Bull Run vs Multibagg vs Altys: Which Indian AI Research Tool Fits You?

Bull Run, Multibagg AI and Altys solve three different versions of the Indian stock-research problem. Bull Run is a public, guided stock screener and research platform for self-directed investors. Multibagg makes AI-assisted company, document and portfolio research accessible. Altys connects research with point-in-time data, strategies, scorecards, models, portfolio governance and monitoring for professional investment teams.

The right choice is therefore not the product with the longest feature list. It is the one designed to finish the job you actually have.

This comparison was checked against the providers’ public websites on 13 September 2026. Product access and features can change. Altys Labs publishes this article and is one of the products discussed, so the comparison deliberately separates observed public claims from evaluation questions.

The short answer

Product	Best starting use	Primary audience	Centre of gravity
Bull Run	Find, screen and compare Indian stocks in a guided interface	Self-directed retail investors	Accessible fundamentals, screens, comparisons, sector context, IPO research and AI explanations
Multibagg AI	Ask company questions, inspect documents and follow market or portfolio developments	Individual investors and research users	AI-assisted company research, documents, themes, market intelligence and portfolio features
Altys	Govern an investment process from rules and evidence to portfolio monitoring	PMS, AIF, family-office, adviser and equity-research teams	Point-in-time data, deterministic strategies and scorecards, cited research, models, Excel verification and alerts

This is not a universal ranking. Bull Run and Multibagg are easier public starting points for an individual investor. The full Altys platform is a guided professional pilot, although Altys also publishes company pages, market trackers, mutual-fund research and educational analysis that anyone can open.

Bull Run: guided screening and readable research

Bull Run describes itself as an independent research and data platform for self-directed Indian investors. Its public positioning combines a stock screener with company fundamentals, stock comparisons, sector and index views, IPO context, educational material and AI-assisted explanations.

The product starts from a familiar retail-investor question:

I have a stock or an idea. How do I narrow the universe and understand the important numbers without drowning in data?

That is a useful problem to solve. A clean screen can turn a vague idea such as “profitable companies with manageable debt” into a shortlist. Company and sector context can then make the ratios more legible. Plain-language explanations lower the cost of getting from a ticker to a sensible first set of questions.

The discipline comes after the shortlist. A composite score is not a recommendation, a low valuation multiple is not automatically value, and an AI explanation is not evidence by itself. A serious user should still ask which filing supplied a number, whether it is consolidated or standalone, which period it covers and whether a corporate action changed the comparison.

Bull Run is therefore best understood as an accessible discovery and first-pass research environment—not as a replacement for judgement.

Multibagg AI: accessible company and document research

Multibagg AI approaches the market through an AI-native research experience. Its public materials describe company exploration, questions across financial documents, thematic discovery, concall and filing workflows, market intelligence and portfolio features for Indian equities.

Its central user question is slightly different:

I want to understand this company and keep up with new information without reading every document from the beginning.

That makes conversational research useful. A user can begin with a company, ask what changed, move into the underlying documents and follow a portfolio or watchlist. The product also presents itself as research rather than a stock-tips service, an important distinction in a category where fluent answers can otherwise look more certain than they are.

The same verification test still applies. A citation should support the exact sentence, not merely come from a related document. A financial answer should identify the period, unit and reporting basis. When evidence is unavailable, the safest system says so instead of completing the gap with plausible language.

Multibagg is a direct fit for investors who want broad, accessible AI-assisted company research and monitoring around Indian stocks.

Altys: research and portfolio governance for a team

Altys begins after the first company question. Its design problem is how a professional team can make an investment process repeatable, inspectable and continuously monitored.

A PMS, AIF or family office may already use a screener, spreadsheets, document folders and capable analysts. The harder problem is that the process is fragmented. Eligibility rules live in one file, factor definitions in another, financial models on personal drives, concall notes in documents, exceptions in meeting minutes and alerts in inboxes. Six months later, reconstructing why a position existed can be harder than researching it again.

Altys connects that chain:

1. Define a universe and explicit strategy rules.
2. Test those rules using information that was actually knowable on each historical date.
3. Apply the firm’s own factor scorecards rather than a universal black-box rating.
4. Research many shortlisted companies on consistent questions through GenGrid.
5. Link material claims to filings, concalls, guidance and operating evidence.
6. Carry the research into models, portfolio context and documented human overrides.
7. Monitor the conditions that would strengthen or weaken the original thesis.
8. Preserve a record that another analyst or investment committee can inspect later.

