iSkylar
INDUSTRY-LEADING SOLUTIONS

Social Media
Solutions

End-to-end social platform engineering for communities that demand real engagement — from real-time feed architecture and AI-powered content discovery to creator monetisation infrastructure, live streaming, and the trust & safety systems that protect platform health at scale.

Menu
Delivery 15-20 min

The Modern Social Platform Ecosystem

Building a social platform is no longer just a feature problem — it is an infrastructure problem. The gap between an app that launches and an app that retains users is almost entirely determined by what happens under the hood: the feed algorithm, the notification engine, the real-time messaging layer, and the content moderation systems that keep the community worth being part of.\n\nThe social platforms that fail do so not because they had the wrong idea — but because they underestimated the engineering complexity behind the experience. A 200ms feed load or a missed notification at the wrong moment compounds into churn at the population level.\n\niSkylar builds the backend infrastructure that makes social platforms actually work — real-time event-driven architecture, ML-ranked content feeds, scalable media processing pipelines, and creator monetisation systems engineered for the engagement dynamics of modern social communities.

ENGINEERED FOR PERFORMANCE

Core Infrastructure Features

MODULE 01

Real-Time Feed & Event Architecture

Event-driven backend using Kafka and Redis that processes user actions, social graph updates, and content events in real time — delivering sub-200ms feed loads for personalised timelines even at tens of millions of daily active users.

MODULE 02

Scalable Media Processing Pipeline

Automated ingestion, transcoding, and CDN distribution for images, video, and audio — handling concurrent upload spikes during live events without queue build-up or delivery latency, with adaptive bitrate streaming for all connection types.

MODULE 03

Real-Time Messaging & Presence Infrastructure

WebSocket-based messaging with end-to-end encryption, read receipts, typing indicators, and online presence status — supporting direct messages, group chats, and broadcast channels under a single unified backend.

MODULE 04

Trust & Safety Moderation Layer

Automated content moderation using computer vision and NLP models to detect policy violations at upload time — combined with a configurable human review queue, appeals workflow, and audit logging for regulatory compliance across jurisdictions.

The Three Pillars of the System

User Experience

  • Personalised social feed
  • Stories & short-form video
  • Live streaming
  • Direct & group messaging
  • Notifications & activity feed

Community & Content

  • User profiles & social graph
  • Content creation tools
  • Hashtags & discovery
  • Community groups & forums
  • Events & RSVP management

Creator & Growth

  • Creator monetisation tools
  • In-app tipping & gifting
  • Subscription & paid content
  • Referral & growth loops
  • Platform analytics for creators
THE INTELLIGENCE LAYER

AI-Driven
Optimization

ML-Ranked Personalised Feed Algorithm

Collaborative filtering and engagement prediction models that rank content by relevance to each individual user — balancing recency, social graph proximity, content type preference, and session context to maximise time-in-app and meaningful interaction rates.

AI-Powered Content Discovery & Search

Semantic search and topic clustering models that surface relevant content, creators, and communities to users beyond their immediate social graph — the primary driver of new connection formation and organic platform growth.

Intelligent Notification Engine

ML models that determine the optimal notification type, timing, and frequency for each individual user — reducing notification fatigue and opt-out rates by 40–60% while increasing click-through and re-engagement from push campaigns.

Automated Trust & Safety at Scale

Computer vision models for image and video policy enforcement combined with NLP classifiers for text-based violations — processing 100% of uploaded content before it reaches the feed, with configurable sensitivity thresholds by content category and user age group.

The Technology Frontier

React Native
Node.js
Go
PostgreSQL
Redis
Kafka
Elasticsearch
AWS CloudFront
WebRTC
Socket.io
TensorFlow
FFmpeg

The Delivery Lifecycle

1

Community Design & Growth Strategy

2

Platform Architecture & Feed Design

3

Agile Build, Feed Tuning & Load Testing

4

Soft Launch, Community Seeding & Hypercare

Built-In Monetization

Creator Monetisation & Revenue Share

In-app tipping, paid subscriptions, exclusive content paywalls, and virtual gifting — with configurable platform revenue share that incentivises your best creators to grow their audience on your platform rather than migrating to competitors.

