Coverage fragments
Financial data, documents, models, notes and portfolio exposures live in separate tools, so context is reconstructed manually.
For portfolio managers
Research breadth without losing the investment process.
Altys helps Indian portfolio managers and lean research teams screen, understand, model and continuously monitor companies on one inspectable evidence trail. AI handles volume; people retain assumptions, exceptions, sizing and capital allocation.
Research coverageFactor scorecardsPortfolio contextThesis monitoring
The operating problem
The portfolio manager’s bottleneck is attention, not information.
A wider opportunity set, deeper diligence and continuous holding-period research all compete for the same finite review time.
Generic alerts create noise
A market feed reports what happened. It rarely knows which company-specific assumption the desk actually cares about.
Strategy evidence is hard to replay
If screens, scores and exceptions are not versioned and point-in-time, the desk cannot honestly evaluate its own process.
The workflow
From investment philosophy to continuously monitored book.
The system makes the research loop repeatable without turning judgement into a black-box score.
01
Define
Express the universe, eligibility gates, scorecards and portfolio constraints.
02
Research
Connect financials, company KPIs, filings, calls, guidance, ownership and forensic evidence.
03
Model
Use sourced history with Excel or Python while keeping assumptions explicit and owned.
04
Decide
Review evidence, counter-evidence, valuation and portfolio impact before approval.
05
Monitor
Route only material changes against the original thesis and portfolio rules.
What the system adds
A research operating system—not an AI portfolio manager.
Altys does not allocate capital. It prepares evidence, runs the team’s rules, monitors changes and preserves why a decision was made.
Point-in-time screeningHistorical research uses what was actually knowable on the decision date, not today’s revised history.
Firm-owned scorecardsWeights, gates, peer groups, missing-data policy and overrides remain visible and versioned.
Portfolio-aware researchCompany evidence can be reviewed alongside weights, concentrations, factor exposures and overlapping holdings.
Excel-verifiable outputsExport the inputs, formulas, gates, scores, ranks and rejected names for independent inspection.
Questions, answered
What teams ask before a pilot.
What AI tools do portfolio managers need?
A professional stack should connect sourced financial data, primary documents, screening, modelling, scorecards, portfolio context and continuous monitoring. A chatbot alone covers only part of that workflow.
Can Altys monitor a concentrated PMS or AIF portfolio?
Yes. Teams can define company-specific guideposts, management commitments, factor thresholds and portfolio rules, then review material changes against the original thesis.
Can portfolio managers verify Altys calculations?
Yes. Material claims link to sources, deterministic analytical workflows remain inspectable, and core screens and scorecards can be exported as Excel workbooks for independent checking.
Does Altys decide position sizes?
No. Altys can show portfolio exposures and rule outcomes, but position sizing, overrides and final investment decisions remain with the responsible team.
Related guides
Continue with the workflow that fits your team.
One-month pilot
Test Altys on a portfolio you already know.
Bring a real universe, scorecard, company model or monitoring problem. We will show the evidence trail end to end.