Unlock your software’s potential with Ozgar AI. Our virtual assistant simplifies navigation and management, empowering developers to tackle challenges confidently and efficiently.
Most legacy systems lack structured documentation and follow no consistent standards—making AI-based analysis challenging. Ozgar is engineered to ingest your system’s unstructured codebases using advanced semantic embedding and parsing techniques.
Our model is optimized specifically to:
By connecting directly to your data sources (source code, database catalog/schemas and system objects besides lots of other data sources as per case), Ozgar begins creating a meaningful, AI-ready knowledge foundation, fast!
Ozgar goes beyond just indexing code—it creates a living, dynamic knowledge hub tailored to your unique environment. It uses agentic AI techniques to continuously:
This knowledge hub becomes your team’s central source of truth—organized, always current, and ready to power everything from onboarding to audits.
Ozgar is built for developers, analysts, and system managers who are buried in technical debt and undocumented logic. It transforms their daily work by offering:
Everything is integrated into a unified workspace connected to your enterprise knowledge hub – saving time, reducing frustration, and helping your team move faster with fewer errors.
Ozgar AI offers a range of powerful features designed to enhance the software development experience.
Central repository for application data, including source code, metadata, and documentation.
AI-driven enrichment for summarization, categorization, and analysis.
Integrates source code, database metadata, operational logs, and technical documentation.
Connectors for seamless data ingestion from various inputs.
Intuitive workspace for managing data ingestion, configuring machine learning, and monitoring service performance.
Tools for user management and troubleshooting.
Visualizes application architecture, dependencies, and usage patterns.
Detailed insights on data flows, business rules, and performance metrics.
Identifies code and database improvement opportunities.
Provides actionable recommendations for optimizing performance and maintainability.
Central repository for application data, including source code, metadata, and documentation.
AI-driven enrichment for summarization, categorization, and analysis.