Build & Integrate
Transform business processes with production-ready AI solutions that deliver measurable outcomes, not demos.
Typical timeline from use case definition to production deployment
Why Build Matters More Than Buy
Off-the-shelf AI tools solve generic problems. Your competitive advantage comes from AI that understands your domain, integrates with your systems, and solves your specific workflow challenges. Organizations that build custom AI solutions report higher ROI and adoption rates than those relying solely on horizontal SaaS products.
Our Build & Integrate practice works with engineering leaders, product teams, and business stakeholders to design and deploy AI systems that actually work in production. We focus on Voice AI, intelligent automation, custom copilots, and enterprise integrations—use cases where customization drives measurable value.
This service is ideal for organizations that have identified specific AI use cases, secured budget and stakeholder alignment, and need experienced teams to execute production deployments on tight timelines.
Business Impact
Revenue & Cost Optimization
AI automation reduces operational costs while improving customer experience. Our healthcare patient outreach system recovered $280K annually per provider by reducing no-shows by 42% while cutting staff time by 80%.
Scale Without Linear Headcount
AI voice automation enables 10x capacity increases without proportional hiring. Organizations deploy conversational AI to handle outbound calling, surveys, and customer engagement at scale.
Operational Efficiency Gains
ML-powered field service optimization improved technician utilization by 35% and reduced response times by 40% for a home services company. Intelligent routing and predictive analytics eliminate manual inefficiencies.
Competitive Differentiation
Custom AI capabilities become moats. Unlike horizontal SaaS tools available to all competitors, purpose-built AI solutions encode your domain expertise and create defensible advantages.
How It Works
Our proven 4-phase approach delivers production-ready AI systems in 8-16 weeks, from use case definition to deployed solutions handling real workloads.
Use Case Definition & Discovery
1-2 weeksIdentify high-impact opportunities, define success metrics, understand technical constraints, and prioritize based on business value. We validate feasibility and scope before committing to build.
- • Stakeholder interviews & workflow mapping
- • Technical feasibility assessment
- • Data availability & quality review
- • Success metrics definition (KPIs, ROI)
- • Use Case Definition Document
- • Technical Architecture Proposal
- • ROI Model & Business Case
- • Project Plan & Timeline
Rapid Prototyping & Validation
2-4 weeksBuild functional MVPs to validate technical approach, demonstrate value, and gather user feedback. Prototypes prove viability before investing in production engineering.
- • Core functionality implementation
- • Prompt engineering & model selection
- • User testing with sample data
- • Performance & accuracy validation
- • Functional MVP (demo-ready)
- • Performance Benchmarks
- • User Feedback Summary
- • Refined Requirements Doc
Production Engineering
3-6 weeksScale prototypes to production-grade systems with proper architecture, security, error handling, monitoring, and performance optimization. Built for real-world workloads, not demos.
- • Production architecture implementation
- • Security hardening & compliance
- • Error handling & edge case coverage
- • Performance optimization & testing
- • Production-Ready Application
- • Infrastructure as Code Templates
- • Security & Compliance Documentation
- • Test Suite (unit, integration, E2E)
Integration & Deployment
2-4 weeksConnect with enterprise systems, implement CI/CD pipelines, conduct user training, and roll out to production. We ensure smooth handoff and your team can maintain the system independently.
- • Enterprise system integration (ERP, CRM)
- • CI/CD pipeline setup & automation
- • User training & documentation
- • Phased rollout & monitoring
- • Deployed Production System
- • API Documentation & Integration Guides
- • User Training Materials
- • Monitoring Dashboards & Runbooks
Proven Results
AI-Driven Patient Outreach for Appointment Management
Deployed HIPAA-compliant voice AI system that autonomously calls patients to confirm or reschedule appointments, with seamless escalation to human agents when needed.
42% reduction in no-shows through automated appointment confirmations and intelligent rescheduling
80% staff time savings on manual calling, freeing clinical staff for patient care
$280K annual revenue recovery per provider from reduced missed appointments
AI Voice Automation for Outbound Calling
Built scalable voice AI platform for marketing surveys and customer engagement using ElevenLabs, GPT-4, and WebRTC for real-time conversational AI.
