Overview
VerifyBee is an email-verification SaaS that helps sales and growth teams scrub invalid addresses from their contact lists before every send — protecting sender reputation, reducing bounce rates, and improving deliverability across every campaign. The platform needed to handle large-scale verification requests reliably while exposing a real-time API that developers could integrate directly into their workflows.
Figmafy was brought in to design and build the full platform: frontend, backend, and data infrastructure.
The challenge
Email verification sounds simple but the engineering demands are not. VerifyBee needed to process bulk verification jobs quickly and accurately, expose a real-time API with low latency, and present results through an interface non-technical users could act on without confusion.
The requirements spanned the full stack:
- Build a responsive, user-friendly frontend that made bulk uploads and results readable at a glance
- Architect a scalable backend capable of handling high volumes of verification requests without degrading accuracy
- Design a data layer optimized for fast retrieval across large contact datasets
- Deliver a real-time API developers could integrate with minimal friction
- Ship a production-ready platform within a six-month timeline
The data retrieval speed was the critical constraint. At scale, slow lookups make verification feel unreliable — so the Elasticsearch and MySQL architecture had to be designed for query performance from the start, not retrofitted later.
Our solution
Figmafy structured the six-month engagement around the three distinct layers of the platform, building and integrating them in sequence.
- Frontend. We built a clean, responsive interface using Bootstrap, HTML, CSS, and JavaScript. The dashboard surfaces verification results clearly — status breakdowns, invalid-address counts, and export options — so users can act on results without digging through raw data.
- Backend. The core application runs on PHP and Laravel, handling the verification workflow, job queuing, and user management. Ruby was integrated for specific processing tasks requiring different runtime characteristics.
- Data layer. We designed a dual-database architecture using Elasticsearch for fast full-text search and real-time lookups, and MySQL for relational data integrity and reporting. This combination gives VerifyBee both speed and accuracy at scale.
- Real-time API. We built and documented a developer-facing API that allows teams to trigger verification requests and retrieve results programmatically — making VerifyBee embeddable in existing outreach and CRM workflows.
Technologies used
- Bootstrap + HTML + CSS + JavaScript — responsive, accessible frontend
- PHP + Laravel — core backend application, job management, and user workflows
- Ruby — specialized processing pipelines
- Elasticsearch — fast full-text search and real-time verification lookups
- MySQL — relational data store for contact records, results, and reporting
Results
Figmafy delivered the full VerifyBee platform within the six-month timeline. The platform processes bulk verification requests with fast, accurate results — eliminating invalid addresses from contact lists before they cause deliverability damage. The real-time API was well-received by developer users integrating VerifyBee into their outreach stacks, and the interface earned positive feedback for its clarity and ease of use when managing bulk verification jobs.
VerifyBee's team can now confidently offer their users a platform that handles scale without sacrificing accuracy — backed by an Elasticsearch data layer built for high-volume retrieval from day one.
If your SaaS needs a full-stack build with a robust backend and a developer-friendly API, explore our full-stack development service or get a free quote and we'll scope it out.
