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Q3 revenue review

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Analyze AAPL performance from my portfolio database

Based on your connected PostgreSQL database, here's the analysis for AAPL: Apple Inc. (AAPL) — Performance SummaryKey metrics from your portfolio database:

AAPL

Revenue flow analysisFY24 segment → income · $ in B

$391B+2.0% YoY

portfolio_db → revenue_segments

Key insights:

1. Strong upward momentum - AAPL gained +12.4% over the last 30 days, outperforming the S&P 500 by 8.2 percentage points
2. Revenue beat expectations - Q3 revenue of $94.9B exceeded analyst consensus of $89.3B — a 6.3% surprise driven by Services and iPhone segments
3. Institutional accumulation - Net institutional buying increased by 2.1M shares this quarter, with Vanguard and BlackRock adding to positions
4. Technical breakout confirmed - Price broke above the 200-day moving average with volume 2.3x the 20-day average — a historically bullish signal

Ask your data anything...

Attach DB

BusinessBusinessteamsteamscan'tcan'tqueryquerydatabases.databases.EngineersEngineersdon'tdon'tknowknowthethebusinessbusinesscontext.context.ChatPlotDBChatPlotDBbridgesbridgesthatthatgapgap——nonoSQLSQLrequired.required.

Close the gap between data and decisions. The people who understand the business can't query the database. The developers who write SQL don't understand the business problem. ChatPlotDB bridges that divide.

Every insight used to require a ticket. A conversation, a wait. ChatPlotDB connects directly to your databases worldwide — no intermediaries, no delays.

Works with your existing stack. PostgreSQL, MySQL, DynamoDB, plus CSV and Excel uploads. Our AI translates business questions into optimized queries — instantly.

Ask questions in plain English. Get answers from your actual data. No SQL. No waiting. No lost context between what you need and what you get.

No lost context between teams. Every insight shows its source queries and data lineage. Business teams and developers finally speak the same language.

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For you.

We're building AI-powered tools that help teams query databases, visualize data, and make faster decisions — without writing SQL.

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Build executive dashboard

Forecast Q2 revenue

Find churn risk customers

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Chat with your database.

In plain English.

Connect PostgreSQL, MySQL, or any supported database and ask questions in natural language. ChatPlotDB translates your questions into optimized SQL, runs the query, and returns results as tables or visualizations.

Deploy AI

Ask questions in plain English, connect your database with ChatPlotDB, or put AI agents to work on complex tasks like data analysis and reporting.

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New question asked

Analyze sales trends

How are sales trending this quarter?

+18% QoQ growth across products

Find top customers

Who are our highest revenue customers?

Acme, Globex, Initech, Soylent

Detect anomalies

Any unusual patterns in orders?

5 spikes detected in last 30 days

Show me top 10 customers by revenue this quarter

SELECT * FROM customers ORDER BY revenue DESC LIMIT 10

Every query makes it smarter.

Continuously.

ChatPlotDB learns from every interaction. Our feedback loop captures query patterns, corrects errors, and refines accuracy — so the system that serves your 1000th query is fundamentally better than the one that served your first.

Feedback Loop

Every interaction improves accuracy. Our system captures query patterns, corrects errors, and refines results continuously.

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Analyze CSVs and Excel files.

Instantly.

Don't have a database? Upload a CSV or Excel file and start exploring. ChatPlotDB ingests the file, understands the structure, and lets you query it conversationally — no data pipeline needed.

File Analysis

Upload a CSV or Excel file and start exploring. ChatPlotDB ingests the file, understands the structure, and lets you query it conversationally.

Try it out

30D

12M

All

Apr - Jun

Jul - Sep

CSV

Excel

JSON

2.8M

2.4M

2.0M

1.6M

1.2M

0.8M

0.4M

July

August

September

Excel files

TimeJuly 2024

Rows1,920,240

Maya Patel

6:32 pm

I uploaded our Q3 sales CSV — 48k rows across 12 product categories. Could you pull out the top performers, flag any month-over-month declines, and tell me which regions are driving most of the growth this quarter?

Summarize

Q3 sales recap: surface top-performing categories, flag month-over-month declines, and highlight regions driving the most growth across 48k rows.

Brief

Details

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Query your data from Slack.

Where work happens.

Bring ChatPlotDB into your team's workflow. Ask data questions directly in Slack channels, share results with your team, and keep insights where the conversations happen.

Slack Integration

Bring ChatPlotDB into your team's workflow. Ask data questions directly in Slack channels and share results with your team.

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PostgreSQL

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Queries

Standard

12,847Records

Reports

Standard

4,291Records

Insights

Standard

8,634Records

/query revenue by region last quarter

Thinking for 2s

1 / 3 tasks done

1Connect to PostgreSQL
Run SQL query
Generate chart in Slack

Queried sales_by_region view

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ChatPlotDB turns natural language into production-grade analytics — connect your database and start asking questions.

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