One prompt, six languages. One user, one agent.
Series-B regional streaming · multi-language · 90-day engagement
The problem
The CEO came in planning to triple the engineering team to clear a multi-year backlog. We pushed back: use the team you have. The real constraint was never headcount — it was that every function, from content to retention to finance, was still working the pre-AI way.
What we built
1 prompt → 6 languages, in parallel
AI-native content production
A two-minute clip that used to take a week now ships in hours. The same story auto-reframes per region — same emotional arc, different cultural context. Multi-language stopped being a sequential effort and became the single biggest shift of the engagement.
From support bot to relationship platform
One user, one agent
A WhatsApp support bot, live in three days, grew into a platform where every user has a dedicated agent — support, retention, re-engagement, recommendations — that knows their history. Three vendor teams collapsed into one in-house system.
20+ in-character bots across six shows
Character chatbots
In-character chatbots with persistent per-user memory. Users spent hours talking to them. The team did not believe it would happen until it did.
2-year backlog → 2 days
Engineering throughput
A feature stuck in the backlog for two years went live in two days. Infrastructure cost halved in a day. A single data-cleanup session eliminated a recurring monthly cost line.
Outcomes
The transferable lesson
The shift was not one team adopting AI — it was every team. Content turned production into code. Retention rebuilt the funnel. Finance shipped its own tools. Engineering converted last, not first. The company stopped scaling with headcount and started scaling with agents — and the economics changed permanently.