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QuotePlot Agent product image.
QuotePlot Agent product image.
The QuotePlot Agent page featuring stock list, stock chart, and chat panel.
AI

QuotePlot AI Agent

Decisions that used to sit behind manual research get an answer on the spot.

IndustryAI · Finance
UsersRetail Investors
PlatformWeb Application
TechPythonFastAPINext.js
DeploymentVercel + FastAPI service

Business Situation

Retail investors following volatile stocks, working across charting tools, news feeds, and forums to form a view before acting.

Operational Challenge

Answering one practical question — what is this stock doing right now, and does the movement matter — meant moving between three or four tools and interpreting the result yourself. Price charts show movement but not condition, and most analysis tools assume the reader already speaks their language.

Solution

QuotePlot Agent answers questions about a stock's status, condition, or trend in plain language, with live charts alongside. A classification pipeline evaluates market signals so each assessment is backed by a real model rather than generic text.

Business Impact

Research that meant assembling context from several sources returns a grounded answer on demand, with 86% classification accuracy on the underlying signals. Because the assessment comes from a model rather than free text, its behaviour can be measured against historical data and improved deliberately.

Workflow

User asks in plain language
Market data ingested
SVM pipeline classifies the signal
Agent grounds the answer
Chart and answer delivered

Features

Natural-language Q&A

Ask about any stock

Live Charts

Prices and trends

SVM Pipeline

86% classification accuracy

Real-time Data

Market API integrations

Grounded Agent

Answers backed by the model

Architecture

A Python FastAPI service hosts the intelligence layer: data ingestion from market APIs, the SVM classification pipeline, and the agent that translates natural-language questions into analyses. A Next.js frontend provides the stock list, charting, and chat interface. Separating the model service from the UI keeps the ML pipeline independently deployable and testable against historical data.

Client Applications

API & Business Logic

Data & Intelligence

Tap or hover a component to see its role in the system.

Available Customizations

Portfolio Tracking
Alerts & Watchlists
Backtesting
More Asset Classes
Sentiment Analysis

Is this suitable for your business?

This foundation is ideal for:

Retail investors
Trading communities
Financial content platforms
Fintech startups
Investment clubs

Foundation Coverage

Reusable modules from the Carlsson Studio foundation, combined with logic built for this domain.

Foundation Modules

  • Dashboard
  • Charts
  • Chat UI

Finance Modules

  • Stocks
  • Signals
  • Queries

AI Modules

  • SVM Classifier
  • NL Agent

Technical Highlights

Backend

PythonFastAPI

ML

SVM86% accuracy

Frontend

Next.js

Data

Market API integrations

Pattern

Model service + UI

Interested in something similar?

We can customize this foundation to match your own business workflow.

Start from this foundation