Built by a marketer who manages multi-million dollar ad budgets. Not by a developer who built a chatbot.
Most AI companies are started by engineers. They build impressive technology and then go looking for a business problem to attach it to.
This company started the other way.
I'm Cesar Taveras. I manage multi-million dollar Meta Ads budgets for Fortune 500 language learning brands — user acquisition campaigns across iOS and Android that drive tens of thousands of installs every month. I live inside dashboards, attribution models, and conversion data.
I didn't start an AI company because AI is trendy. I started it because I kept watching the same problem destroy marketing ROI at company after company: slow follow-up.
Businesses spend real money getting leads to raise their hand. Then those leads sit in a CRM for hours — sometimes days — before anyone responds. By then, the lead is cold, the competitor has closed them, and the ad spend is wasted.
I built a system that fixes that. AI assistants that respond in seconds, qualify leads based on real sales criteria, and book appointments automatically. Not chatbots. Not auto-responders. Real conversational AI that handles objections, adapts tone, and closes.
That's what this company does. Performance marketing meets AI automation.
Why the builder matters.
I spend real budgets. Multi-million dollars in ad spend across Meta, managed daily. Not a case study from 2019. Today.
I understand the full pipeline. From creative strategy to lead gen to qualification to close. AI is one piece. I see the whole picture.
I optimize for business outcomes. Not "engagement." Not "conversations started." Booked appointments. Closed deals. Revenue.
I know what breaks. When your AI assistant gives a wrong answer at 2 am, I know how to find it, fix it, and make sure it doesn't happen again. Because I've been debugging campaigns at scale for years.
The AI assistants I build don't just respond. They respond the way a trained sales rep would — because they're configured by someone who knows what a trained sales rep sounds like.
Not translation. Fluency.
I was born bilingual. English and Spanish aren't two separate skills for me — they're one brain that switches automatically based on who I'm talking to.
That's exactly how the AI assistants work.
When a customer messages in Spanish, the assistant doesn't run the message through a translation layer. It thinks in Spanish. It responds with the right formality, the right tone, the right cultural context. It knows that "usted" and "tu" matter. It knows that a WhatsApp conversation in Mexico sounds different than one in Miami.
When a customer switches mid-conversation — starts in English, drops into Spanish — the assistant follows. Naturally. Because that's what bilingual people do.
62 million US Hispanics represent $2.8 trillion in purchasing power
Most businesses either ignore this market entirely or serve it with translated English that sounds robotic
Hispanic customers who feel understood become loyal customers. They refer family. They stay.
Your "bilingual" chatbot is a translation API. This is a bilingual sales system.
Three steps. No fluff.
Diagnose
We look at your current lead flow. Where leads come from. How fast they get a response. What happens after first contact. Where the pipeline leaks. You get a clear diagnosis: here's what's broken, here's what it's costing you, and here's the fix.
Implement
We build your AI assistants. Trained on your business — your products, your pricing, your objection handling, your qualification criteria, your booking rules. We connect them to your channels and your CRM.
Optimize
AI assistants get better over time. We monitor conversations, adjust responses, refine qualification criteria, and expand to new channels as the system proves itself. Monthly performance reviews with real data — not vanity metrics.