How TechEniac Engineered a Smart Link and AI Verification Platform for 10,000+ Creators with 99.9% Uptime on AWS Kubernetes.
The client identified a critical creator-economy gap: up to 40% of engagement was lost when social links opened in restrictive in-app browsers. With a clear product vision and go-to-market strategy already in place, the client partnered with TechEniac to simplify the MVP, build AI-powered smart link detection, and create scalable infrastructure supporting 10,000+ creators from day one.
The founder identified three compounding problems strangling creator monetization:
When creators share links on Instagram, TikTok, and other social platforms, the links open in built-in in-app browsers that are intentionally restrictive—slow, limited functionality, aggressive ad placement, and poor user experience. Users encounter friction, abandon the purchase flow or signup, and creators lose sales they never even tracked. The platform restricts native app deep linking, forcing users to a degraded mobile web experience. For creators relying on link engagement for revenue, this invisible leak represents tens of thousands of dollars in lost income annually.
Brands running affiliate or partnership campaigns with creators need to verify that creators are following compliance requirements: displaying brand logos, including @mentions, tagging products correctly, using campaign hashtags. Currently, this verification is entirely manual—brand teams manually audit thousands of creator posts, taking days or weeks for a single campaign. With no automation, verification becomes a bottleneck that delays campaign launches and scales inefficiently as creator networks grow.
Brands need to set up campaigns for hundreds or thousands of creators simultaneously, typically by uploading CSV files with creator data. Manual processing of these files is slow, error-prone, and time-consuming. A single campaign with 5,000 creator rows can take 4+ hours to process, with no progress visibility or error reporting. This delay blocks campaign launches and creates friction in the brand-creator workflow.
Smart link engine that detects device type and app installation, opening links in native apps when available and mobile web as fallback, all within 200ms response time
AI-powered content verification pipeline that automatically detects brand logos, mentions, tags, and hashtags in creator posts, replacing days of manual auditing with minutes
Bulk CSV campaign processing that handles thousands of creator rows in minutes, not hours, with progress tracking and webhook notifications
Creator dashboard for link management, analytics, and campaign tracking
Production-grade infrastructure with 99.9% uptime from Day 1 to handle aggressive pre-launch marketing and immediate traffic spikes
The smart link engine is the core value proposition—a custom Node.js-based link resolution system that performs multi-layer detection within 200ms of every click. When a creator's smart link is clicked, the engine evaluates three signals simultaneously: user-agent parsing identifies the device type (iOS, Android, desktop) to determine the optimal redirect path; referrer header analysis detects the originating platform (Instagram, TikTok, Twitter) to understand the in-app browser context; deep-link protocol detection checks for installed native apps and routes to the native app deep link when available, falling back to mobile-optimized web views when the app isn't installed. The engine evaluates all signals simultaneously and issues the optimal redirect—native app deep link for the best user experience, mobile-optimized web view as fallback, or desktop browser experience. Branded short domains give creators professional, recognizable links (e.g., creator-name.brand.com) while the engine handles the intelligence behind the scenes. A continuously updated app-schema registry maps the latest deep-link URL schemes for 30+ major apps, handling version-specific routing with graceful fallback to mobile web.
TechEniac built a content verification pipeline using Gemini Vision models that automates what previously took brands days of manual auditing. The system ingests screenshots or video frames from creator posts and automatically detects brand logo presence, @mention tags, product visibility, and hashtag compliance. Brands configure verification rules in a campaign dashboard, and the AI generates a verification report with confidence scores per criterion. Early testing revealed an 18% false positive rate in logo detection—the model was flagging similar-looking graphics as brand logos. TechEniac implemented a two-stage verification approach: broad logo detection in the first pass, followed by a brand-specific classifier trained on actual brand assets in the second pass. This reduced the false positive rate from 18% to under 3%, making the verification pipeline production-reliable. Outcome: content verification that previously took days now takes minutes, enabling brands to launch campaigns faster and scale to thousands of creators without manual auditing bottlenecks.
Creators get a dashboard for link management, campaign tracking, and real-time engagement analytics. The interface shows which links are performing, where traffic is coming from, and how native app routing is improving engagement vs. standard links. Campaign data displays brand compliance status and verification results. Built with React.js and Next.js for responsive design across mobile and desktop, the dashboard integrates seamlessly with the smart link engine and AI verification system.
Deep Link Detection Across Evolving App Versions
Built a continuously updated app-schema registry that maps URL schemes for 30+ major apps with version-specific logic. When an app updates its deep-link format, the registry is updated within hours. The system maintains intelligent fallback logic: if the target app isn't installed on a user's device, the system automatically routes to a mobile-optimized web view. This eliminates broken redirect chains. Outcome: 99.9%+ link success rate across all apps and versions, with no creator-facing errors.
AI Content Verification False Positives
Implemented a two-stage verification architecture: broad logo detection in the first pass (casting a wide net), followed by a brand-specific classifier trained on actual brand assets in the second pass (filtering to true positives). The brand-specific classifier learns the actual visual characteristics of each brand's logos and assets. This dual-layer approach reduced the false positive rate from 18% to under 3%, making automated verification production-reliable. Outcome: brands now trust the AI verification system and can eliminate manual auditing almost entirely.
Bulk CSV Campaign Processing Timeouts
Moved CSV processing to an async background queue using Bull job processor. When a brand uploads a CSV file, the system immediately queues the processing job and returns a confirmation to the user. Processing happens asynchronously in the background with progress webhooks and email notifications notifying the brand when processing completes or errors occur. This eliminates timeouts and provides transparency into the processing status. Outcome: campaign setup time dropped from 4 hours to 5 minutes—a 97% reduction. Brands can now upload large files and move forward without waiting.
Creators Onboarded
in the firOnboarded in the first year, validating the simplified product focus. Creators adopted the platform rapidly because it solved a real, quantified problem.st year
Link Engagement
through smart link routing vs. standard links
Campaign Setup Time Reduction
from 4 hours to 5 minutes
Smart Link Latency
globally via CloudFront CDN
Platform Uptime
on AWS Kubernetes (EKS)
Content Verification
vs. days with AI-powered brand compliance
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