Filings, concalls, guidances, shareholding, 80+ global and domestic macros, FII/DII flows, and factor scores, all in one place. Then the tools to screen, model, forecast, and test your strategy on it. Every number is calculated, not guessed, and every figure links to the document it came from.
For India's PMS firms, AIFs, family offices, and MFDs.
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.
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.
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.
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.
Every panel side by side, so the price move, the margin bridge and the cash quality are one glance apart.
The panels you open first move to the top. The board arranges itself around how you actually read a company.
Answers are read out of its filings, transcripts and disclosures, with each claim traced to the document behind it.
An attached notebook runs Python on the same point-in-time data: scenarios, exhibits, and a working model you can export.
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.
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
Forecasts built from the company's own numbers with statistical models, not an AI guessing a growth rate. You see the assumptions, the confidence, and the baseline. When the model isn't sure, it tells you instead of guessing.
Set any rule on growth, quality, leverage, or valuation, and screen the whole market. It runs on the data as it stood then, so the results match what you'd actually have known.
Describe a thesis in plain English, like “asset-light businesses gaining pricing power after a capex cycle”, and Altys reads the filings, concalls, and disclosures to find the companies that fit, with the passage that proves each one.
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.
Set it up in plain English. WHEN something happens, a filing drops, a broker email lands, a macro print moves, a threshold breaks, THEN Altys acts: it drafts the note, updates the model, and alerts you.
Your monitoring runs 24/7. Your analysts do the thinking.
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 forecast outputs 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.
Research and monitoring leverage for lean investment teams running concentrated books.
Repeatable, auditable research process across a wider universe than your headcount covers.
Institutional discipline on direct equity and MF allocations, without building a desk.
Fund analysis, comparisons, and portfolio reviews on the full fund universe, so every client conversation is sharper.
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.
For PMS firms, AIFs, family offices, MFDs, and investment research teams.
Tell us about the scorecard, screener, quantitative model, or monitoring process you want to improve before choosing a meeting time.
Complete the access brief above first. The calendar appears once we know what you want to integrate or improve.