The Memory Layer for Market Intelligence
ChatGPT forgets. Perplexity searches. SupaDrop remembers, connects, and compounds.
The Amnesia Problem
Today's AI is brilliant but stateless. Every conversation starts from zero. You can't build on previous analyses. You can't track how a CEO's tone has shifted over 8 quarters without manually rewatching calls, re-reading transcripts, or asking a chat model that can't see history.
You get an answer. Then it's gone. No memory. No connections. No compounding insight.
SupaDrop fixes that.
Disconnected vs Connected
Chat AI
Isolated answers, no memory
SupaDrop
Connected graph, compounding insight
The Difference
SupaDrop is an intelligence infrastructure, not a chat assistant.
One Graph. Every Source.
We started with earnings calls and YouTube interviews, and are expanding from there.
Earnings Calls
YouTube, investor relations streams
Podcasts & Interviews
Long-form conversations and panels
Analyst Commentary
Twitter/X, Substack, expert threads
News & Articles
Context from reputable sources
SEC Filings (coming soon)
10-Ks, 10-Qs, 8-Ks
From ingestion to answer
A four-step pipeline designed for precision and provenance.
Ingest
Content flows in automatically - earnings calls, podcasts, tweets, articles.
Extract
Structured data pulled out: metrics, quotes, sentiment, entities, timestamps.
Connect
Build your private intelligence graph. See patterns across sources and time. No vendor lock-in. Your data stays yours.
Query
Ask anything. 'How has NVIDIA's tone on China changed over 2 years?' Answer in seconds, with citations.
Where teams use SupaDrop
Built for analysts, PMs, founders, and anyone tracking narratives before they show up in price.
Track a Company
- •Every earnings call, automatically analyzed
- •Quarter-over-quarter comparison
- •Guidance tracking, sentiment trends
- •Alert when tone shifts or new risks surface
- •Example: "What did Jensen Huang say about supply chain in the last 4 quarters?"
Monitor a Theme
- •Track 'AI agents' or 'tariff impact' across 50 companies
- •See who's talking about it, how often, in what context
- •Sentiment echo: how does Twitter react vs. what management said?
- •Get alerts when mentions spike
- •Examples: Track 'gross margin pressure' across semiconductors; see which CEOs suddenly mention 'regulatory tailwinds'
- •Subtext: Track narratives before they show up in price.
Build Research with Provenance
- •Multi-source synthesis with full attribution
- •Every insight backed by citations into transcripts and clips
- •Export structured data for reports or models
- •API access for quant workflows
Bloomberg for Unstructured Data
Not a chat assistant. An intelligence infrastructure.
Bloomberg made financial data queryable. SupaDrop does the same for earnings calls, podcasts, interviews, and social media.
Every insight is backed by citations and runs through a trust layer designed to prevent hallucinations.
"What if every piece of content you cared about was automatically analyzed, structured, and connected - so you could query 8 quarters of management commentary in 2 seconds, and see exactly which clip or paragraph each insight came from?"
Real Product. Shipping Now.
We're live with capabilities that analysts use today.
YouTube earnings call analysis
Already shipping in the MVP.
Multi-source synthesis with attribution
Already shipping in the MVP.
Structured output you can query and compare
Already shipping in the MVP.
We're building in public. Try the demo, join early access, and shape what comes next.
Ready to see it?
Already used in real earnings call research.