Decision intelligence for the person
who defends the decision.
Lantern Labs runs your next live investment decision through a proprietary 14-dimension research framework and your own investment philosophy — naming what would make the thesis wrong, and setting the exact thresholds to watch.
What this actually is
Not just faster research. —Decision intelligence.
Lantern Labs helps PM-led family offices, emerging hedge funds, and concentrated funds turn one live investment decision into a documented, falsifiable, and compounding judgment.
Documented
Every thesis is written down with the reasoning intact, so the decision can be defended in the room and revisited later.
Falsifiable
We name what would make the thesis wrong and set the exact thresholds to watch before the position is on.
Compounding
The record stays with the firm, so the next decision is sharper than the last one — regardless of who is on the desk.
Do you recognize this decision?
You're not looking for another dashboard. You're sitting with one real, live decision, and one of these is probably true right now:
- SignalA position blew up, and looking back, the killer risk was knowable — it just never got argued as hard as the bull case.
- SignalA senior analyst left and took the reasoning with them. The position is still on the book; the reason it went on isn't.
- SignalYou ran the name through a research engine and got a fast, competent, generic memo that told you everything about the company and nothing about your decision.
- SignalIn your last IC meeting, nobody could crisply answer: what would make us sell this?
If any of those land, the underlying issue is the same one: your edge is your judgment, and right now it isn't being captured, pressure-tested, or compounded — it's re-derived from scratch every time, and lost every time someone leaves.
How durable is your decision process, really?
Twelve questions, about three minutes, and a scored breakdown of what would fail first if a key person left tomorrow.
How is Lantern different from a research engine I already use for free?
Research engines like Perplexity are genuinely excellent, and they keep improving for free every quarter — at search, retrieval, filings, and drafting a competent IC memo. Lantern concedes that openly, because a prospect who has used both sees through any parity claim anyway.
The framework and the founder's judgment.
A fixed, 14-dimension research methodology where the Anti-Thesis is argued as hard as the bull case, with weak-link/compounding synthesis, Confirmed/Inferred/ Unknown labeling on every data point, reusable Sector Bases, and a failure-pattern library — carried by a founder who has operated on all four sides of a deal: research, portfolio management, investment banking, and management consulting. That judgment is shaped by roughly 20 years across India's capital markets. This produces day-one insight quality, before any client history exists.
Compounding client memory.
Every engagement records what you believed, what the market believed, why you differed, the key variable, the falsifier, the outcome, and the classified error. That record is retrieved into every future decision, so later calls are demonstrably sharper because of earlier ones. It cannot be copied overnight, because it is earned inside the relationship. That is the game changer: your judgment becomes an institutional asset that survives turnover and compounds with every decision.
Research engines tell you everything about a company. Lantern tells you everything that matters... through your lens, applied consistently, every time.
Generic AI vs. Specialized Intelligence
Generic AI can speed up the work. But fragility shows up downstream.
Faster output, same structure underneath. Memory still lives in one analyst's files, challenge still depends on someone volunteering it, and continuity still leaves with the person who built the model. See how by selecting analyst level:
| Capability | Junior analyst | LanternLabs® |
|---|---|---|
| Research quality | Variable | Standardized floor |
| Anti-Thesis discipline | Prompt-dependent | Mandatory workflow |
| Decision memory | Personal notes | Institutional asset |
| Continuity after departure | Low | Retained by the firm |
| Learning from mistakes | Usually informal | Classified, retrievable |
| Independent challenge | Incentive-limited | Structurally adversarial |
Analyst columns assume LLM assistance.
Full capability comparison available on the Services & Pricing page. →
What do you actually get?
The entry point is one in-depth report on one live investment decision you actually care about. It delivers: a decision brief and full analysis; a financial model and valuation; the Weak Link and the strongest Anti-Thesis; falsifiers with measurable thresholds plus monitorables; and the first entry in your accountability ledger. One report proves the process on one decision. Ongoing coverage is what buys the compounding part — the same decision record kept current as the business, the results, and the valuation change, so judgment sharpens on every decision after the first.
- A complete decision package on the name you're weighing now.
- Every call includes falsifiers, thresholds, and monitorables.
- Each decision is logged so your memory compounds over time.
What proof do you have that this works?
- A fixed, public 14-dimension framework — mandatory Anti-Thesis, falsifiers with measurable thresholds, a scenario tree, and a full cited source appendix.
- Complete public sample reports — full deep-dive decision reports, including one on Meta and one on the India small-cap Raghav Productivity Enhancers (RPEL) — free proof, paid specialization.
- A falsifiable track record by design — every call is logged with a threshold and a date, then scored against what actually happened, weighted deliberately toward the refuted theses.
- Founder credibility — 20 years inside India's capital markets, operating on all four sides of a deal. (founder's full background)
Ready to test this on your own decision?
Book a 30-minute discovery call with Tejas Sarvaiya directly — not a demo, not a 'do you like us' chat. It examines your last real decision: what slowed it down, what surfaced too late, and how you track the thesis today.
Not ready for a call yet? Read a complete free sample report or the research-engine-vs-Lantern comparison first. Nothing client-specific is ever free — but the proof of capability always is. (Services & Pricing)
Questions
Is this just AI research, or another Perplexity?
No — and Lantern doesn't pretend research engines aren't excellent, because they are, and they keep improving for free every quarter. What a research engine can't do is remember your firm's philosophy from one session to the next, argue your Anti-Thesis with the same discipline every time, or compound a decision record that's specifically yours.
Do you tell me what to buy, sell, or hold?
No. Lantern is decision intelligence, not decision making. You will never see buy/sell/hold language from Lantern — the job is to sharpen your decision, not make it for you.
Is this a tool I log into, a person, or a report?
It's a service that produces an inspectable artifact — a decision brief with a full Anti-Thesis and falsifiers — plus a compounding memory of your firm's decisions over time.
How is the memory moat real if Lantern is early?
Honestly: today it's process quality and execution. The data moat — the compounding memory — is earned as engagements accumulate. That's stated plainly rather than oversold.
What happens to my thinking and my data?
You own and can port your data and philosophy. Only generalized, non-confidential learning improves Lantern's reusable Sector Base — nothing client-specific ever transfers to another client.