financials, segment analysis, peer comparisons, and the thesis, built on the numbers as they stood on any date. Every figure links to the exact filing, line, and date it came from.

Not a chatbot summary. A report you'd put in front of your committee.

altys.ai Coverage · KEI Industries
Investment Committee Memo

KEI Industries | Evidence review

Revenue TTM
₹8,420 Cr
FCF conversion
0.88
Quality
92

Revenue grew 24% YoY to ₹8,420 Cr1 with FCF conversion holding at 0.882. Management guided FY27 capex near ₹1,200 Cr with ~200 bps margin expansion.3

[1]AR26 · p.42 [2]Cash flow · FY24 [3]Q3 call · 14:20
Strategy · EquityQuality Compounders V10 + 2 EDITS
01 · UniverseNSE 500 · Active companies
02 · EligibilityMarket cap > ₹5,000 Cr · ROCE > 14%
03 · Rank and classifyQC 8-Factor Scorecard · Top 10%
Screen today48 names→
03Altys Strategy Builder

Turn your investment process into a strategy you can run.

Build the strategy as a connected workflow: choose the universe, set eligibility, rank with your scorecards, classify the result, screen today, and test it through time.

Every edit recomputes the preview. Every saved version keeps the rules and data lineage intact.

04Altys Research Grid

One research question. Every shortlisted company.

Bring the shortlist

Open the companies that survived your strategy screen as a working grid. Add financial fields, scorecards, or any research question as a column.

Quality Compounders48 SCREENED NAMES
Fit Quality Value + add research column
48rows readyfrom sealed v10
Research across every row

Ask one question across the shortlist, like “Is pricing power improving after the capex cycle?” Altys reads each company's filings, concalls, and disclosures, then fills the grid with cited answers.

Is pricing power improving after the capex cycle?
48 rows · reading company sources · cited answers
Astral LtdAR26 · MD&A
“…pricing power restored as the capex cycle normalizes and utilization improves…”
Supreme IndsQ3 call · 22:10
“…asset turns rising, incremental capex now minimal against the base…”
05Altys Backtester

Test your strategy on the past.

Run any strategy against history using only what was known at the time, not numbers that were restated later. Every run is sealed: the universe, the rules, the rebalance dates and the data vintage are frozen together, so the result is reproducible instead of merely repeatable.

Quality compounders · quarterly rebalance Sealed run · NSE 500 · FY19 → FY26
SEALED 29 rebalances
Verdict
★★★★★
7.2y of evidence
CAGR · as known
19.3%
27.1% if restated
Alpha vs NSE 500
+4.8%
rolling 3y, 71% of windows
Max drawdown
−28.4%
Mar 2020 · 11m recovery
Equity curve
As it was known then · 19.3% CAGR Restated later · 27.1% (overstated)
What drove it · top contributors
Persistent Sys+3.9%
Astral Ltd+3.0%
KEI Industries+2.4%
Deepak Nitrite−1.1%
The honesty pane
Delisted and merged names stay in the universe — no survivorship lift.
Rules see a filing only after its actual publication date.
Prices adjusted for splits, bonuses and demergers, dividends included.
Pre-2020 windows carry thinner fundamental history — the run says so.
The gap between the two curves is survivorship and restatement leakage. Altys backtests only on figures as they were first reported — no look-ahead — and keeps the run going forward as a live forward test, so you can watch the strategy earn its stars.
06Altys Alerting

Alerts that watch the thesis.

Build rules on price, valuation, financial metrics, factor scores, or movement since the company entered your pipeline. Replay each rule against the last 12 months before you arm it.

When a rule fires, you see exactly why. No unexplained notification and no noisy feed.

Alert rule5 RULES LIVE
WHEN
P/Erises above90th percentile of history
WATCH
Pipeline · Deep ResearchReady to InvestInvested
PIDILITIND · P/E at 91st percentilenow
Fired by valuation history · rule v312-mo replay
07How It's Built

Built like market infrastructure, not a wrapper.

If this seems obviously correct to you, you're who we built it for.

Everything is point-in-time. We keep the data as it stood on every date, so you can ask what was known at any moment, not just what got restated later.

The math is calculated, not generated. Ratios, growth, factors, and strategy scores run as code over identified inputs, with a full trail.

AI stays in its lane. It retrieves, compares, summarizes, and cites. If evidence is missing, the answer fails closed instead of filling the gap with plausible prose.

Who it's for

PMS firms

Research and monitoring leverage for lean investment teams running concentrated books.

AIFs

Repeatable, auditable research process across a wider universe than your headcount covers.

Family offices

Institutional discipline on direct equity and MF allocations, without building a desk.

MFDs

Fund analysis, comparisons, and portfolio reviews on the full fund universe, so every client conversation is sharper.

One-month pilot

Turn your research process into
a continuous loop.

Over one month, we integrate or improve your scorecards, screeners, and continuous watchlist monitoring, then run them together on your real investment universe. Altys keeps the process moving from idea discovery to useful alerts, even when your team is offline.

