Neo - Autonomous AI Agent for Machine Learning, Data Science & Business Intelligence

Neo is a fully autonomous AI agent that brings machine learning and AI capabilities to everyone, from AI engineers and data scientists to business analysts, financial quants, and domain experts. Build, train, and deploy AI models directly from VS Code using natural language - no deep technical expertise required.

Who Neo is For

🤖 Gen AI & LLM Engineers: Build RAG systems, fine-tune latest models (Llama 3, Qwen, Gemma), deploy production LLM applications. 🎯 Data Scientists & ML Engineers: Train deep learning models, experiment with state-of-the-art architectures, build ML pipelines. 📊 Business Analysts: Generate insights, build predictive models, automate data analysis. 💼 Financial Analysts & Quants: Time series forecasting, risk modeling, algorithmic trading strategies. 🏥 Domain Experts (Healthcare, Legal, Marketing): Apply AI to your domain without coding expertise. 📈 Product Managers: Prototype ML features, validate hypotheses with data.

What Neo Can Do

🧠 Generative AI & LLM Applications

RAG Systems: Build question-answering systems with your company documents using Llama 3, Mistral, or GPT-4
Fine-tune Latest LLMs: Adapt Llama 3, Qwen 2.5, Gemma 2, Mistral, or Phi models to your data
LLM Agent Development: Create autonomous agents with tool use, memory, and reasoning capabilities
Chatbots & Assistants: Deploy customer service bots and internal knowledge assistants
Document Analysis: Summarize contracts, research papers, and reports with vision-language models
Content Generation: Generate marketing copy, reports, and product descriptions
Semantic Search: Build intelligent search using modern embedding models

🤖 Machine Learning & AI Development

Build ML Models: Create PyTorch, TensorFlow, and scikit-learn models from natural language
Train Deep Learning Models: End-to-end model training with automatic hyperparameter optimization
Modern Architectures: Work with Vision Transformers, Diffusion Models, and latest research
Model Evaluation: Compare models, generate metrics, create performance visualizations

💼 Business Intelligence & Analytics

Predictive Analytics: Forecast sales, customer churn, demand, and business KPIs
Customer Segmentation: Cluster analysis for marketing and customer insights
A/B Testing Analysis: Statistical testing and experiment evaluation
Business Dashboards: Generate insights and visualizations from your business data
Automated Reporting: Create recurring analysis reports with ML-powered insights

💹 Financial Analysis & Quantitative Finance

Time Series Forecasting: Predict stock prices, currency rates, and market trends using Transformers, LSTM, or Prophet
Risk Modeling: Build VaR, credit risk, and portfolio risk models
Algorithmic Trading: Develop and backtest trading strategies with ML
Financial Statement Analysis: Automate ratio analysis and financial health scoring
Fraud Detection: Anomaly detection for transaction monitoring
Portfolio Optimization: Modern portfolio theory with ML enhancements

📊 Data Science & Analysis

Exploratory Data Analysis (EDA): Automatic insights, visualizations, statistical summaries
Data Preprocessing: Clean, transform, and prepare datasets
Feature Engineering: Create predictive features from raw data
Statistical Modeling: Regression, hypothesis testing, causal inference
Data Pipelines: ETL workflows for data ingestion and processing

👁️ Computer Vision

Image Classification: Product categorization, quality control, medical imaging
Object Detection: Inventory tracking, defect detection, security monitoring
OCR & Document Processing: Extract text from invoices, forms, receipts
Face Recognition: Identity verification, attendance systems

🎤 Speech & Audio AI

Speech-to-Text: Transcribe meetings, calls, interviews
Sentiment Analysis: Analyze customer call sentiment
Text-to-Speech: Voice notifications, audiobook generation
Audio Classification: Sound event detection, music genre classification

🔬 Experiment & Research Management

MLOps Integration: Track experiments with Weights & Biases, MLflow, TensorBoard
A/B Testing: Design and analyze experiments
Model Comparison: Benchmark multiple approaches systematically
Reproducibility: Generate shareable, reproducible analyses

☁️ Cloud Integration

Neo connects to your cloud services:

AWS S3: Load datasets and save models
Weights & Biases: Track ML experiments and metrics
HuggingFace Hub: Access pre-trained models
Kaggle: Use competition datasets

Quick Start

Install Neo from VS Code marketplace
Click the Neo icon in the sidebar
Click Login with your Neo account
Optionally configure cloud integrations (AWS, W&B, HuggingFace, Kaggle)

