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AI Infrastructure
Google's Gemini gives our agents something no other AI model offers at this scale: the ability to hold an entire codebase, all its documentation, and visual designs in context simultaneously. One million tokens. Zero fragmentation.
The Advantage
Context is not a spec sheet number. It is the difference between an AI that understands your file and an AI that understands your system. Here is why that distinction changes everything.
Most AI models see individual files. Gemini sees your entire project -- every file, every dependency, every configuration -- simultaneously. This eliminates hallucinated imports, missed dependencies, and context-blind suggestions.
When you rename a type, restructure a module, or refactor an API, Gemini understands the ripple effects across hundreds of files. Every import, every reference, every test that needs updating is identified in a single pass.
Smaller context windows force AI to process code in fragments, losing architectural understanding at every boundary. Gemini holds the full picture from start to finish, producing coherent changes that respect your entire system design.
Use Cases
Gemini is not a replacement for Claude Code. It is a force multiplier. We use it where massive context and multi-modal understanding make the difference between good output and transformative output.
Feed an entire repository into a single review session. Gemini analyzes architectural patterns, identifies inconsistencies across modules, flags security vulnerabilities, and surfaces dead code -- not file by file, but as a holistic assessment of your entire codebase.
Catches issues that file-level reviewers miss entirely
Technical specifications, regulatory documents, and research papers that span hundreds of pages are processed in full. Gemini extracts requirements, identifies contradictions, and synthesizes actionable summaries without losing critical details buried on page 247.
From 200-page spec to structured requirements in minutes
Gemini processes screenshots, design mockups, architecture diagrams, and whiteboard sketches alongside text. Show it a Figma design and your current codebase, and it generates the exact components needed to match the design -- pixel aware and context aware.
Design-to-code with visual and structural understanding
With full project context -- existing code, documentation, dependencies, deployment configuration -- Gemini produces migration plans, refactoring strategies, and technical roadmaps that account for every constraint in your system.
Plans that account for your actual codebase, not generic advice
Integration
Gemini is integrated into our agent pipeline at specific high-value points where large context and multi-modal processing produce measurably better results than alternatives.
Your entire repository is loaded into Gemini's context window. Source files, configuration, documentation, test suites, and dependency manifests. Nothing is excluded, nothing is summarized.
Gemini processes the full context to build an internal model of your architecture. It understands data flow, component relationships, API contracts, and testing patterns across your entire project.
Design files, screenshots, and diagrams are processed alongside code. Gemini identifies gaps between your current implementation and target design, flagging missing components and style inconsistencies.
Analysis results feed directly into Claude Code for execution. Refactoring plans become implemented changes. Code review findings become fixed issues. Design gaps become built components.
Capabilities
When your AI can hold your entire project in context, the quality of every decision -- from architecture to implementation -- improves fundamentally.
1M+ token context window for entire repository analysis
Multi-modal processing of code, images, and documents
Cross-file dependency tracking and impact analysis
Architecture-aware refactoring recommendations
Design-to-code translation from screenshots and mockups
Regulatory document parsing and compliance checking
Technical debt identification across full codebases
Migration planning with complete dependency awareness
30 minutes. No commitment. Walk us through your project and we will show you what large-context AI processing can do for your specific codebase.
Bring your most complex project. The bigger the context, the more impressive the results.