What Makes This Different How this platform compares to retail tools and general-purpose AI

This platform sits in a gap between two categories of tools most investors use: brokerage-provided research (Schwab, Fidelity, Robinhood) and general-purpose AI assistants (ChatGPT, Claude). Neither was designed to do what this does.

vs. Retail Brokerage Platforms

Schwab Analyst Ratings, Fidelity Research, Robinhood Snacks — these give you pre-packaged research written for a mass audience. They’re useful for basic due diligence but share the same structural limitations:

CapabilityRetail PlatformsThis Platform
Earnings Analysis Beat/miss headline, maybe a summary paragraph Structured extraction of every metric, margins, guidance, management tone, themes — compared quarter-over-quarter automatically
Investment Thesis Third-party analyst reports (if available) Auto-generated theses with conviction scoring, delta tracking, consistency checks — plus ingestion of your own thesis notes and external documents, with bias flagging
Scoring Star ratings or buy/hold/sell from a single analyst Multi-dimensional composite (Fundamental, Thematic, Valuation, Catalyst) with transparent formulas and configurable weights
AI Exposure Not tracked Five-dimension AI Resilience framework scored per company, with infrastructure reinterpretation and calibration anchors
Ownership Intelligence Top holders list (delayed) SEC Form 4 insider transactions with relative scoring (% of holdings, baseline context). WhaleWisdom 13F institutional tracking with accumulation/distribution signals, HHI concentration, holder trend sparklines.
Signals Basic price alerts Estimate revisions, PE momentum (velocity + acceleration), theme lifecycle tracking, peer rank drift, thesis consistency, insider activity, institutional momentum, price path flags, valuation drift
Filing Intelligence Links to SEC filings 10-Q/10-K MD&A extraction with XBRL + LLM fallback, risk factor delta analysis (new/changed risks only), 8-K same-day press release parsing
Automation None — you check manually Full autopilot: pre-market recaps, post-market recaps, earnings processing, signal alerts, weekly outlook — 20+ scheduled daily tasks
Peer Context Side-by-side comparison tables Percentile rankings across 5 dimensions within custom peer groups, with composite scoring and rank drift alerts

vs. Claude / ChatGPT

You can ask Claude or ChatGPT to analyze a stock. You’ll get a thoughtful response. But that response has no memory, no data pipeline, and no way to track whether its analysis was right. Here’s the structural difference:

CapabilityGeneral-Purpose AIThis Platform
Data Freshness Training cutoff + whatever you paste in Live pipeline ingesting FMP, SEC EDGAR (XBRL, Form 4, 8-K, 10-Q/10-K), FRED, WhaleWisdom 13F, CarbonArc alt data, Reddit sentiment, newsletters — refreshed on schedule
Persistence Ephemeral — each conversation starts blank Persistent signal store with TTL-based expiration, historical snapshots (PE, estimates, conviction, target accuracy), version-tracked theses
Scoring Discipline Subjective, varies by prompt Deterministic formulas with calibration anchors, soft caps, cross-signal penalties, and sector-aware thresholds
LLM Calibration Uncalibrated — scores drift across sessions Reference anchors (PLTR, ORCL, CEG, etc.) provided in every scoring prompt to ground output. 92-point soft cap requires cited vulnerabilities.
Consistency Checks None — it will confidently contradict itself Thesis consistency engine that flags when conviction contradicts estimates, ratings, price action, peer rank, or ownership signals
Longitudinal Tracking Cannot track changes over time Theme momentum lifecycle (new → accelerating → stable → decaying), estimate revision velocity, conviction history sparklines, target accuracy over time
Portfolio Awareness Doesn’t know your holdings Portfolio and watchlist distinction flows through every view: scoring, peer rankings, previews, rebalancing, alerts. Inception position tracking, transaction reconciliation, Jefferies brokerage integration.
Automation You drive every interaction Background scheduler runs 20+ daily tasks: signal refreshes, earnings processing, insider activity, price path analysis, recap generation, alert checks

The Core Idea

Pipeline, not chatbot

This platform uses LLMs as a component inside a structured pipeline — not as the interface itself. Claude scores AI resilience, extracts transcript data, generates theses, analyzes 10-Q/10-K filings, and writes recaps. But every LLM output flows through deterministic scoring formulas, consistency checks, and calibration constraints before it reaches you. The result is AI-assisted analysis with guardrails, not AI-generated opinions.

Your thesis, pressure-tested

The system doesn’t just generate its own theses — it ingests yours. You can attach thesis notes, external research documents, and personal conviction rationale to any company. The pipeline then treats your input as a first-class signal: it incorporates your reasoning into thesis generation, but simultaneously flags potential biases by cross-referencing your narrative against quantitative signals (estimate revisions, peer rankings, price action, financial health trends, insider activity, institutional flows). If you’re bullish on a name where the data is deteriorating, the system will surface that tension explicitly rather than silently agreeing with you.

