Market intelligence your systems can actually use
One normalized layer for social conviction, trader setups and official filings — built to move cleanly from research to automation.
Financial data used to be scattered across feeds, social posts and regulatory documents. Raspberry turns those sources into structured context without publishing your live results on the marketing site.
- Any
- US ticker, on demand
- ~100
- trusted traders tracked
- AI
- scores every tweet
- 1 key
- all-access, instant
From raw market chatter to structured signal
Every layer is designed to give a human or an agent the context behind the number.
Live X data
We pull what traders are posting about any US ticker on X (Twitter) the moment you ask — the raw conversation, cleaned and structured.
Influencer breakout radar
What the 100 trusted traders are flagging today as pullback/staircase breakout setups — ranked, with their tweets as the why.
AI sentiment — stocks & whole markets
Every post read by an AI model (DeepSeek) and scored bullish/bearish/neutral — for any US stock, or for a whole market (9 tracked: US, gold, silver, BTC, ETH, oil, the dollar, copper and bonds). Market readings use a strict 72-hour window, disclose any search top-up and report confidence separately from price action.
On-demand, any ticker
Ask for any US stock and get fresh sentiment in the moment, cached for 30 minutes so repeat calls are instant.
Trusted trader network
A curated network of real stock & options traders on X — signal weighted by the accounts that actually move markets, not random noise.
Simple REST API
One fast JSON API. Get a key, make a request, get clean data back — no infrastructure to run.
Seven focused APIs. One consistent interface.
Each API does one thing well. The examples explain the response shape without publishing current results; your key unlocks the live data.
Stock Sentiment
Live X sentiment for any US ticker — every post AI-scored bullish / bearish / neutral, with bull & bear recaps.
GET /api/sentiment?ticker=NVDAlabel · score · bullSummary · bearSummaryMarket Sentiment
About 40 quality-filtered X posts across each of 9 whole markets, condensed into a balanced DeepSeek summary.
GET /api/market-sentiment?market=btcmarket · label · score · aiSummaryNews Sentiment
Financial-news headlines read by AI and scored, with source links and dates.
GET /api/news?ticker=NVDAheadlines[] · sentiment · source · publishedAtSentiment History
Is the mood improving or worsening? A sentiment trend line over time, not just a snapshot.
GET /api/history?ticker=NVDApoints[] · direction · change · periodBreakout Radar
The stocks trusted traders are flagging right now — each validated against the real chart and given a pattern, grade and breakout score.
GET /api/influencerssetup · pivot · broke · distance · traderRationaleInsider Trading
Recent SEC Form 4 buys and sells — insider, role, shares, dollar value and a link to each filing.
GET /api/v1/insider-trades/AAPLcode · role · shares · grossValue · EDGAR filingCompany Guidance
Management outlook extracted from official SEC-filed earnings releases, with exact evidence, GAAP basis and changes versus prior guidance.
GET /api/v1/guidance/NVDAperiod · metric · range · basis · change · SEC evidenceInvestment Strategies
Rules-based US-market strategies — Triple RSI, Daily RSI Mean Reversion, Momentum Breakout, Turn of the Month, Santa Claus Rally, Russell Rebalancing, Earnings Season and a Supertrend market-regime read. Live status, entry/exit, real backtested stats and the reasons behind each, on one key.
GET /api/strategiesstatus · entry · exit · rules · reasonsClean and effortless APIs
Build your first request in seconds. Leave the classification, validation and data wrangling to us.
/api/sentiment?ticker=NVDAimport requests
response = requests.get(
"https://raspberrytrades.com/api/sentiment",
headers={"x-api-key": "YOUR_API_KEY"},
params={"ticker": "NVDA"}
)
data = response.json()This interactive example never calls the live API or exposes current values.
From a question to usable context
No scraping stack, no spreadsheet cleanup and no model to maintain.
You ask
Call the API for any US ticker, or hit the influencer radar. One request, your key in the header.
We read & score
We pull the latest posts from X and an AI model reads each one — understanding sarcasm, news and context, not just keywords.
You get clean signal
Structured JSON back in moments: a sentiment summary, or the breakout setups the trusted traders are flagging today.
The people and systems that move on information
Raspberry fits the same clean data layer into discretionary trading, research and automated workflows.
Active traders
See what the trusted traders are setting up on today and gauge the mood on any ticker before you size in.
Funds & analysts
Add a social-sentiment factor to your process — an early read on narratives forming before they reach a terminal.
Developers & quants
One REST endpoint, one key, clean JSON. Drop sentiment and breakout signals straight into your models and bots.
Questions, answered
Where does the data come from?+
We read public posts from X (Twitter) in real time. When you request a ticker, we pull the latest relevant posts and analyze them on the spot.
How is sentiment calculated?+
An AI model (DeepSeek) reads the full text of each tweet and labels it bullish, bearish or neutral — understanding sarcasm, news and context. It is not keyword counting. The overall score is engagement-weighted.
Which stocks are covered?+
Any US-listed ticker, on demand. There's no fixed list — ask for a symbol and you get a fresh read.
What is the influencer breakout radar?+
A curated network of ~100 trusted stock & options traders on X. The radar surfaces the stocks they're flagging today as pullback or staircase breakout setups, ranked, with their actual tweets as the reason why.
How do I authenticate?+
Send your key in the x-api-key header on each request. One key gives you access to every endpoint.
Is this financial advice?+
No. Everything we provide is informational only and not investment advice. Sentiment and setups are algorithmic interpretations of public posts and can be wrong.