The Altys DELTA Research LoopDiscover · Evaluate · Look deeper · Track · Alert
What we improveBuilt around your process
Scorecards aligned with your investment process
Screeners built around your mandate and research questions
Packaged quantitative models adapted to your mandate
Continuous Radar monitoring across portfolios and watchlists
Useful alerts configured around what matters to your team
Hands-on technical support from your personal AI team
Request access
What it changesFor investment teams
Save analyst hoursAutomate repetitive data collection, checking, scoring, and monitoring so analysts can spend more time on judgment.
Reduce human errorApply the same rules and evidence checks every time, with fewer missed updates and manual breaks.
Deploy quant models fasterUse packaged quantitative models and Radar's real-time updates instead of building every model and data pipeline from scratch.
Stay updated when the team is offlineRadar watches continuously and alerts your team only when something useful or material changes.

For PMS firms, AIFs, family offices, MFDs, and investment research teams.

One-month pilot

What should we integrate
or improve first?

Tell us about the scorecard, screener, quantitative model, or monitoring process you want to improve before choosing a meeting time.

You are *
What would you like to improve? optional

Your request is in.

Choose a time with Shlok to scope the work and define what success looks like for the one-month pilot.

Choose a time with Shlok
One real workflowYour research universeOne month

Talk to the founder.

Pilot scoping with Shlok · 30 min · Google Meet · one-on-one
Weekdays, 11 am – 8 pm IST

Complete the access brief above first. The calendar appears once we know what you want to integrate or improve.

FAQ

Questions, answered.

What is Altys Labs?+
Altys Labs, also known as Altys or Altys AI, is an AI-assisted, human-governed equity research and investment governance platform for Indian investment teams. It connects source-linked data, strategy testing, scorecards, parallel company research, models, Excel verification, portfolio monitoring and alerts. People retain assumptions, exceptions and capital-allocation decisions.
What is the Altys Company Board?+
The Company Board is one screen per company: price and events, financials, valuation history, cash quality, ownership, factor scores and broker consensus, laid out as panels on a single canvas instead of tabs. The board reorders itself around the panels you actually open, you can ask questions of the company's own filings and calls and get cited answers, and you can model scenarios in Python in an attached notebook.
Who is Altys for?+
Altys is built for institutional investors in India: PMS firms, AIFs, family offices, MFDs, and investment research teams.
Is Altys publicly accessible?+
Altys publishes public Indian company research, market trackers, mutual-fund pages, and educational analysis that anyone can open without an Altys platform login. The complete research operating system is currently available to professional investment teams through a guided one-month pilot.
What data does Altys cover?+
Indian listed equities and mutual funds: filings and XBRL, concall transcripts, management guidance, shareholding, 80+ global and domestic macro series, FII/DII flows, and factor scores. Every series is kept point-in-time, stored as it stood on each date, so screens and backtests reflect what you would actually have known.
Does Altys hallucinate financial numbers?+
Altys is built to prevent hallucinated financial numbers. Figures come from sourced financial data and deterministic calculations, material claims carry citations, and unsupported answers fail closed as error or unavailable. No responsible system should replace analyst verification or claim that every possible error disappears.
Are Altys financial ratios and strategy scores generated by AI?+
No. Ratios, growth, factors, and strategy scores run through explicit code-owned methods using identified inputs. AI can retrieve, compare, and explain the result, but it is not the calculation engine that originates the number.
How does Altys verify an AI-generated research answer?+
For material research answers, Altys retrieves from structured data and company documents, requires supporting citations, and checks that the answer has valid evidence before it can resolve as complete. The analyst can open the source and verify the company, period, basis, and claim.
What happens when Altys cannot find supporting evidence?+
The answer resolves to error or unavailable. Altys does not let an unsupported material claim pass as a completed research answer simply because a language model can write plausible prose.
How is Altys different from ChatGPT, Claude or Gemini for stock research?+
General assistants are broad language tools. Altys supplies an India-first financial data layer, deterministic calculations, point-in-time context, research workflows, backtesting, and continuous company monitoring. General models can still help with drafting, but Altys provides the evidence system underneath.
Can every Altys number be traced to its source?+
Each surfaced financial figure is designed to preserve lineage to its source or calculation inputs. Material textual claims carry citations so the user can inspect the supporting evidence instead of trusting the model's memory.
Can Altys calculations be exported and checked in Excel?+
Yes. Strategy screens and scorecards can be downloaded as formula-native Excel workbooks with inputs, eligibility, weights, calculations and provenance. GenGrid and analytical tables export as Excel-ready CSV. Alert rules remain inspectable through versioned definitions, fired-by context and historical replay.
How does point-in-time data prevent misleading historical analysis?+
Point-in-time data stores both the period a value describes and the date it became knowable. Historical screens and backtests therefore use only information available by the decision date, not later restatements or corrections.
How is Altys different from a stock screener?+
A screener shows you today's numbers. Altys keeps every number point-in-time and connects screening to a strategy builder, reproducible backtesting, cited research grids, analyst-grade reports, and continuous alerts. Every figure is sourced back to the document it came from.
How does the one-month pilot start?+
Tell us which scorecard, screener, quantitative model, or monitoring process you want to integrate or improve, then choose a time with Shlok. The first conversation defines the scope and success criteria for the pilot.