How Bias Detection Works

When user-supplied thesis notes are present, the system runs a structured check across several dimensions:

CheckWhat It Flags
Conviction vs. Estimates High user conviction but consensus estimates are falling — are you seeing something analysts aren’t, or anchoring to a stale view?
Conviction vs. Price Action Bullish thesis but price is below your own bear case target — the market is pricing in something you may be dismissing
Conviction vs. Peer Rank High conviction on a name ranking in the bottom quartile of its peer group across multiple dimensions
Narrative vs. Financial Trends Growth thesis but margins contracting, FCF declining, or leverage increasing over the trailing 4 quarters
Conviction vs. Ownership Bullish thesis but institutional holders are distributing and/or insiders are selling at elevated levels relative to historical baseline
Confirmation Bias User notes emphasize the same bullish themes already captured by the system — flags absence of bear-case consideration

The goal isn’t to override your judgment. It’s to ensure that when you hold a strong view, you’re doing so with full awareness of what the data says — not in spite of it accidentally.

What Runs Automatically

Once deployed, the platform operates on a daily schedule without manual intervention:

Daily (Mon–Fri)

Time (ET)TaskWhat It Does
2:00 AMOvernight GapfillFill missing summaries and theses for tickers that lack them
3:00 AMSignal ValidationValidate signal accuracy; compute calibration factors (Sunday)
4:00 AMDecision MatureMature decision scorecards
5:45 AMStaleness AuditCheck data freshness across all tables, email if stale
6:00 AMCatalyst RefreshRefresh all catalyst data (earnings calendar, conferences, macro events)
6:15 AMInsider RefreshSEC Form 4 parsing + insider signal computation
7:00 AMMorning AlertsScan all signals for threshold breaches, generate alert digest
8:30 AMMarket HealthFRED/FMP macro snapshot (VIX, DXY, treasury rates, sector performance)
8:35 AMPrice PathIndex technicals (SPY/QQQ/SMH/IGV) + company price path flags
8:40 AMPre-Market RecapLLM-generated briefing: overnight movers, key levels, day’s earnings calendar
9:00 AMEarly Scan (AM)Quick-process any earnings reported pre-market
9:10 AMMacro NarrativeTiered: Mon=Week Ahead, Tue/Wed/Fri=update, Thu=Week in Review
4:30 PMPost-Market RecapEnd-of-day briefing with session performance (FMP batch-quote), after-hours earnings
5:30 PMNews SummaryDaily news digest email
7:00 PMEvening AlertsSecond alert pass after full day’s data settles
8:00 PMScore ChangesDaily conviction score deltas
10:00 PMEarnings AutopilotFull pipeline: prep upcoming (7-day lookahead), process reported, refresh scores

Tuesday + Friday

Time (ET)TaskWhat It Does
6:00 AMBuy RadarCompute watchlist recommendations
5:00 PMFull RefreshComplete chain: prices → PE → technicals → financial health → theme momentum → signals → revision acceleration → AI scores → conviction → contrarian → bias check

Friday Only

Time (ET)TaskWhat It Does
4:30 PMPerf NarrativeAI-generated portfolio performance narrative
5:00 PMNewsletter DigestThe Information intelligence summary (multi-story extraction)
5:30 PMSector InsightsWeekly sector analysis + email

Sunday

Time (ET)TaskWhat It Does
3:30 AMThesis AccuracyThesis accuracy dimension analysis
4:30 AMValuation HistoryMonthly valuation history snapshot (1st Sunday only)
4:45 AMDivergenceConsensus divergence computation
4:50 AMSnapshotsTAM estimates, conviction snapshot, target accuracy snapshot
5:00 AMBacktestsAll backtests + summary + model proposals
5:15 AMTheme CurationEmerging theme detection (bi-weekly)
5:30 AM10-Q/10-K FilingsProcess all pending quarterly/annual filings
2:00 PMTicker DiscoveryDiscovery scan for new coverage candidates
6:00 PMWeekly OutlookWeek-ahead briefing with earnings calendar, macro events, thesis updates due
7:00 PMConviction ReportWeekly conviction report email

Data Sources

SourceWhat It ProvidesRefresh
FMPTranscripts, analyst ratings/estimates, price history, batch quotes, treasury rates, VIX/DXY, company profiles, key metricsDaily + on-demand
SEC EDGAR (XBRL)Quarterly financial statements (revenue, margins, balance sheet)Weekly
SEC EDGAR (8-K)Same-day earnings press releases, parsed by ClaudeDaily (earnings days)
SEC EDGAR (Form 4)Insider transactions (open-market purchases/sales, % of holdings)Daily 6:15 AM
SEC EDGAR (10-Q/10-K)MD&A themes, risk factor deltas (XBRL extraction + Claude Haiku fallback)Sunday 5:30 AM
WhaleWisdom13F institutional holdings (top 50 holders per ticker per quarter, HMAC-SHA1 auth)Quarterly
FREDMacro economic indicators (interest rates, CPI, unemployment, GDP)Daily 8:30 AM
CarbonArcAlternative data (web traffic, app usage, hiring, credit card spend) for covered entitiesOn-demand
RedditRetail sentiment on covered tickers, Claude-scored for signalWeekly
NewslettersMulti-story extraction with per-story ticker attribution and theme distillationFriday 5:00 PM
Anthropic ClaudeTranscript analysis, thesis generation, scoring, recap writing, 8-K parsing, 10-Q/10-K analysis, AI resilience scoringThroughout