New to Neo? Sign up free at heyneo.so

2. Tell Neo What You Want to Build

Use natural language to describe your goal, Neo handles the technical implementation:

For Business Analysts:

"Analyze my sales data, identify trends, and predict next quarter revenue"

"Build a customer churn prediction model using my CRM data"

"Create a customer segmentation model and visualize the segments"

"Analyze A/B test results and determine statistical significance"

"Generate a weekly automated report with key business metrics"

For Financial Analysts & Quants:

"Forecast stock prices using LSTM with my historical data from S3"

"Build a portfolio optimization model with Sharpe ratio maximization"

"Create a credit risk scoring model using logistic regression"

"Backtest a moving average crossover strategy on crypto data"

"Build a VaR model for my portfolio and calculate risk metrics"

"Detect anomalies in transaction data for fraud detection"

For ML Engineers & Data Scientists:

"Fine-tune Llama 3 for sentiment analysis on customer reviews"

"Build YOLOv8 object detection for warehouse inventory images"

"Create a RAG system using Pinecone with Qwen embeddings"

"Train a PyTorch Vision Transformer with custom attention mechanism"

"Compare ViT vs ConvNeXt on my image classification task"

For Domain Experts (Healthcare, Legal, Marketing):

"Analyze patient readmission patterns and build a prediction model"

"Extract key clauses from legal contracts using NLP"

"Predict customer lifetime value from marketing campaign data"

"Classify medical images for disease detection"

"Summarize research papers and extract key findings"

For Product Managers:

"Build a recommendation engine prototype for my product catalog"

"Analyze user feedback sentiment and categorize feature requests"

"Predict user retention based on onboarding behavior"

"Create a content moderation classifier for user-generated content"

3. Watch Neo Work Autonomously

Neo operates as a fully autonomous agent:

Understands your business goal and breaks it into technical steps
Writes production-ready Python code (no coding required from you)
Installs required packages automatically
Runs analysis and training scripts
Generates insights, visualizations, and reports
Handles cloud operations (upload/download data and models)

You maintain full control: Pause, review, or stop at any time. No black box: See exactly what Neo is doing.

Key Features

🚀 Autonomous Workflow Execution

Describe what you want in plain English. Neo handles the technical implementation. No need to know PyTorch, TensorFlow, or ML algorithms.

💻 Local & Secure

All code runs locally in your workspace. Your data, models, and credentials stay on your machine. Full transparency.

📦 Framework & Library Support

Works with industry-standard tools:

ML/DL: PyTorch, TensorFlow, scikit-learn, XGBoost, LightGBM
Data Analysis: pandas, NumPy, statsmodels, scipy
Visualization: matplotlib, seaborn, plotly
NLP: Hugging Face Transformers, spaCy, NLTK
Computer Vision: OpenCV, torchvision, PIL
LLM Frameworks: LangChain, LlamaIndex
Finance: QuantLib, zipline, backtrader, yfinance

🔄 Full Context Awareness

Neo understands your data structure, existing code, and project context. Works with CSV, Excel, SQL databases, APIs, and cloud storage.

📈 Real-Time Progress

Monitor progress while Neo works: see current tasks, training metrics, and logs in real-time.

🔐 Secure Credential Management

Store AWS, Weights & Biases, HuggingFace, and Kaggle credentials securely using VS Code's encrypted storage.

💬 Conversational Interface

Ask follow-up questions, request modifications, or get explanations. Neo maintains context throughout the conversation.

Use Cases by Role

📊 Business Analysts

Predictive analytics for revenue, churn, demand forecasting
Customer segmentation and cohort analysis
Marketing campaign performance analysis
Automated reporting and dashboards
Statistical hypothesis testing

💼 Financial Analysts & Quants

Time series forecasting (Temporal Fusion Transformers, LSTM, Prophet, ARIMA)
Risk modeling and portfolio optimization
Algorithmic trading strategy development
Financial statement analysis and ratio calculations
Fraud detection and anomaly detection
Credit scoring models

🎯 Marketing & Sales

Customer lifetime value prediction
Lead scoring and conversion prediction
Sentiment analysis from customer feedback
Recommendation engines
Market basket analysis

🏥 Healthcare & Life Sciences

Patient risk prediction and readmission modeling
Medical image classification
Clinical trial data analysis
Drug discovery data processing
Electronic health record (EHR) analysis

🎓 Researchers & Academics

Reproduce ML research papers
Run comparative experiments
Statistical analysis for publications
Data processing for research
Create reproducible analysis pipelines

