Accelerate data science workflows 100x while keeping your proprietary data completely secure and private. Unlike code copilots, Voitta understands your entire analytical workflow—from data exploration to production deployment.
In Finnish, "voitta" means to win, to defeat, and to overcome.
Reduce time-to-insight from weeks to hours—complete data science projects in a fraction of the time
Your proprietary data never leaves your infrastructure. Use your own enterprise LLM keys
Unlike code copilots, handles the entire data science lifecycle—not just code completion
GitHub Copilot and similar tools only autocomplete code. They don't understand your data, can't run analyses, won't generate visualizations, and offer no insights into your results. You're still doing 90% of the work manually.
Your PhD-level data scientists waste time on data cleaning, debugging pandas code, tweaking matplotlib parameters, and wrestling with infrastructure instead of extracting insights and building models.
Generic AI tools send your proprietary data to third-party servers. Enterprises need solutions that keep sensitive data completely private while still leveraging AI capabilities.
Data scientists juggle Jupyter notebooks, SQL clients, BI tools, statistical packages, and visualization libraries. Context switching between these tools destroys flow state and productivity.
Voitta isn't a code copilot—it's an intelligent assistant that understands your entire data science workflow. Describe what you want in natural language, and Voitta handles everything from data loading to final visualization.
import pandas as pd
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
# Load and clean data
df = pd.read_csv('portfolio_data.csv')
df['returns'] = df['price'].pct_change()
df = df.dropna()
# Calculate VaR
confidence_level = 0.05
var_95 = np.percentile(
df['returns'],
confidence_level * 100
)
expected_shortfall = df[
df['returns'] <= var_95
]['returns'].mean()
# Create visualization
plt.figure(figsize=(12, 8))
plt.hist(
df['returns'],
bins=50,
alpha=0.7,
density=True
)
plt.axvline(
var_95,
color='red',
linestyle='--',
label=f'95% VaR: {var_95:.4f}'
)
plt.title('Portfolio Returns Distribution')
plt.legend()
plt.show()Problem: You still write all this code, debug errors, tweak parameters, and manually interpret results. Copilots only autocomplete—they don't understand your data or generate insights.
"Analyze portfolio returns from the CSV file, calculate 95% VaR with expected shortfall, and create a publication-quality distribution plot with the VaR threshold highlighted."
Your proprietary data is your competitive advantage. Voitta keeps it completely secure.
Your data never leaves your infrastructure. On-premise deployment or private VPC ensures complete data sovereignty. No data is ever sent to external servers or used for model training.
Use your enterprise LLM API keys (OpenAI, Anthropic Claude, Azure, Google, AWS Bedrock, or self-hosted models). Full transparency and control over which AI models access your workflows—never your raw data.
Built for regulated industries. Supports SOC 2, HIPAA, GDPR, and financial services compliance requirements. Complete audit trails, SSO integration, and role-based access control.
For maximum security environments, deploy Voitta completely air-gapped with local LLM models. No internet connectivity required—all processing happens on your infrastructure.
Code copilots like GitHub Copilot, Cursor, and Codeium are great for autocompleting code. But data science requires much more than code completion.
| Capability | Code Copilots (GitHub Copilot, Cursor) | Voitta |
|---|---|---|
| Code Completion | ✅ Excellent | ✅ Excellent |
| Understands Your Data | ❌ No data awareness | ✅ Analyzes schemas, distributions, relationships |
| Executes Code | ❌ Suggests only—you run manually | ✅ Runs analyses automatically with error handling |
| Generates Visualizations | ❌ You tweak matplotlib manually | ✅ Creates publication-ready plots automatically |
| Provides Statistical Insights | ❌ No interpretation of results | ✅ Explains findings and suggests next steps |
| Iterative Analysis | ❌ Each prompt starts fresh | ✅ Maintains context across entire workflow |
| Data Pipeline Integration | ❌ No data source connectivity | ✅ Connects to S3, Snowflake, SQL, APIs, HPC clusters |
| Model Validation | ❌ No statistical validation | ✅ Validates assumptions and tests hypotheses |
| Collaborative Workflows | ❌ Individual suggestions only | ✅ Shared workspaces with version control |
| Enterprise Data Security | ⚠️ Code sent to cloud servers | ✅ On-premise deployment, zero data leakage |
Code copilots are text editors with autocomplete. Voitta is an intelligent data science partner that understands your data, runs analyses, generates insights, and handles the entire workflow from hypothesis to publication-ready results.
Think of it this way: A code copilot is like spell-check for code. Voitta is like having a senior data scientist working alongside you 24/7.
Created by practitioners who've lived the pain of slow, fragmented workflows. We understand the complete data science lifecycle because we are data scientists.
Designed from day one for enterprise security requirements. Your data stays on your infrastructure, encrypted and protected.
Not an exaggeration—complete in hours what used to take weeks. Real customers report 50-100x acceleration in time-to-insight.
Unlike copilots that just suggest code, Voitta understands context, runs analyses, validates results, and provides actionable insights.
Cloud, on-premise, VPC, or air-gapped. Deploy Voitta wherever your data lives with whatever LLM provider you prefer.
Fast deployment and immediate productivity gains mean you see ROI within the first month, not quarters.
45-minute personalized demonstration with your technical stakeholders. We'll show Voitta working on your actual use cases (using sample data).
30-60 day structured pilot with your data science team:
Based on pilot results, develop phased rollout strategy across your data science organization with full support and training.
Or try Voitta now (individual users)