Sobre

Company Overview Atomicat is Brazil's leading digital marketing platform with 10,000+ active users. We're building "MIA" - a sophisticated AI assistant that will revolutionize how users interact with our platform. This is a strategic project requiring an agency with deep AI expertise and enterprise software experience. Platform Context Established SaaS with Next.js frontend and Firebase Authentication Multi-database architecture (Firestore, MongoDB, BigQuery) Complex features: sites, pages, projects, forms, quizzes, funnels, analytics, and Elementor-like page builder Serving Portuguese and Spanish-speaking markets Project Vision: Three Progressive Phases Phase 1: Intelligent Knowledge Assistant (Months 1-2) * Build an AI that understands everything about our platform and each user's data * Answer questions like "How many sites do I have?" or "What's my best performing page?" * Provide insights from cross-database queries * Understand context from user's historical data * Support Portuguese, Spanish, and English Phase 2: Action-Capable Assistant (Months 3-4) * Transform MIA into an operational powerhouse * Execute CRUD operations across all platform features * Implement confirmation workflows for critical actions * Build rollback mechanisms and audit logging * Create intelligent suggestions before actions Phase 3: Business Intelligence Advisor (Months 5-6) * Evolve MIA into a growth partner * Analyze performance trends and suggest optimizations * Provide competitor insights and market intelligence * Generate actionable business recommendations * Predict user needs and proactively offer solutions Why We Need an Agency, Not a Freelancer This project requires multiple specialists (AI/ML engineers, backend developers, data engineers, UX designers). Proven methodology for AI project delivery. Risk mitigation through team redundancy. Quality assurance processes for production AI. Ongoing support and iteration capabilities. Required Agency Capabilities Core Team We Expect: AI/ML Lead Engineer - LLM integration, RAG implementation Backend Architect - Microservices, real-time systems Data Engineer - Multi-database synchronization, ETL pipelines Frontend Developer - React/Next.js chat interface DevOps Engineer - Scaling, monitoring, deployment QA Specialist - AI testing, edge cases Project Manager - Agile delivery, stakeholder management Technical Expertise Required: AI/ML Stack: Production experience with GPT-4, Claude, or similar LLMs RAG (Retrieval-Augmented Generation) architectures Vector databases (Pinecone, Weaviate, Qdrant) LangChain or similar orchestration frameworks Prompt engineering and fine-tuning Hallucination prevention strategies Infrastructure & Architecture: Microservices architecture design Real-time data synchronization across multiple databases Event-driven architectures (Kafka, RabbitMQ) Caching strategies (Redis, Memcached) WebSocket/SSE for real-time responses Kubernetes or similar for container orchestration Security & Compliance: Multi-tenant data isolation Role-based access control (RBAC) Audit logging and compliance Data encryption at rest and in transit GDPR/LGPD compliance Specific Deliverables Discovery Phase (Week 1-2): Architecture design document Technology stack recommendations Risk assessment and mitigation plan Detailed project timeline Infrastructure cost projections Phase 1 Deliverables: Knowledge ingestion pipeline Multi-database connector system Context management framework Basic chat interface Real-time query system Portuguese/Spanish language support Phase 2 Deliverables: Action execution framework Confirmation and rollback systems Audit logging infrastructure Admin dashboard Safety mechanisms API documentation Phase 3 Deliverables: Analytics integration Recommendation engine Predictive models Performance dashboards Business intelligence reports Complete documentation What Your Proposal Must Include 1. Agency Credentials Years in business and team size Relevant certifications (AWS, Google Cloud, etc.) Previous AI assistant projects for SaaS platforms Client references we can contact 2. Case Studies (Minimum 2) Provide detailed case studies showing: * Problem definition and solution approach * Technical architecture diagrams * Performance metrics and results * Challenges faced and how you solved them * Links to live products (if possible) 3. Technical Approach Detailed explanation of: Proposed architecture (with diagrams) Technology stack and justification Data synchronization strategy Scaling approach for 10,000+ users Security implementation Handling of Portuguese/Spanish languages 4. Team Composition Specific team members assigned Their roles and expertise Time allocation (% dedication) Location and time zone coverage Communication structure 5. Project Management Methodology (Agile, Scrum, etc.) Communication cadence Progress tracking tools Risk management approach Quality assurance process 6. Pricing Structure Fixed price vs. time & materials justification Payment milestone breakdown What's included/excluded Post-launch support options SLA terms Budget & Timeline Budget Range: $50,000 - $150,000 USD Discovery Phase: $5,000 - $10,000 Development Phases: $40,000 - $120,000 Support & Maintenance: $5,000 - $20,000 Timeline: 5-6 months for full implementation Preferred Model: Fixed-price milestones with clear acceptance criteria Evaluation Criteria We'll evaluate agencies based on: Technical Expertise (30%) - Depth of AI/ML experience Relevant Experience (25%) - Similar projects delivered Team Strength (20%) - Quality and availability of team Approach & Methodology (15%) - Clarity and feasibility Value & Budget (10%) - ROI and cost-effectiveness Red Flags We're Avoiding Agencies with no production AI experience Over-promising unrealistic timelines No experience with multi-database architectures Can't explain hallucination prevention No Portuguese/Spanish language experience Lack of proper security credentials Outsourcing without transparency Ideal Agency Profile 5+ years focused on AI/ML projects Has built enterprise SaaS AI assistants Strong presence in LATAM or Portuguese-speaking markets Microsoft/Google/AWS partnerships ISO certifications for security Demonstrated thought leadership in AI Post-launch support capabilities Critical Questions for Agencies In your proposal, address: How will you prevent MIA from exposing one user's data to another? Your approach to real-time synchronization across Firestore, MongoDB, and BigQuery? How will you handle Portuguese/Spanish language nuances? Strategy for managing API costs at scale? How will you ensure MIA doesn't hallucinate user data? Your approach to testing AI systems? How to Apply Start your proposal with "Our agency has delivered enterprise AI" and include: Your best AI assistant project - with metrics and architecture Team composition - specific people who will work on MIA Preliminary architecture - high-level diagram of your approach Risk assessment - top 3 risks you foresee and mitigation Two references - from similar projects Availability - start date and capacity commitment What We Provide Complete platform documentation API access and testing environments Direct access to CTO and product team Sample data sets for development Clear acceptance criteria Fast feedback cycles Long-term Partnership Opportunity This project will lead to ongoing feature development, maintenance and optimization contract ($10,000-20,000/month), additional AI projects across our platform, potential equity participation for the right partner. Interview Process Initial proposal review (3 days) Technical deep-dive call (90 minutes) Team presentation and Q&A Reference checks Final negotiation Important Notice We're looking for a true AI partner, not just a development shop. You should be excited about pushing the boundaries of what's possible with AI in SaaS. If you're just looking to build another chatbot, this isn't the right fit. Competitive Advantage The selected agency will become our exclusive AI partner and will be featured in our case studies and marketing materials, providing significant exposure in the LATAM market.