AI helps retrieve, compare, organise and explain. It is not the hidden calculator for every ratio or strategy result. Calculation-heavy work uses explicit methods; unsupported evidence should remain unavailable; the portfolio manager retains the decision.

Why Excel verification is a meaningful difference

“Explainable AI” often means showing a paragraph about how an answer was generated. That is not enough for an investment committee. The useful standard is whether another person can reproduce the work.

Altys treats exportability as a control:

• strategy screens can leave the system with the universe, rule and resulting membership;
• scorecards and scorecard reports can expose inputs, bucket logic, formulas and provenance;
• GenGrid research can be exported for review across companies;
• analytical tables can be checked outside the application;
• alerts can be inspected against the condition and evidence that caused them to fire.

The purpose is not to move the workflow back into spreadsheets. It is to let Excel remain an independent verification layer. A professional user should be able to challenge the software without trusting the software to explain itself.

The comparison by research job

Research job	Bull Run	Multibagg AI	Altys
Public company discovery	Core fit	Core fit	Public pages available; full workflow is professional-pilot access
Fundamental screening	Core fit	Available within a broader research workflow	Connected to point-in-time strategy rules and governance
Plain-language company explanation	Core fit	Core fit	Used within cited professional research
Document and concall questions	Supporting workflow	Core fit	Connected with guidance history, scorecards, models and portfolio context
Point-in-time historical testing	Not the central public claim	Not the central public claim	Core design requirement
Firm-defined factor scorecards	General platform scores	Product-specific research signals	Team-defined, deterministic scorecards with exportable verification
Backtesting	Check current product scope	Check current product scope	Point-in-time strategy and factor testing
Portfolio governance	Portfolio research and tracking context	Portfolio features	Rules, exceptions, decision context, drift and monitoring across a team
Excel verification	Check the required export on the current plan	Check the required export on the current plan	Core strategies and scorecards are designed to be independently checked
Best fit	Self-directed investor seeking guided research	Investor seeking accessible AI-first research	Professional team governing a repeatable process

“Not the central public claim” does not mean a provider lacks a capability. It means a buyer should verify it directly rather than infer it from adjacent marketing language.

A six-question test before choosing

Run the same difficult company through every shortlisted product. Do not use only a clean, large-cap example.

1. Can you reach the exact source?

Ask for a material number, open the cited document and confirm the value, period, entity and unit.

2. What happens when the answer is unavailable?

Ask for an operating KPI the company does not disclose. A confident invention is worse than a visible gap.

3. Can you reproduce a score?

If the product says a company has a high quality score, can you identify the inputs, weights and missing-data treatment?

4. Is the backtest point-in-time honest?

A historical screen should not use a restatement, revised classification or late filing before the market could have known it.

5. Does the research survive outside the interface?

Export the result. Check whether the evidence, rules and calculations remain intelligible in Excel or another independent review surface.

6. Can a finding become a monitored condition?

Research has continuing value only if the system can tell you when a relevant assumption, guidance item, ownership pattern or financial threshold changes.

Which one should you choose?

Choose Bull Run when you are a self-directed Indian investor who wants a public, guided route through screening, fundamentals, comparisons and plain-language explanations.

Choose Multibagg AI when you want accessible AI-first company and document research, thematic discovery and portfolio-oriented monitoring for Indian stocks.

Evaluate Altys when the buyer is an Indian investment team and the requirement is broader: point-in-time data, firm-defined rules, scorecards, cross-company research, models, portfolio governance, Excel verification and continuous monitoring in one auditable process.

Many investors will use more than one system. A fast public research tool can sit beside a deeper professional workflow. The key is to know which tool is responsible for discovery, which holds the evidence, which owns the calculation and which records the final human decision.

For the wider market, see the best AI stock research tools in India and the broader guide to investment research platforms for Indian stocks.

This article compares research software, not securities. It is educational and does not contain investment advice or stock recommendations. Altys Labs is not a SEBI-registered Research Analyst or Investment Adviser.