Systems That Transform Businesses
Every system we build has one goal: move the business forward. Here are the stories behind the architecture.
ONKCO
Lisbon's vibrant restaurant scene spans thousands of establishments, but diners had no intelligent way to discover, compare, or get real-time information about restaurants. Existing review platforms were static and搜索-heavy, not conversational.
Diners spent 20+ minutes researching restaurants across multiple apps and review sites. Information was often outdated — closed restaurants still listed, hours changed seasonally, and menu updates went unpublished. Non-Portuguese speakers faced language barriers accessing local restaurant information. Restaurant owners had no direct channel to communicate real-time updates to potential customers.
We built an AI-native conversational chatbot powered by a real-time knowledge graph of Lisbon's restaurant ecosystem. The system ingested data from multiple sources — official registries, social media, user reviews, and direct restaurant submissions — and maintained freshness through automated verification pipelines. Natural language understanding allowed users to ask complex queries like 'find a vegan-friendly spot in Alfama open late on Sundays.'
Launched as a WhatsApp-first chatbot for maximum accessibility in the Portuguese market. Onboarded 500+ restaurants in the first quarter. Implemented a restaurant owner dashboard for self-service updates. Continuous learning pipeline improved recommendation accuracy by 2.3x over the first 6 months.
Salons Point
A chain of 80+ salons operating across 15 cities needed a centralized platform to replace fragmented scheduling, client management, and operational workflows.
Each salon operated independently with separate booking systems, paper-based client records, and disconnected inventory management. Client retention was declining because there was no centralized view of client history or preferences. No-show rates exceeded 35% with no automated recovery process.
We built a unified platform with an intelligent booking engine that optimized appointment scheduling across all locations based on stylist availability, service duration patterns, and client preferences. ML-based demand forecasting predicted peak periods and optimized staffing. An automated engagement system handled reminders, follow-ups, and rebooking with personalized timing based on client behavior patterns.
Rolled out in 4 phases across 18 months. Each phase covered 20 locations. The migration included digitizing 200,000+ paper client records. Automated SMS and email engagement replaced manual phone-based appointment management.
TheBotBuildr
Small and mid-size businesses needed access to conversational AI but lacked the ML engineering resources to build and maintain custom agent systems.
Building production-grade conversational AI required specialized ML talent, expensive infrastructure, and months of development. Existing no-code chatbot platforms lacked the intelligence and flexibility for real business use cases. Businesses were stuck choosing between expensive custom builds or inadequate off-the-shelf solutions.
We engineered a no-code agent builder platform with pluggable LLM backends, a visual conversation designer, and built-in analytics. The platform abstracted vector databases, RAG pipelines, and model orchestration behind an intuitive interface. Agents deployed on the platform automatically scaled across cloud infrastructure with built-in monitoring and fallback strategies.
Platform launched with 50 beta customers and expanded to 10,000+ agents within 12 months. Average setup time dropped from weeks to 5 minutes. Enterprise tier added for larger deployments with custom model fine-tuning and dedicated infrastructure.