Custom advertising technology platforms, programmatic systems, OTT applications, real-time media analytics dashboards, and AI recommendation engines — built for publishers, media houses, streaming companies, and ad agencies that need to own their technology stack rather than depend on third-party platforms.
The global advertising technology market is projected to exceed $1 trillion by 2027, driven by the shift of advertising budgets from traditional media to programmatic digital channels. India's digital advertising market alone crossed ₹50,000 crore in 2024 and is growing at 25% annually — fuelled by cheap mobile data, rising video consumption, and increasingly sophisticated audience targeting capabilities. Yet the majority of media companies and publishers in this growth market still depend on off-the-shelf platforms where they pay per impression, share their audience data with third parties, and own no proprietary technology.
The strategic shift happening across the industry is towards first-party data ownership and proprietary technology stacks. Publishers who rely entirely on Google Ad Manager and AWS Elemental for their ad serving and streaming have no competitive differentiation — their margins are squeezed by platform fees, their audience data is shared with the platform owner, and they cannot build the custom features their content and advertisers require. Building custom AdTech platforms, programmatic advertising systems, and OTT applications is how media businesses convert their content and audience assets into proprietary technology moats.
We build custom media technology for publishers building their first ad server, streaming companies launching OTT applications, advertising agencies developing campaign automation tools, data companies monetising audience segments, and media houses needing unified analytics across all their properties. We work with the complete AdTech stack — from header bidding and real-time bidding infrastructure to AI-powered recommendation engines and audience segmentation platforms.
Our media technology work connects to our AI & automation, cloud & DevOps, and SaaS product development capabilities. Related industries: eCommerce and Fintech.
Digital publishers, streaming companies, ad networks, and media technology startups based in Noida, Delhi-NCR, Mumbai, Bangalore, and Hyderabad. India's media technology ecosystem is one of the fastest-growing in Asia — we build for both domestic scale and global ambitions.
From programmatic infrastructure to OTT platforms — end-to-end media technology development.
Custom audience segmentation using your own first-party data delivers targeting precision that third-party cookie-based solutions cannot match — and remains effective as cookie deprecation eliminates third-party data. Advertisers pay premium CPMs for publisher first-party audiences because they are more reliable and privacy-compliant.
Header bidding with multiple demand sources increases average CPM by 20–40% over single-source waterfall setups. First-party data segments command 3–5× premium CPMs over untargeted inventory. Eliminating platform licence fees on high-volume inventory significantly improves margin on every impression.
Unified real-time analytics across all properties and channels — editorial, advertising, streaming, and subscription — in a single dashboard. Decisions based on live performance rather than yesterday's report. Anomaly detection alerting immediately when fill rates drop, CPMs shift, or streaming quality degrades.
Automated bid management, budget reallocation, creative rotation testing, and pacing optimisation reduce the ad operations headcount required to manage large campaign portfolios. Self-serve advertiser portals reduce the sales team's manual work on campaign setup and reporting significantly.
Owning your technology stack eliminates per-impression and per-event licence fees that scale linearly with your audience growth. Custom infrastructure sized to your actual traffic is consistently more cost-efficient than SaaS pricing tiers designed around average usage rather than your specific traffic patterns.
AI recommendation engines delivering personalised content discovery increase session duration 3× on OTT platforms and reduce subscriber churn significantly. Personalised ad experiences — fewer, more relevant ads rather than high-frequency generic targeting — improve user satisfaction while increasing CPMs from more engaged audiences.
Every metric that matters — live, unified, and actionable from a single dashboard.
Live dashboards updating every 30–60 seconds — concurrent viewers, active sessions, ad fill rates, CPM, revenue per hour, video start and completion events, subscription activations and cancellations. Kafka-based event pipeline ensuring sub-minute latency from event to dashboard update at any scale.
Pixel and server-side click tracking with deduplication and invalid traffic filtering. CTR analysis by ad format, placement, creative, audience segment, device type, and time of day. Click fraud detection using behavioural signals to filter bot traffic before it reaches advertiser billing. Viewability measurement for display and video inventory.
Funnel analysis from ad impression through click, landing page visit, subscription start, trial activation, and paid conversion — showing exactly where users drop out and quantifying the revenue impact of optimising each funnel stage. Attribution modelling connecting advertising spend to subscription revenue at the campaign, channel, and creative level.
Multi-touch attribution modelling connecting advertising exposure across multiple touchpoints to final conversion — moving beyond last-click attribution that undervalues top-of-funnel channels. Revenue attribution by content category, traffic source, audience segment, and device type for data-driven editorial and advertising strategy decisions.
