A two-person agency used translation automation to unlock international revenue on their first 2 models, then reinvested that revenue to grow to 10 models and 8 chatters within 8 months. This is the full timeline with hiring decisions, revenue milestones, and the mistakes they made along the way.
A small US-based agency started with 2 models and 2 chatters generating 15,000 EUR/month. By adding ForgeFlow translation to serve international fans, they increased per-model revenue by 40% and used the extra cash flow to fund expansion. After 8 months, they managed 10 models with 8 chatters, generating 92,000 EUR/month - a 6.1x increase in total revenue.
The agency (anonymized as "Agency S") launched in early 2025 out of Miami. Two co-founders each managed one OnlyFans creator account, handling all chatting themselves. Both spoke only English.
| Metric | Value (Month 0) |
|---|---|
| Models managed | 2 |
| Chatters | 2 (the founders) |
| Languages | English only |
| Monthly revenue | ~15,000 EUR |
| Revenue per model | ~7,500 EUR |
| International messages ignored | ~35% of inbound DMs |
The agency was profitable but small. Both founders were spending 10+ hours per day chatting. They wanted to scale but faced a chicken-and-egg problem: they needed more revenue to hire chatters, but they needed more chatters to generate more revenue.
The breakthrough insight: They did not need more chatters to grow revenue - they needed to monetize the 35% of inbound messages they were already ignoring. Those messages were in Spanish, French, German, Portuguese, and Italian. Each one represented a fan willing to spend money if someone would just talk to them.
Instead of immediately trying to onboard new models, Agency S focused on extracting more revenue from their existing 2 accounts by adding language support.
They deployed ForgeFlow on both accounts and began responding to every foreign-language DM. The results came quickly:
| Metric | Month 0 | Month 1 | Month 2 |
|---|---|---|---|
| Models | 2 | 2 | 2 |
| Chatters | 2 | 2 | 2 |
| Languages | 1 | 4 | 6 |
| Monthly revenue | 15,000 EUR | 18,600 EUR | 21,200 EUR |
| Revenue per model | 7,500 EUR | 9,300 EUR | 10,600 EUR |
In just 2 months, they increased total revenue by 41% without adding a single model or chatter. The additional 6,200 EUR/month came entirely from fans who had been messaging in languages the agency previously could not handle.
Agency S deliberately chose to scale languages before models. Their reasoning: adding a new model requires finding a creator, negotiating terms, setting up content production, and onboarding - a process that takes 2-4 weeks and has a failure rate. Adding a new language takes 30 seconds (one click in ForgeFlow) and immediately starts generating revenue from existing fans.
With monthly revenue now at 21,000+ EUR and still climbing, Agency S had the cash flow to hire. They brought on their first two chatters - both English speakers with no foreign language skills.
This was a deliberate choice. Because ForgeFlow handled all translation, they could hire based on chatting ability and sales instinct rather than language skills. This significantly widened their talent pool and reduced hiring costs.
| Metric | Month 3 | Month 4 |
|---|---|---|
| Models | 4 | 5 |
| Chatters | 4 | 4 |
| Languages per model | 6 | 7 |
| Monthly revenue | 34,500 EUR | 42,800 EUR |
| Revenue per model | 8,625 EUR | 8,560 EUR |
Revenue per model dipped slightly as the new models were still building their subscriber base. However, total revenue nearly doubled because every new model was immediately serving fans in 6-7 languages from day one - something that would have been impossible without translation automation.
With proven systems in place, Agency S accelerated. They added models in batches and hired chatters to maintain coverage ratios.
| Month | Models | Chatters | Monthly Revenue | Revenue/Model |
|---|---|---|---|---|
| Month 5 | 6 | 5 | 51,000 EUR | 8,500 EUR |
| Month 6 | 7 | 6 | 60,200 EUR | 8,600 EUR |
| Month 7 | 9 | 7 | 76,500 EUR | 8,500 EUR |
| Month 8 | 10 | 8 | 92,000 EUR | 9,200 EUR |
By month 8, the agency was generating 92,000 EUR/month - a 6.1x increase from the starting point of 15,000 EUR. Revenue per model also climbed to 9,200 EUR as earlier models matured and their international fan bases grew.
Agency S estimated what their staffing requirements would have looked like without ForgeFlow:
| Scenario | Chatters Needed | Monthly Payroll | Languages Covered |
|---|---|---|---|
| Without ForgeFlow (English only) | 10 | ~25,000 EUR | 1 |
| Without ForgeFlow (multilingual hires) | 18 | ~52,000 EUR | 7 |
| With ForgeFlow (actual) | 8 | ~20,000 EUR | 7 |
ForgeFlow saved the agency an estimated 32,000 EUR/month in staffing costs compared to hiring native speakers, while also enabling faster scaling because they did not need to find multilingual talent for each new market.
The growth was not without setbacks. Agency S shared three significant mistakes they made during the scaling process:
| Item | Amount |
|---|---|
| Total revenue (8 months) | 401,800 EUR |
| Revenue without ForgeFlow (estimated, English only) | ~145,000 EUR |
| Incremental revenue attributed to multi-language | ~256,800 EUR |
| ForgeFlow cost (scaling from 2 to 10 models) | ~3,450 EUR |
| Additional chatter payroll (6 hires over 8 months) | ~78,000 EUR |
| Net additional profit from scaling | ~175,350 EUR |
In this case study, the agency went from 2 to 10 models in 8 months. The key enabler was translation automation, which allowed each chatter to handle fans in multiple languages without hiring language-specific staff. Growth was funded by the incremental international revenue from the first 2-3 models.
This agency managed 10 models with 8 chatters by using ForgeFlow translation automation. Without translation tools, they estimated they would need 15-20 chatters to cover the same language markets. The automation reduced the required headcount by roughly 50%.
For this agency, the biggest bottleneck was language coverage. They could onboard new models quickly, but each new model brought fans in 3-5 languages. Without translation automation, they would have needed to hire native speakers for each language, making scaling slow and expensive.
This agency averaged 9,200 EUR per model per month across 10 models after implementing multi-language chatting. Before translation automation, their 2 models averaged 7,500 EUR each. Revenue per model increased because international fans represented untapped spending that was previously lost.
This agency found that scaling languages first (on existing models) was more profitable per euro invested than adding new models. They expanded their first 2 models to 6 languages before onboarding model 3. The international revenue from existing models funded the expansion to new models.
Set up in 3 minutes. 7-day free trial. No credit card required.
Start Free TrialVoice Only - 29 EUR/mo