Radar check
What we found when we opened it. Every bar is one fact, with its date.
Last code pushed 22 Oct 2026, 4 days before this check.
No releases published on GitHub; the code date above is the one to trust.
Public since February 2026, 8 months.
23 stars and 5 forks.
98 commits and 8 new issues in the last 90 days.
7 contributors. 84 pull requests merged in 90 days. A small team carries it.
A security policy says how to report a problem. No published security advisories.
How the bars are scored
- Alive. Days since the last code push: a week or less 100, a month 90, three months 70, six months 50, a year 30, eighteen months 15, older 0.
- Releases. Age of the latest GitHub release, on a similar scale; no bar when the project publishes no releases.
- Maturity. Age of the project: eight years 100, five 90, three 70, two 55, one 40, six months 25, younger 10.
- Adoption. Stars on a log scale: 100,000 stars is 100, 10,000 is 80, 1,000 is 60, 100 is 40.
- Activity. Commits in the last 90 days: 300 or more 100, 100 85, 30 65, 10 45, any 25.
- Community. People who have contributed: 100 or more 100, 30 80, 10 60, 5 40, 2 25, one 10.
- Security. A published security policy 80, none 40; published advisories are listed, not scored.
Checked by Repo Radar on 26 Oct 2026 from the repository on GitHub.
In simple English
This tool checks what AI search engines say about your brand. It sends keywords to engines like OpenAI and Perplexity, records their answers, and spots which domains they recommend. It shows you the results in a web dashboard with charts, reports, and alerts. You run it on your own Amazon Web Services account. It costs money for the cloud resources and the AI provider keys you use.
What it is
A serverless application deployed with AWS CDK that automates brand mention tracking across multiple AI search engines. It uses Python backend functions, DynamoDB storage, and an interface built with React and TypeScript.
What it is good for
Marketing teams and founders who want to measure how often artificial intelligence search engines cite their products or their competitors.
- Tracks multiple AI engines from one dashboard.
- Sends alerts when your brand visibility drops.
- Exports reports to Excel and other formats.
- Requires an active Amazon Web Services account and command-line deployment.
- Ongoing costs for cloud infrastructure and paid AI provider keys.
- Complex setup involving API keys, secrets, and cloud permissions.
Manual searches on AI search engines and spreadsheets for competitor research.
Amazon Bedrock
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npm install aws configure npm run deploy