Works
AirMedia
Launched a real-time AI-powered social marketing platform.
PROJECT SNAPSHOT
AirMedia began as a simple question. What if social media marketers could automate their content and reporting with the same speed and insight as top-tier teams? We set out to build a platform that would turn unstructured data, including posts, analytics, and market trends, into actionable intelligence for marketers.
THE CHALLENGE
In 2023, social marketers were overwhelmed by platforms, drowning in analytics, and spending too much time on repetitive reporting and content ideation. The explosion of AI tools promised relief but delivered scattered features and siloed experiences. We built AirMedia to fill this gap. Our own team had struggled to scale social channels efficiently and existing solutions felt clunky, expensive, or inflexible. We knew there had to be a better way so we decided to build it ourselves.
THE PARTNERSHIP
The project kicked off with a blend of rapid user interviews and competitive teardown. We spoke with agencies, small business owners, and in-house marketers to map their pain points. Our process was grounded in hands-on discovery, weekly design sprints, and honest reviews of what was working and what needed rethinking. We adopted an agile approach from the start, keeping our development roadmap open to new insights from real users. The focus was to deliver practical value, not over-engineered features.
THE BUILD
The development moved fast. We defined the AI core early, choosing LLM-powered content generation and real-time analytics summarisation as the backbone. React and Django gave us flexibility and speed on the front and back end, while OpenAI APIs powered the AI layer. We tested with a closed beta group, shipped new features weekly, and iterated on UX based on usage data instead of gut feel. The biggest challenge was balancing advanced AI with everyday usability. Our breakthrough was a conversational UI that guided users without overwhelming them. We hit obstacles in integrating social APIs at scale, but persistent user feedback helped us prioritise what mattered most.
AirMedia went live in under four months. Early adopters cut weekly content prep by half, and small agencies reported a 30 percent reduction in time spent on analytics and reporting. User feedback praised the platform’s clarity and speed, especially for teams without dedicated marketing analysts. One agency founder said, AirMedia turned hours of second-guessing into instant clarity and now we focus on campaigns, not spreadsheets. The launch triggered inbound interest from partner agencies and prompted us to build white-label features and automated onboarding.
Related Works
Works
AirMedia
Launched a real-time AI-powered social marketing platform.
PROJECT SNAPSHOT
AirMedia began as a simple question. What if social media marketers could automate their content and reporting with the same speed and insight as top-tier teams? We set out to build a platform that would turn unstructured data, including posts, analytics, and market trends, into actionable intelligence for marketers.
THE CHALLENGE
In 2023, social marketers were overwhelmed by platforms, drowning in analytics, and spending too much time on repetitive reporting and content ideation. The explosion of AI tools promised relief but delivered scattered features and siloed experiences. We built AirMedia to fill this gap. Our own team had struggled to scale social channels efficiently and existing solutions felt clunky, expensive, or inflexible. We knew there had to be a better way so we decided to build it ourselves.
THE PARTNERSHIP
The project kicked off with a blend of rapid user interviews and competitive teardown. We spoke with agencies, small business owners, and in-house marketers to map their pain points. Our process was grounded in hands-on discovery, weekly design sprints, and honest reviews of what was working and what needed rethinking. We adopted an agile approach from the start, keeping our development roadmap open to new insights from real users. The focus was to deliver practical value, not over-engineered features.
THE BUILD
The development moved fast. We defined the AI core early, choosing LLM-powered content generation and real-time analytics summarisation as the backbone. React and Django gave us flexibility and speed on the front and back end, while OpenAI APIs powered the AI layer. We tested with a closed beta group, shipped new features weekly, and iterated on UX based on usage data instead of gut feel. The biggest challenge was balancing advanced AI with everyday usability. Our breakthrough was a conversational UI that guided users without overwhelming them. We hit obstacles in integrating social APIs at scale, but persistent user feedback helped us prioritise what mattered most.
AirMedia went live in under four months. Early adopters cut weekly content prep by half, and small agencies reported a 30 percent reduction in time spent on analytics and reporting. User feedback praised the platform’s clarity and speed, especially for teams without dedicated marketing analysts. One agency founder said, AirMedia turned hours of second-guessing into instant clarity and now we focus on campaigns, not spreadsheets. The launch triggered inbound interest from partner agencies and prompted us to build white-label features and automated onboarding.