How we work
Projects
Client
Linkbound
Technologies
React
React Native
Industry
SaaS
Duration
2024 - Ongoing
About the product
To understand Linkbound’s value, it’s important to distinguish between cold and warm outreach. Cold outreach means contacting people who have no prior connection to you or your content – essentially strangers.
Warm outreach, on the other hand, focuses on people who have already shown interest in your content by engaging with your posts through likes, comments, or shares. These people are already familiar with you and have demonstrated some level of interest.
Linkbound helps sales professionals identify and connect with these warm prospects who have already engaged with their LinkedIn content. Linkbound is not a tool for those who want to “spam” LinkedIn. It is designed for professionals who wish to build genuine relationships.
Challenge #1
LinkedIn has evolved from a simple job search into a business networking and personal branding platform. But many users still don’t use its full potential.
The platform captures engagement data – who’s liking and commenting on your posts. It does not systematically organize these interactions or identify high-potential leads.
Creators put out content, get tons of reactions, and then… what?
Many struggle to turn that visibility into real business opportunities. Without a clear way to track and prioritize interactions, they miss out on potential clients and leave money on the table.
Here’s what Linkbound founder and our CEO, Senad Šantić identified in consultation with Jasmin Alić, LinkedIn Coach and expert:
Challenge #2
LinkedIn is now an essential tool for business networking and personal branding, but many users still don’t understand how to monetize their efforts.
CHALLENGE #3
Building Linkbound presented several complex technical hurdles
The solution
Rather than diving straight into building a full-featured product, we applied our lean startup methodology.
Instead of asking, “What do we want to build?”, we asked, “What hypothesis do we need to test?”
Our core hypothesis was that sales professionals could achieve higher response rates by focusing outreach on people already engaged with their LinkedIn content.
We started with a minimal but powerful feature set.
We listed and filtered the LinkedIn profiles of those who engaged with the content.
That way, we could quickly test without overcommitting resources. After confirming initial traction, we expanded based on direct feedback from the sales team. The system initially included:
Engagement analytics
Advanced filtering capabilities
Saved dynamic lists
Interaction tracking
Performance metrics
Smart follow-up alerts
THE PRODUCT
meant we built what users needed and not what we thought they might want
Top network
Filtering and tagging
Custom lists
Interactions
Smart alerts
AI-powered messaging
Tech stack
Frontend:
-We combined React, Vite, and Tailwind to create a fast and polished Chrome extension that integrates naturally with Chrome’s workflow.
-Web dashboard using the same tech stack for consistency and maintenance efficiency
-Mobile app developed with React Native for on-the-go access
Backend:
–Laravel API handles communication between databases and user interfaces
-Go workers for high-performance data processing, especially under load
-Laravel Filament for rapid internal admin panel development
-Laravel API handles communication between databases and user interface
-Go workers for high-performance data processing, especially under load
-Laravel Filament for rapid internal admin panel development
& more
Our technical team structure was intentionally lean and efficient
-High-availability Kubernetes cluster (SLA) ensuring 99.99% uptime
-Helm Charts for simplified deployment management
-Comprehensive monitoring via Prometheus and Grafana
-PostgreSQL with PgBouncer for connection pooling and read replicas
-Redis for caching frequently accessed data
-MongoDB for application audit trails
-Technical lead – oversaw architecture and ensured code quality
-Backend developer – focused on data processing and API development
-Frontend developer – created the Chrome extension and web interfaces
-UX/UI Designer – developed the visual language and user experience
-QA specialist – conducted both manual and automated testing
-Fluentbit & Fluent Operator: To manage logs and improve observability, we deployed Fluentbit as the log collector and FluentOperator to manage Fluentbit configurations in Kubernetes.
-Fluentbit aggregates logs from all containers within the cluster and forwards them to our logging backend, where they can be indexed and analyzed
-This setup enables us to monitor logs in real time and troubleshoot issues quickly
-The tool operates independently from the user’s LinkedIn account, with no direct API integration or connection to the profile, ensuring no risk of the accounts being penalized or banned by LinkedIn
-Secure credential management with Infisical
-Sentry for proactive and comprehensive error handling – ensuring better user experience
-SonarQube for security hotspot in code and static code analysis
-DepentaBot for security upgrades of the packages
The results
Response rate
to messages sent to qualified leads (compared to typical cold outreach rates of 1-3%)
Responses led to a meeting
Chrome extension installs
ARR within the first week
major marketing campaigns
These results validated our build-measure-learn approach and confirmed that our MVP delivered on its core promise.
What’s particularly noteworthy is that we achieved these results with an incredibly efficient investment of resources.
By focusing on building only what was necessary to test our hypothesis and then iterating based on actual user feedback, we created a product that delivered immediate value without wasting time on unnecessary features.
Senad Santic
Founder & CEO at Linkbound
Our approach to product development
The result is a product that delivers genuine business value with minimal waste.
