Improved Search Accuracy and Speed
NLP-powered engine increased search efficiency by 272% compared to keyword-based algorithms.
Azati developed a platform connecting users with local tradesmen through web and mobile apps, featuring a smart NLP-powered search engine, customizable profiles, reputation system, and integrated payments, addressing the challenge of inefficient lead generation, low trust, and poor search relevance.
user retention rate after first month
faster local tradesman search via NLP
increase in completed service bookings
The client needed a fast, accurate, and cost-effective platform for connecting users with local tradesmen. Their main pain points were high lead generation costs, low search relevance for user queries, and lack of trust between users and service providers. The goal was to implement a smart, NLP-powered search engine, a transparent reputation system, and integrated payments to create a reliable and engaging online services marketplace.
The customer needed a cost-effective alternative to SEO and PPC for attracting clients to the platform. We offered an online marketplace where tradesmen could gain visibility through organic search and reputation-based ranking instead of paid promotion.
The existing search solutions couldn’t handle natural, complex queries, leading to irrelevant results. We decided to built a machine learning-powered search engine with NLP capabilities to understand user intent and deliver accurate matches.
The customer needed a mechanism for building trust between service providers and clients. Our team implemented a transparent reputation system based on completed jobs and real user reviews, removing the need for tradesmen to pay for visibility.
We chose Ruby on Rails to quickly develop and deliver a Minimal Viable Product, using the framework's modularity to expand functionality over time.
Data extracted from websites was unstructured. We used a NoSQL database to store this data in a structured format, which allowed recruiters to search and evaluate candidates effectively.
Azati managed the entire development cycle, including project management, frontend and backend development, mobile apps, and infrastructure setup.
We enabled tradesmen to maintain profile pages with reviews and job ratings, fostering trust through completed work rather than paid promotion.
We implemented gamified mechanics like referral bonuses and early registration points to encourage adoption and reduce subscription costs for users.
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Schedule a callThe search engine understands complex, natural-language queries, enabling users to find tradesmen quickly even if the input is ambiguous or incomplete. It leverages machine learning to interpret intent and deliver highly relevant results.
Tradesmen can create detailed profiles including services offered, portfolios, completed jobs, and client reviews. This enhances trust and allows users to evaluate providers before making a selection.
The platform ranks tradesmen based on completed jobs and user feedback rather than paid promotions, ensuring that trustworthy providers are more visible and encouraging high-quality service.
Gamified incentives such as referral bonuses and early registration points help attract new users, retain existing ones, and motivate tradesmen to actively participate and maintain their profiles.
The solution includes synchronized web, iOS, and Android applications, allowing users and tradesmen to interact with the platform seamlessly across devices.
Supports multiple payment gateways, including digital currencies and international options, enabling secure, seamless transactions for services booked through the platform.
NLP-powered engine increased search efficiency by 272% compared to keyword-based algorithms.
Ruby on Rails enabled rapid MVP delivery and easy future feature expansion.
Reputation and community features increased trust and retention.
The client launched a competitive online services marketplace in a new industry.
Platform provided an affordable alternative to PPC advertising.
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