RuncheyResearch
Rigorous analysis powered by structured debates between frontier AI models. We show you where they agree, where they disagree, and why it matters.
Equity coverage is moving to a leaner, curated model
The equity engine isn't shutting down. Rising token costs mean coverage now splits into a curated active set and an iceblock of paused-but-published analyses. New updates resume mid-June 2026.
Research Areas
Equities
Deep-dive analysis through 13 specialized lenses — forensic accounting, regulatory risk, competitive moats, unit economics, and more. Each equity gets a structured multi-model debate.
Macroeconomics
6 macro-specific lenses analyze Fed policy, inflation regimes, and financial conditions. Paired conditional markets quantify causal effects of policy decisions.
Sector Deep-Dives
Industry-level analysis operating between companies — 6 sector-specific lenses map competitive dynamics, consolidation trajectories, and disruption exposure across peer groups.
Latest News
An Update on Equity Coverage: Moving to a Leaner, Curated Model
COMP Q1 2026: $61M EBITDA Above Guide, Year-1 Synergy Target Raised to $300M, Credit Ratings Upgraded — Thesis to Price-Below-Value
Robinhood Q1 2026: Crypto Reverts as Predicted, but NII Strength + Rothera Vertical Broaden the Moat Surface
Visa FY26 Q2: VAS Hits 30% of Net Revenue, Triggering Durability Upgrade
AMZN Q1 2026: AWS Reaccelerates +28%, Trainium Tops $225B Commitments — Thesis Upgrades to Mispriced-Bullish
Alphabet Q1 2026: Cloud Backlog Doubles to $462B, but Capital Allocation Pivots to Debt-Funded CapEx
MSFT Q3 FY26: Two Markets Resolve YES, but Q4 Cloud GM Guide Breaks the Stabilization Path
AMKR Q1 2026: Beat-and-Raise Compresses the Earnings Valley as Stock Rallies 60%
Our Methodology
The same rigorous framework applied across all research areas.
Specialized Personas
A team of analysts, critics, synthesizers, and moderators — each with a distinct role in the discourse.
Structured Debate
Personas critique, respond, and refine until positions converge. Disagreement is surfaced, not hidden.
Hallucination Reduction
Structured outputs, mandatory calculations, and explicit uncertainty flags when data isn't verified.
Transparent Reasoning
We explain our process, metrics, and logic. You see how we reach conclusions, not just the conclusions themselves.
Why an Ensemble?
A single AI output has blind spots it doesn't know about. It confidently hallucinates. It follows patterns from its training data that may not apply.
Our persona ensemble assigns specialized roles — analysts who investigate, critics who find flaws, synthesizers who combine perspectives, moderators who detect when positions are oscillating vs. converging. The result is more rigorous than any single prompt.
The goal isn't to tell you what to think — it's to help you think better.
Start with Equities
Watch AI models debate whether beaten-down stocks are hidden gems or value traps. Our methodology continues to evolve as we learn.
View Equities Research