Live streaming quotes
WebSocket price feed for US equities, production-grade.
- COVERAGE
- All US equities
- STREAM
- WebSocket · ~1s bars
- HISTORY
- Daily, back to IPO
NVDA142.66 ▲
— of 20 markets open · live
Give it the question.
It does the analyst's whole day.
Ask for a DCF, a competitive teardown, an earnings post-mortem — and it writes the code, pulls the filings, builds the model, and hands you the memo. Not a summary of the work. The work.
Open Pre-open Closed
01 · YOUR ANALYST TEAM, IN PARALLELDecompose. Parallelize.
Where it all lands ↗Decompose. Parallelize.
Deliver — with you in the loop.
A whole research team thrown at one task — specialized agents working the data, the filings, and the valuation at once, then reassembled into a finished model, memo, and charts. Every step yours to steer.
02 · THE DATA, BUILT FOR AGENT ACCESSEvery input that moves a stock,
Every input that moves a stock,
wired for the agent to reach.
Prices and fundamentals, macro and the rates curve, institutional ownership and insider flow, earnings-call transcripts, SEC filings, options, news with sentiment — even web-scraped alt-data. The whole surface within the agent's reach, every pull cited back to source.
03 · WHATEVER FORMAT YOU NEEDHowever you need to ship it.
However you need to ship it.
Memo, model, deck, dashboard.
It ships a DOCX memo. Models the numbers in XLSX. Builds a PPTX deck. Lays out a PDF report. Wires a live dashboard. Renders finished charts and figures. Production-grade, in whatever format the moment calls for.
.docxNarrative write-up — headings, prose, inline citations.
memo.docx
04 · YOUR WORKSPACE, YOUR CONTEXTNot a chat window.
Not a chat window.
A desk that compounds.
Your profile, the agent's notes, its memory, and every file it builds persist in one environment you own — so it picks up with full context, not a blank slate.Select any part to see what it is.
Workspace
Context assembled · this turn
- Your profile, the agent's notes & both memory layers — in full
- Every file in
work/andresults/, plus prior threads - Your uploaded research library — summarized and indexed
Reasoning with the whole workspace in context. No re-briefing, ever.
Read on every turn
The agent's notes and memory are assembled into its context on every model call — it always knows the goal and the history, with no re-briefing.
Scoped & persistent
Work and memory stay with the project; your profile and user memory follow you across every workspace. Files survive sandbox restarts.
Compounds
It writes findings back into agent.md and memory, and keeps every file in work/ — so the next task starts ahead.
05 · SCHEDULED, OR TRIGGEREDOn your schedule.
On your schedule.
And on the market's.
A 7am brief before the open, a pre-earnings deep-dive the night before — and price or event triggers that fire mid-session. Each one runs the whole analysis end to end and lands with the answer, not a ping.
Automations5 active, 1 paused
NameScheduleModeNext runStatus
NVDA price alertActive
Morning Market BriefingActive
Weekly Portfolio ReviewActive
TSLA intraday momentumActive
CRWD Q1 Pre-EarningsActive
CPI release recapPaused
SNOW Q1 earnings recap Completed
06 · IT JOINS THE TOOLS YOU ALREADY USEAlready live in Slack?
Already live in Slack?
Your analyst moves in too.
Add LangAlpha to the Slack, Discord, Telegram, or Feishu workspace your team already runs on — and get finished analysis back, charts and memo included, without leaving the conversation.
Connect a channel ↗
FAQ
Questions, answered.
Chat answers from memory and stops. This agent does the work — it writes and runs real code in a sandbox against live market data and SEC filings, keeps a workspace that holds your context, and fans out subagents in parallel. You get analysis you can open, rerun, and audit, not a plausible-sounding guess.
Every figure traces back to the code that produced it and the source it came from. The agent leaves its scripts, its data pulls, and inline citations — to the exact filing or quote behind each claim — open to inspect. You verify the work instead of trusting a black box.
Live US equity quotes, fundamentals, options chains, the full Treasury curve and macro series, and news with sentiment — plus SEC EDGAR filings the agent reads in full: the actual 10-K, 10-Q, and 8-K, not a summary. Global names come in through its data providers, every pull cited to source.
We don't use your conversations to train AI models, and we don't sell your data. LangAlpha does not connect to your bank or brokerage — it works from market data and filings, not your accounts. So share as much as you like — the more it knows about you and your book, the sharper its work, and it all stays yours. Need airtight confidentiality? Self-host, and nothing leaves your own infrastructure.
Only when you let it. It proposes a plan before heavy work — approve, reject, or rewrite it — asks clarifying questions mid-run, and lets you steer any subagent while it works. And it never trades on its own: LangAlpha prepares the analysis and runs the research you schedule, and the call to act stays yours.
Yes. The core agent is open source under Apache 2.0 and runs in your own VPC with a Docker-based sandbox. Bring your own model and data keys; per-workspace secrets stay in an encrypted vault, read only at execution time — your data, your keys, your network boundary.
Start free on the hosted platform — paid plans add higher limits and lift the daily cap. Prefer your own model subscriptions? Bring your own keys (Claude, GPT, Gemini, or others) and pay your provider directly. Or self-host: the core agent is open source on GitHub, running entirely on your own keys and infrastructure.
Give it your hardest question.
Judge the answer yourself.
Hand it the analysis you've been avoiding — the model, the deep-dive, the screen — and see what comes back. Free to run for research, or self-host on your keys.