# AppSecAI > AppSecAI turns findings from any code scanner into validated, tested code fixes, delivered as pull requests that the customer's own team reviews and merges. Triage accuracy is 97% and fix accuracy is 93%, both published on the OWASP Benchmark and reproducible. Pricing is per accepted fix — rejected fixes cost nothing. AppSecAI was founded by the team that started Contrast Security. The product has two halves. Expert Triage Automation (ETA) ingests findings from every scanner a team runs, correlates and dedupes them, and separates real vulnerabilities from false positives. Expert Fix Automation (EFA) writes the code fix, validates it against security, functionality and code-quality checks, and delivers it as a pull request. Access to customer code is read-only: merges happen in the customer's own pipeline, under their own branch protection rules. The problem AppSecAI addresses is the gap between find rate and fix rate. The median time to remediate a vulnerability is 243 days at a cost of $5,000–$20,000 per manual fix, while AI-assisted development is pushing finding volume up sharply. Prioritization tools re-order that queue; AppSecAI is built to shrink it. Findings are accepted from Anthropic, Black Duck, Checkmarx, CodeQL, Fortify, Gemini, OpenAI, Semgrep, Snyk, SonarQube and Veracode — individually or all at once — plus anything that exports SARIF or JSON. Fixes are generated for C# / .NET, Java, Python, JavaScript / TypeScript, Ruby, Go, PHP, C / C++, Rust, Kotlin, Scala, Swift and VB.NET. The complete text of the pages listed below is available at https://www.appsecai.io/llms-full.txt. ## Product - [Expert Triage Automation (ETA)](https://www.appsecai.io/expert-triage-automation-eta): AI triage separating real vulnerabilities from false positives across every scanner at once — 97% accuracy on the OWASP Benchmark, seconds per finding against roughly 5 minutes for manual review. - [Expert Fix Automation (EFA)](https://www.appsecai.io/expert-fix-automation): Generates production-ready code fixes that follow the team's coding standards, validates them, and delivers each as a pull request — 93% fix accuracy, 8.2 minute average fix time. - [Performance metrics](https://www.appsecai.io/performance-metrics): Published benchmark results — 97.2% aggregate triage accuracy across 25,123 open-sourced findings, 93.5% false positive reduction, 93% automated fix rate on OWASP BenchmarkJava100 with zero security regressions introduced, broken down per scanner. - [Pricing](https://www.appsecai.io/pricing): Published per-fix rates — $250 Standard, $200 Growth, $150 Scale, per fixed vulnerability. Triage included at no charge, free trial available, nothing owed for fixes the customer rejects. ## Who it is for - [CISOs](https://www.appsecai.io/application-security-for-cisos): Portfolio coverage under remediation policy, cost per fix as a unit economic, risk retired over time, and a per-fix evidence chain for auditors. - [Application security teams](https://www.appsecai.io/application-security-teams): How an AppSec team moves from reporting risk to retiring it — policy set per vulnerability class and per application, PR grouping strategies, and what the working week looks like afterward. - [Product security](https://www.appsecai.io/product-security): Fixes delivered inside the sprint the finding was raised, so releases ship fixed rather than held. - [Vulnerability management](https://www.appsecai.io/vulnerability-management): Turning a backlog that ages into debt into a burndown — why prioritization re-orders a queue rather than shrinking it. - [Engineering leaders](https://www.appsecai.io/engineering-security-automation): Removing security friction from the development workflow — no new tools, no agent in the IDE, no security tickets in the sprint. ## Company - [About AppSecAI](https://www.appsecai.io/about): The founding story, the Contrast Security lineage, the company's positions on lock-in and open benchmarks, and leadership bios for Bruce Fram, Michael Cartsonis, Kevin Fealey and Lori Harmon. - [Customer results](https://www.appsecai.io/results): Four detailed customer stories with numbers — Taama, IndustrialMind.ai, IntermediaIT and Galah Cyber — covering both software companies and AppSec service providers. - [Partner program](https://www.appsecai.io/partners): For security consultants, MSSPs and penetration testers who want to deliver fixed code to clients rather than findings reports — the model IntermediaIT and Galah Cyber built their services on. ## Learn - [Application Security: The Complete Guide in the AI Era](https://www.appsecai.io/application_security_complete_guide): Reference guide covering SAST, DAST, IAST, SCA, ASPM, CNAPP, API security, container security and the OWASP Top 10, each through the lens of what AI changes. - [The AI Security Advantage, by Bruce Fram](https://www.appsecai.io/the-ai-security-advantage-by-bruce-fram): Nine-chapter book on Fix Automation Management for CISOs and AppSec leaders — cost per fix, vendor evaluation, ROI case, running a PoC, and scaling across a portfolio. - [Blog](https://www.appsecai.io/blog): Ongoing writing on AppSec economics, AI-driven vulnerability discovery, and remediation practice. ## Get started - [Try it on your own findings](https://www.appsecai.io/try-now): Submit SARIF scanner output and a repository URL, and get back a triage report and merge-ready pull requests, free. - [Watch the demo](https://www.appsecai.io/demo): A two-minute product demo, plus scheduling for a 30-minute technical session against your own codebase. ## Optional - [Careers](https://www.appsecai.io/careers): Open roles at AppSecAI. - [Privacy policy](https://www.appsecai.io/privacy-policy) - [Terms of service](https://www.appsecai.io/terms-of-service) - [Cookie policy](https://www.appsecai.io/cookie-policy)