Category: Reputation Tech / AI Analytics
Year Started: 2024
Technologies Used: Serper.dev API, ClarityLens AI, OpenAI, PHP, Python, Chart.js, Tailwind UI, Zapier, Supabase
PRAligns was created to solve a growing problem for modern brands — understanding how they are perceived across the web in real time. It fuses AI sentiment analysis, clarity scoring, and search intelligence to map a brand’s public reputation every day.
Strategy & Execution
We integrated Serper.dev for live Google SERP data and paired it with ClarityLens AI to detect tone and bias across articles, tweets, and forum mentions. Each mention is scored for Toxicity, Clarity, Positivity, and Credibility.
Dashboards built with Chart.js visualize trends, while Zapier automations push alerts to Slack or WhatsApp when negative sentiment spikes.
The backend is modular — each analysis runs asynchronously via Python workers and stores results in Supabase, enabling historical comparisons.
Impact & Results
Early adopters reported up to 70 % faster PR response times and a 45 % increase in positive sentiment after guided messaging revisions.
PRAligns converts unstructured data into daily insight cards: Top Stories, Domain Leaders, Bias Summary, People Also Ask, etc.
Vision
PRAligns is shaping into an AI command center for brand reputation, helping founders and CMOs not just monitor perception but actively improve it through clarity-driven storytelling.