What's New
Product updates, improvements and fixes across the KlickAnalytics platform.
Introducing KlickAnalytics for Slack
Market intelligence can now move directly into the conversations where your team already works.
With the new KlickAnalytics Slack integration, users can run KA commands from Slack and receive structured market data and analytics without leaving the channel.
Use commands such as:
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ka quote TSLAfor the latest quote and trading data -
ka ta MSFTfor technical indicators and market signals -
Additional KA commands for prices, fundamentals, analytics, and research workflows
KlickAnalytics first returns the result privately, allowing you to review it before deciding whether to share it with the channel. This keeps exploratory queries out of the wider conversation while making important findings easy to distribute when ready.
With KlickAnalytics for Slack, teams can:
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Run KA commands from a Slack conversation
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Retrieve quotes and market statistics
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Review technical analysis and indicators
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Receive structured, readable results
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Keep initial results visible only to the requesting user
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Share selected findings with the complete channel
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Discuss market intelligen
Ask the market a question. Get a calculated answer.
The AI is not a chatbot bolted onto a document store. It calls the same analytics engine that powers every screen on this platform — so what comes back is a number it computed from raw history, with the command that produced it.
86,000+ instruments
Global equities, ETFs, funds, options, FX, commodities, crypto, economics, filings, transcripts and news — one normalised symbol universe with adjusted history.
A real analytics engine
Screening, backtesting, technicals, options analytics, correlations, seasonality and factor models — computed on demand from raw prices, never a stale cache.
It shows its working
Answers arrive with the charts, tables and tool calls behind them, so you can check the number instead of trusting a paraphrase.
Your own documents
Upload filings, decks and research. Ask across them and the answer cites the page it came from.
Agents and workflows
Multi-step research that runs the platform's tools for you — screen, pull the history, compute, compare, then write it up.
MCP, CLI and API
The same command catalogue from Claude, your own agent, a shell or your pipeline. The answer on screen is the answer your job gets at 4am.
You ask
“How does NVDA usually trade through earnings?”
It calls
→ ka.options_expected_move(NVDA)
It answers
NVDA has averaged a 9.2% absolute move on the day after earnings and closed higher 67% of the time. Two in three reactions land between −4.2% and +16.3% — the distribution is skewed right, not symmetric.
Every figure computed live from our own history — not scraped, not summarised.
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