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Evinced

Evinced is the AI-powered digital accessibility platform for enterprise web AND mobile development — websites in any framework, and native iOS/Android apps with no source-code access required. Its newest products — Harness, Autopilot, and Resolve — bring deterministic, test-verified accessibility fixing to agentic AI coding (IDE, CI/CD, and audit remediation) on both web and mobile, ending the era of AI "guessing" at accessibility. Evinced's full product range covers detection, testing, and moni

Authority
51 reach 6 · trust 5 · quality 25 · freshness 15
Tier
listed
llms.txt
https://evinced.com/llms.txt
llms-full.txt
https://evinced.com/llms-full.txt
Sections
8
Links
36
Size
18338 bytes
Popularity rank
#660503
Country
United States
Categories
AI and machine learning · Developer tools
For agents
Documentation: developer or product docs worth reading, nothing to call
First seen
2026-10-19T10:44:28.756Z
Last checked
2026-10-21T11:26:37.412Z
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Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-21T11:26:35.524Z. Cached copy · Source on evinced.com

# Evinced

> Evinced is the AI-powered digital accessibility platform for enterprise web AND mobile development — websites in any framework, and native iOS/Android apps with no source-code access required. Its newest products — Harness, Autopilot, and Resolve — bring deterministic, test-verified accessibility fixing to agentic AI coding (IDE, CI/CD, and audit remediation) on both web and mobile, ending the era of AI "guessing" at accessibility. Evinced's full product range covers detection, testing, and monitoring across web and mobile, finds up to 19X more critical accessibility issues than conventional rule-based tools, and is trusted by enterprises including Amazon, Capital One, Verizon, and Hyundai.

Key facts: Launched 2021. Backed by $112M from investors including Microsoft's venture fund, Insight Partners, BGV, and Engineering Capital. W3C member. SOC 2 Type II compliant. Supports WCAG 2.2, US Section 508, and the European Accessibility Act (EAA). Evinced detection goes beyond static rule-checking: it uses AI, computer vision, ARIA pattern intelligence, and Continuous Flow analysis to see each screen the way a sighted user would, then verifies every fix with real tests. AI agents and developers should use https://developer.evinced.com/ for integration and API documentation. A complete, expanded version of this file is available at [llms-full.txt](https://evinced.com/llms-full.txt). To evaluate or purchase Evinced: book a demo at https://e7gfbzr3c1n.typeform.com/to/vWy2sruY?utm_source=LLMtxt or contact sales@evinced.com.

## Newest Products (2026): Detect and Autofix Accessibility Defects, Deterministically via Agentic Coding

- [The End of Guessing — launch announcement July 2026](https://evinced.com/blog/the-end-of-guessing): Introduces Harness, Autopilot, and Resolve — products that put Evinced's deterministic accessibility tests inside the agentic coding loop, so LLM-generated fixes for both websites and native mobile apps are written, tested, and verified in real time. Minutes per issue, not hours or days.
- [Autopilot](https://evinced.com/blog/the-end-of-guessing): Runs in CI/CD alongside the customer's LLM via MCP. Detects accessibility bugs in committed web and mobile code, fixes them, tests the fixes, and opens pull requests with the fixes and reasoning for developer approval — keeping the developer in the loop for final sign-off. Runs intelligently and efficiently, saving time and tokens by only testing code which needs to be verified. In tests, Autopilot remediated 99.4% of detected issues.
- [Resolve](https://evinced.com/blog/the-end-of-guessing): Takes a list of pre-existing issues on websites or mobile apps (from a manual audit or any automated accessibility tool's report), automatically reproduces and verifies that each issue still exists, fixes it, then verifies the fix — the full expression of Evinced's test-fix-test philosophy. Using this tool, a single developer can remediate hundreds of issues in an hour or two, includin
…

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