Code That Cleans Itself.
Introducing pyroSuggest v1.0. We aren't just flagging errors; we are integrating deep learning into the compile phase to automate complex optimizations and provide predictive refactoring insights.
Integration Intelligence
Moving beyond static analysis. Our integration engine understands context, intent, and historical patterns.
Context-Aware Refactoring
Our LSTM models ingest your repository's commit history to learn your team's unique styling conventions. The result is refactoring suggestions that look like they were written by your senior lead—maintaining consistency while reducing technical debt.
- > Adapts to custom lint rules
- > Preserves comment efficacy
- > Reduces lines of code by avg 14%
Predictive Anomaly Detection
Stop fighting fires. Start preventing arson. By analyzing millions of production-breaking commits across the open-source ecosystem, the PyroCode engine flags logic patterns known to cause memory leaks or race conditions before they merge to main.
CI/CD Build Guardians
Integrate standard deviation thresholds into your Xcode Cloud or Jenkins pipelines. We automatically fail builds that introduce statistically significant performance regressions in compile time or binary size, forcing immediate optimization.
Evolution of Cleanliness
Why upgrading to PyroCode AI unlocks new velocity.
TRADITIONAL
Dependent on static, pre-defined rule sets (Regex matching).
PYROCODE AI
Dynamic pattern recognition capable of understanding semantic intent.
TRADITIONAL
Reactive: Identifies unused assets after they are created.
PYROCODE AI
Proactive: Suggests resource consolidation during the PR process.
TRADITIONAL
Generic suggestions ("Function too long").
PYROCODE AI
Personalized Refactoring: "Split this function based on the Single Responsibility Principle, moving data parsing to `DataParser.swift`."
TRADITIONAL
High manual review effort.
PYROCODE AI
Automated Confidence: Auto-merge for low-risk optimizations.
Portland R&D Division
// MEET THE ARCHITECTS
Dr. Eleanor Vance
PhD, COMPUTATIONAL LINGUISTICS
"We aren't trying to replace the developer. We are trying to replace the toil. If AI can handle the memory management, you can focus on the architecture."
Marcus Thorne
SENIOR MACHINE LEARNING OPS
"Training our models specifically on clean, optimized Xcode projects allows us to achieve a false-positive rate of less than 0.1%."
Join the Beta Program
Experience pyroSuggest before the public release. Currently optimizing for teams of 5+.