SerpApi's answer

We provide more search engines under one subscription.

Seranova's answer:

• Seranova is built for trades and service businesses, which makes it unique among competitors who serve broad industries.
  
• Competitors often focus on multi-platform review management, while Seranova focuses on Google, where local visibility actually comes from.
  
• The routing logic is more straightforward and more practical, reducing the need for owners to monitor every message manually.
  
• It protects businesses by escalating negative messages privately before a review is requested, which many generic platforms do not handle well.
  
• It is easier to adopt, because the workflow mirrors how real service jobs are completed.

SerpApi's answer

Developers/Companies who need data from search engines.

Seranova's answer:

• Local service business owners and operators who rely on Google Reviews to attract customers.
  
• HVAC, plumbing, electrical, and roofing companies that need consistent follow-up.
  
• Restaurants, salons, spas, and clinics that depend on repeat customer satisfaction.
  
• Small and mid-sized teams that want automation without adding administrative work.

SerpApi's answer

Ruby on Rails and MongoDB

Seranova's answer:

• Next.js for the frontend and application framework
  
• React for UI components
  
• TypeScript for type safety
  
• Supabase and PostgreSQL for authentication and data storage
  
• TailwindCSS for styling
  
• OpenAI models for sentiment analysis
  
• Twilio for SMS delivery
  
• Vercel for hosting and deployment

SerpApi's answer

We're the first web scraping company that focus on scraping search engines.

Seranova's answer:

• Seranova focuses specifically on Google Reviews, the platform that matters most for local service businesses.
  
• Its workflows are built around fundamental post-job interactions, which makes it stand out from the platforms providing generic marketing automation.
  
• Sentiment analysis is optimized for short, service-style customer replies rather than long messages.
  
• Negative feedback is kept private automatically, giving the business owners one more chance to solve the problem before the customers are asked for public review.
  
• The system requires almost no manual effort, which matches the fast-paced reality of field service teams.

SerpApi's answer

Back in 2017, Julien Khaleghy, the founder of SerpApi, built an iOS app that can analyze data from a picture. iOS didn't have a proper machine learning framework back then. It was challenging: iPhones' RAM were limited, no GPU or no dedicated chip acceleration were available, using only CPU was painfully slow, and compiling/porting C code from machine learning framework like Tensorflow or Caffe to iOS wasn't straightforward. Oddly, all of this wasn't the most difficult part of this project. Collecting images from Google Images was.

In these projects, 80% of his time ended up being spent on scraping and parsing Google Images. And maybe only 20% on actual machine learning model training, UI design of the actual apps, and iOS programming. This is how SerpApi was born.

Seranova's answer:

• Seranova was created after seeing how often service businesses struggled with review requests and customer feedback.
  
• Owners were losing positive reviews because technicians forgot to ask.
  
• Negative experiences became public before anyone on the team knew about them.
  
• There was no predictable way to follow up after a job without manual reminders.
  
• Seranova was built to automate the process, keep issues private, and help service businesses maintain a consistent flow of authentic five-star reviews.

SerpApi's answer

• Airbnb
• Nvidia
• Meta
• Shopify
• Grubhub
• and more!

Seranova's answer:

• Heaven Breeze HVAC
• Gastroenterology Diagnostic Center