USE CASE SCENARIOS

PhD student Anna created a new optimizer and claimed +15% improvement. Seedgi Lab launched automatic validation with 15 runs, statistical tests, and benchmarks across different tasks. Real result: +2.3% ± 0.8% (statistical significance probability 0.03)—statistically significant, but honest. Paper accepted at NeurIPS conference thanks to correct methodology instead of inflated claims

Top-Tier Conference Publication

Machine learning engineer Dmitry from a fintech company spent 6 hours training models. Through quick smoke-test in one evening, tested 10 optimizers, selected top 3, and ran full validation on real data. Stochastic Gradient Descent with momentum value of 0.8 reduced time by 18% without quality loss (statistical probability 0.6). Savings: 1 hour compute per iteration, $500 monthly on infrastructure.

18% Production Model Acceleration

Alex is building a machine learning startup solo and didn't know where to start. Launched Seedgi Lab Web interface, uploaded data, selected "Quick experiment"—within 10 minutes received results with best optimizer recommendation (Adam). Exported model code and created working prototype in one evening instead of weeks of development.

From Idea to Working Prototype in One Evening

Clients who need this product

• Papers rejected due to weak statistics (single run or three runs only)
• Results cannot be reproduced by other researchers
• Weeks spent writing baseline code and statistical tests
• Reviewers demand correct statistical significance values and confidence intervals
• No time to set up experimental infrastructure
• Difficult to prove statistical significance of improvements

Academic Researchers

• New optimizer promised +20%, but delivered -5% in production
• Days wasted on manual hyperparameter tuning
• Models train too slowly—optimization needed
• No unified place to compare all experiments
• Inflated claims from research papers don't work on real data
• Difficult to explain return on investment from experiments to management

Production Machine Learning Engineers

• Don't know which optimizer to choose for my task
• My experiments are chaotic, no system
• No time to understand complex machine learning frameworks
• Want to quickly create working prototype without studying theory
• Unclear what really works versus what's just hype
• Limited budget for infrastructure and computing resources

Startups and Independent Developers

• Each researcher uses their own approach—impossible to compare results
• Students lose experiment results, duplicate each other's work
• No unified methodology standard in the team
• Difficult to track progress of multiple projects simultaneously
• Impossible to reproduce experiments conducted a year ago
• Chaos in storage and versioning of experiments

Artificial Intelligence Laboratory Leaders

95% Failures:

The Key to Success

Unlike traditional machine learning platforms that showcase only successes, Seedgi Lab honestly documents all failures—they comprise 95% of experiments. This isn't a flaw, but a revolutionary approach: systematic analysis of what DOESN'T work saves months of research. The platform automatically identifies inflated claims (for example, "+40% improvement" becomes realistic "+2.3% ± 0.8%"), ensures statistical significance (probability value less than 0.05) and complete reproducibility. The "Controlled Madness" philosophy means: test bold ideas, but with sober scientific assessment. This is real science, not a race for sensations. 

 Methodology & Testing 

Honest Methodology

Seedgi Lab enforces scientific correctness in experiments: minimum 15 runs for statistics, automatic calculation of statistical significance values and 95% confidence intervals, Bonferroni correction for multiple comparisons. The system prevents incorrect experiments, protecting against inflated claims and pseudoscience.

Systematic Testing

Platform for systematic validation of radical neural network optimization ideas. 25+ ready-to-use optimizers, automatic benchmarks across multiple tasks, documentation of all failures. Evolution from chaotic experiments to reproducible results through structured methodology and automatic validation.

SeedGi

Quantum Way 42

Innovation City, 12345