Content consumption analysis showing which articles, videos, and formats drive the deepest engagement, longest sessions, and highest return visit rates. Audience cohort analysis tracking how engagement and monetisation patterns differ across acquisition channels, registration cohorts, and content preferences. Churn risk scoring identifying subscribers at risk of cancellation before they cancel.
Scheduled report generation delivering daily, weekly, and monthly performance summaries to editorial, commercial, and executive teams — each view showing the metrics most relevant to that team's decisions. Advertiser-facing reporting portals giving clients self-serve access to their campaign performance data without ad operations team involvement in every report request.
Architecture-first development — performance and scale designed in from day one, not retrofitted after launch.
AdTech and media platforms handle billions of events daily — security, performance, and uptime are architectural requirements.
Granular permission management — ad operations teams, data analysts, editorial staff, and executive viewers each access only the system components and data relevant to their role. Audit logging of all data access and configuration changes. API key management with scope-limited tokens for third-party integrations. OAuth 2.0 / OpenID Connect for SSO integration with enterprise identity providers.
All public-facing APIs — bid request endpoints, tracking pixels, analytics APIs, and streaming APIs — protected with rate limiting, request signature verification, and DDoS mitigation. Bot traffic detection filtering invalid traffic before it reaches billing or analytics systems. WAF (Web Application Firewall) protecting ad serving endpoints from injection and abuse attacks.
User behaviour data, audience segment data, and financial transaction data encrypted at rest (AES-256) and in transit (TLS 1.3). Encryption key management using AWS KMS or Azure Key Vault. PII minimisation — storing the minimum data required for targeting and measurement. Consent management platform integration ensuring audience data is only used for purposes users have consented to.
Kubernetes-based container orchestration with Horizontal Pod Autoscaler responding to CPU, memory, and custom metrics (queue depth, request latency). Pre-scaling rules for predictable traffic spikes — live event or series premiere nights. Auction path and streaming paths scaled independently based on their distinct load patterns. CloudFront CDN absorbing static asset and video delivery load at the edge before it reaches origin.
Continuous database replication with point-in-time recovery. Cross-region backup for data assets (audience segments, campaign configurations, user data). Kafka topic replication for event stream durability. Disaster recovery runbooks with defined RTO/RPO validated through quarterly DR drills. Bid request queue persistence ensuring no revenue loss if auction infrastructure restarts during traffic.
Multi-AZ deployment with load balancer health checks ensuring automatic failover if an availability zone has issues. 99.9% uptime SLA for ad serving and streaming paths — downtime here directly impacts revenue. Circuit breakers preventing cascade failures across microservices. Chaos engineering practices identifying weak points before they cause production incidents.
Custom supply-side platform for a network of 35 regional Indian news publishers — unified header bidding across all properties, Prebid.js server-side implementation, private marketplace deal management, and real-time yield analytics. Connects to 12 DSPs simultaneously. Processes 180 million bid requests daily with average auction latency of 62ms. Average CPM across the network improved 34% vs. the single-network waterfall setup it replaced.
Full OTT platform for a South Indian content production company — video pipeline with 4K transcoding, CloudFront CDN, Widevine DRM, React Native apps for Android and iOS, Next.js web app, Android TV app, SVOD subscription management with Razorpay, and collaborative filtering recommendation engine. Launched with 1,200-title library. Achieved 95% average 90-second video start success rate at launch. AI recommendations increased average session duration from 28 to 74 minutes.
Real-time analytics platform unifying data from 8 digital news properties — integrating ad server, CMS, Google Analytics, and subscription system into a single live dashboard. Kafka event pipeline ingesting 6 million events/hour. ClickHouse for sub-second query response on 90-day rolling datasets. Editorial, commercial, and executive views with custom metrics per team. Replaced a 4-hour daily manual reporting process with live dashboards. Revenue anomaly detection saved an estimated ₹8 lakh in a single underperforming campaign discovered and corrected same-day.
"CPM improved 34% across our publisher network the first month after switching to the custom SSP. Auction latency at 62ms means we are competitive on every bid request — previously our single-network waterfall was leaving premium impressions on the table. The real-time yield dashboard alone changed how our ad ops team makes daily decisions."
"Session duration went from 28 minutes to 74 minutes after the recommendation engine launched. That single metric improvement meant subscribers were watching 2.6× more content per session — our churn rate dropped 22% in the first quarter because subscribers were finding shows to watch rather than leaving after finishing one title."
"We used to spend 4 hours every morning manually compiling the previous day's performance report from 6 different tools. Now we have live data on screen before the morning standup. The revenue anomaly detection alone saved ₹8 lakh when it caught an underdelivering campaign on the same day it started — previously we would have discovered it a week later."
Start with a free consultation. Vivek will review your current technology stack, traffic volumes, monetisation model, and competitive landscape — and outline exactly what a custom platform would deliver for your media or advertising business.