Side-by-side comparison of AI visibility scores, market position, and capabilities
SF AI document parsing API processing 1B+ pages monthly at 20%+ higher accuracy than AWS/Google/Microsoft; $108M total ($75M a16z Series B Oct 2025) serving Scale AI, Harvey, and Fortune 10 for enterprise document intelligence.
Reducto is a San Francisco-based AI document intelligence company — backed by $108 million in total funding including a $75 million Series B led by Andreessen Horowitz in October 2025, plus a $24.5 million Series A from Benchmark in April 2025 and an $8.4 million seed from First Round Capital, Y Combinator, BoxGroup, SV Angel, and Liquid2 in October 2024 — providing enterprises and AI development teams with the most accurate document parsing API available for extracting structured data from PDFs, scanned documents, spreadsheets, and unstructured files at human-level reading accuracy. Reducto processes over one billion pages monthly for thousands of customers including Scale AI, Harvey, Rogo, Fortune 10 enterprises, global financial institutions, and Big Four accounting firms — delivering 20%+ higher extraction accuracy than AWS Textract, Google Document AI, and Microsoft Azure Form Recognizer.
SF cloud infrastructure cost management for engineers showing AWS/GCP costs in pull requests before deployment; YC W21 $17.2M at 3,500 companies including 10% of Fortune 500 competing with CloudHealth for FinOps.
Infracost is a San Francisco-based cloud cost management platform — backed by Y Combinator (W21) with $17.2 million raised including a $15 million Series A led by Pruven Capital with Insight Partners in November 2025 — providing engineers with real-time infrastructure cost visibility during the development workflow, surfacing estimated cloud costs directly in pull requests before code is merged to production. Serving 3,500+ companies including 10% of the Fortune 500, Infracost integrates with Terraform and infrastructure-as-code workflows to calculate and display the monthly cost impact of infrastructure changes at the point in the workflow where engineers can still make cost-aware decisions.
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