✨ AI Advisor

What Is the AI Advisor Tab?

The AI Advisor tab is a structured prompt library — 18 expert templates that turn the company data on your screen into a precise, context-rich brief ready to paste into Claude, ChatGPT, Gemini, or Perplexity. It is not a chatbot embedded in the page. It is a research accelerator: it does the hard work of framing the right question with the right context, so the AI you use delivers analysis that is specific, structured, and actionable rather than generic and meandering.

Each template card shows:

• Name and purpose — what question this template answers
• Best platform badge — which AI produces the best output for this template (Claude / Gemini / ChatGPT / Perplexity / All platforms)
• Copy Prompt — one click copies the full prompt to your clipboard
• .TXT — download the prompt as a text file
• Direct platform links — open ChatGPT, Gemini, Claude, or Perplexity directly
• Edit — customise the template before copying

The Intelligence Block — What Happens Before Your Prompt

This is the most important thing to understand about the Premium Web App AI Advisor. Before any template reaches the AI, Finmagine prepends an Intelligence Block — a structured context layer computed from the company's financial data. You do not write this. You do not copy it. It is automatically attached to every prompt.

The Intelligence Block contains four components:

1. Finmagine Rating

A BUY / HOLD / AVOID signal derived from the Scorecard and valuation metrics. This is not a recommendation — it is a structured signal that tells the AI the current overall assessment so it can weight its analysis accordingly.

2. Reverse DCF

A Discounted Cash Flow model worked backwards from the current stock price. It calculates the growth rate the market is implying — and compares it to the company's actual historical growth rate. The gap between the two is the signal:

• Implied CAGR significantly below actual CAGR → market is pricing in deterioration that hasn't materialised → potential undervaluation
• Implied CAGR significantly above actual CAGR → market expects acceleration → priced for perfection

3. Anomaly Flags

Pre-computed alerts from the ratio analysis. Examples: "ROCE (36.8%) significantly exceeds ROE (27.3%) — high capital intensity or large minority interests", or "Debtor days rising 3 consecutive years — receivables quality deteriorating." These flags are passed directly to the AI so it investigates them rather than missing them.

4. Key Metrics Snapshot

A compact header showing P/E, ROCE, D/E, and 3-year revenue CAGR — the four numbers that most quickly characterise a business. The AI has these in context before reading a word of the template.

5. Richer Context — Auto-Injected Corporate Activity

Two additional data layers are now automatically injected into every prompt, giving the AI corporate activity context without any extra effort from you:

• Corporate Actions — last 24 months: QIB allotments, warrants, rights issues, bonus shares, stock splits, and dividends are extracted from the Screener page and included in the prompt. The AI can now flag dilution patterns, understand capital structure changes, and contextualise management's capital allocation signals.
• Significant Announcements — last 6–7 months: Instead of the most recent 10 filings (which often include routine updates), the system now filters for genuinely material events: board results, fundraising, acquisitions, CEO/MD changes, SEBI orders, buybacks, and major capacity announcements. The AI receives a curated feed of what actually matters, not a firehose of noise.

Why Premium Web App AI Advisor Beats the Chrome Extension

The Finmagine Chrome extension (AI Advisor for Screener.in) uses the same prompt templates. So why bother with the Premium Web App? The answer is entirely in what gets sent alongside the template — the data layer underneath it.

The practical consequence: the AI receives a pre-digested analyst briefing instead of a spreadsheet dump. It does not have to classify ratios — they are classified. It does not have to spot anomalies — they are flagged. It does not have to calculate valuation implied growth — it is computed. Every cycle of reasoning the AI would have spent on data processing is now spent on insight.

The Stage 2 → Growth Triggers Flow

One of the most powerful cross-product integrations in Finmagine connects the Trader Chrome extension with the AI Advisor Web App. It bridges a technical signal (price action stage detection) with a fundamental research question (what is driving this setup?).

This is a complete research workflow in under 5 minutes: Trader surfaces the technical setup → AI Advisor explains the fundamental catalyst → you decide whether the thesis justifies the position. Neither product alone delivers this — it requires the integration.

The 18 Templates — Complete Reference

Templates are organised below by purpose. Each entry shows what the template does, which AI platform delivers the best output, and — where a dedicated deep-dive tutorial exists — a link to the full guide.

Platform Selection Guide

Not every AI platform handles every template equally. The best platform badge on each card is based on tested output — here's the full reasoning:

Customising Templates with Edit Prompt

Every template has an Edit button that opens the full prompt text in an editable view. You can modify it before copying. Common uses:

• Add a specific question you want answered within the structured output
• Focus on a specific period — e.g. restrict the Quarterly Deep-Dive to Q3FY26 only
• Add sector context the AI might not have — recent regulatory change, a competitor announcement
• Remove sections you don't need to keep the output concise
• Add a comparison company to templates that normally cover a single stock

Recommended Workflow

Not sure which templates to run? You don't need all 18 templates for every stock. Most users get 90% of the picture from 5. The AI Advisor has a built-in template guide — click the "Not sure which templates to run?" disclosure in the panel to see three curated combinations by use case.

Run all 18 only when doing institutional-grade deep research on a high-conviction position.

Step 1 Start with Comprehensive Analysis if you're new to a company. Read the output to build your mental model. Flag the two or three things the AI identifies as the most important risks or opportunities.

Step 2 Run Risk-Reward once you understand the business. This gives you the structured investment case — what needs to go right, what could go wrong, what margin of safety the current price implies.

Step 3 Use Quarterly Deep-Dive post-results — every quarter, after the concall, this is the fastest way to assess whether the management narrative is coherent, improving, or deteriorating.

Step 4 Run Management Credibility Score after 2–3 quarters of tracking. This is where the multi-quarter pattern becomes visible — not whether last quarter's guidance was met, but whether the organisation consistently delivers on what it promises.

Step 5 Use Growth Triggers before adding to a position — if the Scorecard and ratios look good, this template answers the last question: what specific event or inflection will cause the market to re-rate this stock? Without a trigger, a great business can stay sideways for years.

Step 6 Use Ask Anything for surgical questions — once you've built your thesis, use this to verify specific claims. "Did management mention the new plant capacity timeline in the last 3 concalls?" Claude will find the exact quote and quarter.