Native Advertising & Sponsored Content

Contextual in-feed ad placements, sponsored community posts, and branded challenges integrated natively into the content experience — generating CPM-based advertising revenue from your content inventory without degrading organic engagement.

Premium Membership & Feature Tiers

Offer power users enhanced features — advanced analytics, profile badges, priority support, and exclusive content access — through a monthly or annual subscription that creates predictable recurring revenue from your most engaged user segment.

Investment & Pricing

Scalable packages designed to grow with your business, from MVP to Enterprise solutions.

Growth
From $30,000

  • Community design & engagement loop workshop
  • Social app (iOS & Android)
  • User profiles & social graph
  • Feed & content discovery
  • Real-time messaging
  • Media upload & CDN delivery
  • Basic moderation tools
  • 3 months post-launch support
  • Full IP & source code ownership
POPULAR
Enterprise
Custom Quote

  • All Growth features
  • ML-ranked personalised feed algorithm
  • AI content discovery & search
  • Intelligent notification engine
  • Automated trust & safety moderation
  • Live streaming infrastructure
  • Creator monetisation suite
  • Advanced analytics dashboard
  • Dedicated offshore engineering team
  • SLA 99.9% uptime guarantee
  • Priority support & hypercare

* Note: Final costs vary based on feature complexity, platform choices, and specific API integrations. Get an exact quote for your project.

Success Stories

From Pilot Purgatory to Production: How an Enterprise Finally Made AI Work Across the Business

ENTERPRISE AI

From Pilot Purgatory to Production: How an Enterprise Finally Made AI Work Across the Business

73% — Faster Document Processing

41% Cloud Cost Reduction in 90 Days : How a SaaS Scale-Up Finally Got Control of Its Cloud Bill

CLOUD / SAAS

41% Cloud Cost Reduction in 90 Days : How a SaaS Scale-Up Finally Got Control of Its Cloud Bill

41% — Cloud Cost Reduction

Frequently Asked Questions

How do you build a feed algorithm that actually drives engagement rather than just showing newest content?
We build ML-ranked feeds using collaborative filtering and engagement prediction models trained on your own user behaviour data. In the early days before sufficient data exists, we start with a hybrid recency-plus-social-graph approach and transition to full ML ranking as the dataset grows — typically around 50,000 active users. We also build the A/B testing infrastructure to continuously tune ranking weights against your specific engagement goals.
How do you handle content moderation at scale without a large trust and safety team?
We integrate automated pre-publication moderation using computer vision (for images and video) and NLP classifiers (for text) that process 100% of content before it reaches the feed. Borderline content is routed to a human review queue. This approach typically catches 85–90% of policy violations automatically, reducing the human review workload to genuinely ambiguous cases.
What real-time infrastructure do you use for messaging and live features?
We use WebSocket connections (Socket.io / native WebSocket) for real-time messaging, typing indicators, and presence — with Redis Pub/Sub managing state across multiple server instances. Live streaming runs on WebRTC for peer-to-peer or low-latency use cases, and HLS with a CDN origin for broadcast-to-many scenarios.
How do you approach the cold-start problem — getting a new social platform populated before it has users?
We design creator seeding strategies into the launch plan: identifying and onboarding power users before public launch, pre-populating content feeds via invite-only cohorts, and configuring the feed algorithm to prioritise content diversity over pure engagement optimisation in the early stage. We also build the referral and invite mechanics that accelerate organic graph growth from day one.
Can you build creator monetisation tools that compete with Patreon, Substack, or similar platforms?
Yes. We build the full creator monetisation stack: subscription tiers with exclusive content access, in-app tipping and virtual gifting with platform revenue share, pay-per-view content, and direct messaging paywalls. The economics are fully configurable — you set the platform take rate and payout schedule, and we build the Stripe Connect or regional payment provider integration to handle disbursements.
How long does it take to build a social platform, and how do you handle scale as the user base grows?
A focused community app with core social features typically takes 16–20 weeks. A full platform with AI feed ranking and creator monetisation runs 22–30 weeks. Architecture is designed for horizontal scaling from day one — adding users does not require architectural rework, only compute provisioning.

Ready to launch your vision?

Get a comprehensive development roadmap and fixed-price proposal within 48 hours.

Need help? 👋