KEY TAKEAWAYS
- Create a consistent research template across analysts and companies.
- Build peer tables from the underlying supported financial and ownership fields rather than a black-box composite verdict.
- Follow numerical changes into filings and source material instead of stopping at an AI summary.
- Keep source/provenance and freshness visible so the desk can distinguish evidence from interpretation.
A repeatable desk workflow
Define the research question
Start with the decision-relevant evidence needed — not with a request for a stock verdict.
Assemble company facts
Fetch the supported financial trend, ownership, pledge, operating and event context.
Build the peer frame
Resolve relevant peers and compare the same fields and periods across them.
Trace the why
Use filings and disclosures to investigate material changes, preserving the source trail for review.
Research blocks the desk can standardise
Example prompts
EXAMPLE PROMPTS
- Build a five-year financial trend table for these three peers. Use the same fields and periods, show source/freshness context, and do not rank the stocks.
- What changed in promoter/FII/DII ownership over the last reported periods? Cross-check any large move against recent disclosures.
- Compare company-disclosed operating metrics for these peers where the same metric is available. State explicitly when the fields are not comparable.
- Turn this company's latest reported numbers into an evidence checklist for analyst review: financial changes, ownership changes, events and filings. No investment verdict.
What the AI should not do
Do not convert missing evidence into confident narrative, do not silently compare differently-defined metrics, and do not turn the output into a buy/sell/hold label. The analyst should be able to move from every material claim back to the underlying source or reported figure.
If the main job is recurring oversight of an existing book, use the PMS / AIF holdings-monitoring workflow.
FAQ
Common questions
What can an Indian-equity research desk use DalalOS for?
A desk can use DalalOS as structured evidence infrastructure for company financial trends, peer comparison, ownership, promoter pledge, company-disclosed operating metrics, events and filings where supported.
Does DalalOS write the analyst's investment conclusion?
DalalOS supplies the source-aware inputs, not the investment verdict. It does not emit buy/sell calls, target prices or proprietary stock rankings. An AI client can summarise evidence, but the analyst owns interpretation.
Why use MCP instead of copying data into prompts?
MCP gives the AI client a repeatable callable interface. That reduces manual copy/paste, makes multi-step research easier to reproduce, and lets responses retain source/freshness context where available.
Can the desk use one workflow across multiple companies?
Yes. The useful pattern is a common research template — resolve company, gather financials, compare peers, inspect ownership and follow disclosures — repeated across names subject to client orchestration and usage limits.
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