Extract alpha from the best investing minds on the internet.
See what is worth trusting now.
AI Frontrunner ranks market calls by source history, thesis context, graph connections, and follow-up research so each idea comes with evidence, not hype.
Explore the public proof layer
Start with the live research preview, thesis graph, public author, ticker, and ticker-thesis pages, then move into the public API docs. These surfaces are designed for discovery, SEO, and proof: who made the call, what they said, how it worked out, how theses connect, and how to integrate the data programmatically.
Authors
Proof-backed author pages with historical recommendations, trust scores, and right-versus-wrong analysis.
Open authors →
Assets
Public asset rankings driven by live ticker theses, author conviction, and observed thesis-call outcomes.
Open assets →
Ticker Theses
Browse active and historical asset theses linking one thesis to many assets, authors, and source proofs.
Open ticker theses →
Measure who actually generates alpha
Collect predictions and investment ideas from internet experts, backtest what they said in the past, and rank authors and sources by observed investing performance.
Turn public content into live investment theses
Extract ticker exposure, thesis, direction, timing, and confidence from noisy videos, posts, interviews, and threads in a structured form.
Decide whether new ideas are worth trusting
When a source publishes a new idea, score it using that source’s actual historical track record and related thesis outcomes instead of relying on raw charisma.
Built for source-driven alpha discovery
Most investing tools start with a ticker. AI Frontrunner starts with the author, source, and thesis history behind the ticker, so you can tell who consistently adds signal, who destroys it, and which live ideas deserve capital today.
The output is not another noisy feed. It is a continuously refreshed ranking of theses and tickers weighted by historical source quality and current conviction.
X / Twitter
Track recurring stock calls, macro predictions, and thesis updates from high-signal finance accounts.
Separate reflexive hype from durable retail insight by tracking which communities and authors were actually right.
YouTube
Backfill creator history, extract market-related ticker theses from videos, and benchmark channels against forward market outcomes.
Collect expert sources
Register internet authors, channels, and communities that regularly publish market views and stock ideas.
Reconstruct historical predictions
Backfill their old content and rebuild what they were actually arguing, buying, avoiding, or shorting over time.
Extract theses and asset calls
Convert raw content into structured ideas with assets, thesis, direction, time window, and supporting rationale.
Backtest what actually worked
Compare those ideas against subsequent market data to estimate which authors and sources have historically generated alpha.
Rank current opportunities
Use historical trust, current thesis quality, and market context to keep a live ranked list of the most interesting assets and narratives.
Pricing built around research depth and execution
Start with read-only access to the shared intelligence layer, move to Basic when you want alerts and Telegram workflows, and use Pro for priority workspace research requests and Desk review.
Free is for consumption. Basic is for operating on the shared signal layer. Pro is for building proprietary edge on top of it.
Organization plans
For groups, billing should belong to the organization. Members inherit access from the workspace plan while admins manage seats, roles, and shared research capacity.
90-day Pilot
Guided validation for a small public-equity team before a full Desk deployment.
Custom
Annual contract
One defined research question and weekly decision briefs
Named onboarding owner and evidence-review cadence
Private-workspace readiness assessed before any data is shared
Pilot success criteria agreed before activation
Research Desk
A reviewed research workflow for an established small investment team.
Custom
Annual contract
Decision briefs, daily deltas, and a weekly IC memo
Configured evidence and research-review workflow
Usage, access, and data-scope terms set in the contract
Private data and shared-workspace features only after access controls are enabled
Enterprise
Custom deployment, controls, and commercial terms.
Custom
Annual contract
Custom seats, usage limits, and research budgets
Security review, procurement, and contract support
Dedicated onboarding and workflow design
Optional private data-source and integration roadmap
Make internet investing research auditable.
AI Frontrunner is built for investors who want more than another feed of hot takes. It turns public market commentary into a ranked evidence layer with backtests, source trust, and realtime thesis monitoring.
If a source was early and right in the past, that should matter. If a source has a long history of bad calls, that should matter too. The product is built around that discipline.
Research operators
Use one evidence layer to decide which internet experts deserve analyst attention and which narratives should be ignored.
Self-directed investors
Replace scattered screenshots and notes with a ranked asset list built from trusted sources with proven historical performance.
Trading teams
Benchmark conviction by source track record and thesis quality instead of letting the loudest narrative dominate the process.
Operator Workspace
Replace opinion streams with a trust-weighted market intelligence system.
Track expert calls, score them against history, and keep a live ranked view of the tickers and theses that matter most right now.
Designed for investors who want to extract alpha from the internet without trusting every loud account equally.