🏗️ Product & Engineering Teams

Prototype ML features quickly
Integrate LLMs into applications
Build recommendation systems
Implement search and ranking algorithms
Create data-driven features

Commands

Open Command Palette (Cmd+Shift+P / Ctrl+Shift+P):

Neo: Login - Authenticate with Neo
Neo: Logout - Sign out
Neo: Start New Chat - Begin new project
Neo: Chat History - Resume previous projects
Neo: Open Chat Sidebar - Open Neo sidebar
Neo: Terminate Chat - Stop execution

Cloud Integrations

Connect your private datasets and production tools directly from Neo's integrations panel (Settings → Integrations in Neo sidebar). These integrations enable Neo to seamlessly access your proprietary data, track experiments, and deploy models without manual file transfers—critical for enterprise workflows, fine-tuning on private documents, and production ML pipelines.

AWS S3: Load private datasets and save trained models to your secure cloud storage
Weights & Biases: Track experiments, compare model performance, and collaborate with your team
HuggingFace: Access 500K+ pre-trained models and deploy fine-tuned models to the Hub
Kaggle: Import competition datasets and benchmark against public leaderboards

Requirements

VS Code: 1.85.0 or higher
Python: 3.8+ (installed automatically if needed)
Internet: Required for AI inference
Neo Account: Free at heyneo.so

Privacy & Security

✅ Local Execution: Code and data stay on your machine
✅ Encrypted Storage: Credentials encrypted with VS Code SecretStorage
✅ Workspace Isolation: Operations restricted to your project
✅ Full Transparency: All actions logged and visible
✅ User Control: Pause, resume, or stop anytime

Example Workflows

Business: Sales Forecasting

"Load my sales_data.csv, perform time series decomposition,
build ARIMA and LSTM forecasts, compare accuracy,
create visualization showing historical and predicted sales"

Finance: Portfolio Optimization

"Load stock prices for AAPL, GOOGL, MSFT from Yahoo Finance,
calculate returns and covariance matrix, optimize portfolio
for maximum Sharpe ratio, show efficient frontier plot"

ML: Customer Churn Prediction

"Load customer data from S3, perform EDA, handle missing values,
create features, train XGBoost and Random Forest models,
compare performance, show feature importance, generate predictions"

NLP: Document Analysis

"Load PDF documents from ./contracts folder, extract text,
summarize key terms, identify clauses, create comparison table,
save results to Excel"

Computer Vision: Quality Control

"Load product images, train image classifier to detect defects,
use transfer learning with Vision Transformer, evaluate on test set,
generate confusion matrix and misclassification report"

Troubleshooting

Neo not responding?

Check View → Output → Neo Agent for errors
Verify internet connection
Resume from Chat History if interrupted

Package installation fails?

Ensure Python 3.8+ is installed
Check pip is accessible from terminal
Verify disk space availability

Cloud integration errors?

Verify credentials in Settings → Integrations
Test connection before running workflows
Check firewall/proxy settings

Data loading issues?

Ensure file paths are correct
Check file permissions
Verify data format (CSV, Excel, JSON, etc.)

Need help or want to report an issue?

In-app feedback: Click Settings in Neo sidebar → Send Feedback
Email support: support@heyneo.so

Keywords

Machine Learning, AI Agent, Data Science, Business Intelligence, Predictive Analytics, Financial Modeling, Time Series Forecasting, Deep Learning, LLM, Fine-tuning, Model Training, Computer Vision, NLP, Natural Language Processing, RAG, Retrieval Augmented Generation, Generative AI, Gen AI, PyTorch, TensorFlow, scikit-learn, Hugging Face, MLOps, Customer Analytics, Churn Prediction, Sales Forecasting, Portfolio Optimization, Risk Modeling, Algorithmic Trading, Quantitative Finance, Python, Data Analysis, Exploratory Data Analysis, Statistical Modeling, Business Analytics, Marketing Analytics, Customer Segmentation, A/B Testing, Automated Machine Learning, AutoML, Neural Networks, Transformers, BERT, GPT, Speech Recognition, Text to Speech, Image Classification, Object Detection, Sentiment Analysis, LangChain, Data Visualization

Support

Need help? We're here for you!

💬 In-App Feedback: Click Settings in Neo sidebar → Send Feedback (bug reports, feature requests, questions)
💌 Email Support: support@heyneo.so
🌐 Website: heyneo.so

License

AI-powered workflows for everyone. From AI engineers to data analysts ❤️

Neo - AI Agent for ML, Data Science & Business Analytics

Neo Research Inc.