The Starting Point
CodePilot (name changed) is a 12-person startup building an AI-powered code review tool. Their product ingests pull requests, sends the changed files to Claude Sonnet 4.6 for analysis, and returns actionable feedback to developers. By March 2026, they were processing 800 pull requests per day across 47 enterprise customers.
The Cost Breakdown
Each pull request averaged 35,000 characters of changed code across 8 files. At roughly 10,000 text tokens per PR, and with Claude Sonnet 4.6 priced at $3 per million input tokens, each review cost $0.03 in input tokens plus $0.05 in output tokens. At 800 PRs per day, input costs alone hit $720/month — and total API spending reached $4,200/month.
The Integration
The team integrated pxpipe into their preprocessing pipeline. Before sending code to Claude, the changed files are concatenated with diff headers and rendered into dense PNGs. The average PR now consumes 1,200 image tokens instead of 10,000 text tokens — an 88% reduction in input costs.
The Results
Monthly input token costs dropped from $720 to $86. Total API spending dropped from $4,200 to $490. The quality of Claude's code reviews remained identical in blind A/B testing across 200 PRs. Review latency decreased slightly because Claude processes fewer input tokens faster.
Lessons Learned
The team discovered that visual encoding works best for files over 2,000 characters. For small files (under 500 characters), the image tile overhead makes text cheaper. They implemented a hybrid approach: files under 2,000 characters go as text, everything larger goes as images.
Frequently Asked Questions
Conclusion
Visual token encoding is a practical, immediately deployable optimization that works with your existing AI stack. Whether you are a developer building pipelines or a founder managing API budgets, the ~88% input cost reduction compounds into real savings that improve your margins and extend your runway.
Ready to try it? Open PXINK and drop a file to see your savings instantly.