95% conversation success rate with natural voice quality and intelligent conversation flow
10x capacity increase in outreach without adding staff or infrastructure
Real-time WebRTC integration for low-latency voice conversations
What You Receive
Complete production systems with all code, infrastructure, documentation, and knowledge transfer needed for your team to operate independently.
Production Application
- • Deployed AI system handling real workloads
- • Clean, documented source code (full ownership)
- • Infrastructure as Code (Terraform, CloudFormation)
- • CI/CD pipelines for automated deployment
- • Comprehensive test suite (unit, integration, E2E)
Security & Compliance
- • Security architecture documentation
- • Compliance checklists (HIPAA, GDPR as applicable)
- • Authentication & authorization implementation
- • Data encryption (at rest and in transit)
- • Audit logging & monitoring setup
Integration & APIs
- • Enterprise system connectors (ERP, CRM, databases)
- • RESTful API documentation (OpenAPI/Swagger)
- • Webhook configurations & event handling
- • Integration testing suite
- • Rate limiting & quota management
Training & Knowledge Transfer
- • Technical runbooks & operational guides
- • User training materials & workshops
- • Troubleshooting guides & FAQs
- • Architecture decision records (ADRs)
- • Post-launch support (30-60 days)
Engagement Model
8-16 week initial build for typical use cases. MVP in 4-6 weeks. Complex enterprise integrations may extend timeline.
AI engineer, full-stack developer, DevOps engineer. Product manager for requirements and stakeholder coordination.
Product owner (10-15 hrs/week), technical SME for integration support, user representatives for testing and feedback.
How We Measure Success
Risk Mitigation
We understand AI projects carry technical and business risk. Here's how we derisk delivery:
Phased Validation Gates
Decision points after Phase 1 (Use Case) and Phase 2 (MVP) allow you to validate viability before committing to production engineering. No obligation to continue if prototype doesn't meet expectations.
Weekly Demos & Iteration
Show working software every week, not at the end. Continuous feedback ensures we build what you actually need. No big reveals—you see progress in real-time.
Production-First Mindset
We don't build throwaway demos. Every prototype is designed with production in mind—proper error handling, security, and scalability from day one. Prototypes evolve into production systems, not get rewritten.
Full Code Ownership
You own all source code, infrastructure templates, and intellectual property. No vendor lock-in, no proprietary dependencies. Your team can maintain and extend the system without us.
Industry-Specific Use Cases
Healthcare
HIPAA-compliant AI for clinical and operational workflows. Patient outreach, clinical decision support, medical coding automation, and conversational AI for patient engagement.
Financial Services
Conversational banking, fraud detection, loan processing automation, and customer service copilots. Built for regulatory compliance and explainability requirements.
Home Services & Field Operations
Intelligent routing, predictive maintenance, customer communication automation, and ServiceTitan/ Jobber integrations for field service businesses.
Retail & E-Commerce
Personalization engines, demand forecasting, customer service automation, and conversational commerce. Integration with Shopify, Salesforce, and major e-commerce platforms.
Why Choose RPT.ai for AI Development
Production Experience, Not Demos
We've deployed AI systems handling millions of interactions in regulated industries. Our code runs in production, not just in notebooks. We know what breaks, what scales, and what actually works when real users and real data hit your system.
Full-Stack AI Teams
Unlike AI research labs or ML consultancies, we build complete systems—front-end, back-end, DevOps, and AI components. You get a deployed application, not just model code. No handoff gaps between AI and engineering teams.
Voice AI Specialization
Deep expertise in conversational AI, real-time voice systems (WebRTC, Twilio, Plivo), speech-to-text (Whisper), and text-to-speech (ElevenLabs). We've deployed production voice AI at scale.
Rapid MVP to Production Path
Proven methodology to go from concept to deployed system in 8-16 weeks. We don't spend months on requirements—we prototype fast, validate with users, and iterate to production. Speed without sacrificing quality.
Frequently Asked Questions
How much does it cost to build a custom AI solution?
Project costs range based on complexity and timeline. Simple copilots or automation workflows start at lower investment levels, while complex enterprise integrations or multi-modal systems require higher investment. We provide fixed-price quotes after Phase 1 (Use Case Definition) so you have clarity before committing to build.
Can you integrate with our existing systems?
Yes. We specialize in enterprise integrations—ERP (SAP, Oracle, NetSuite), CRM (Salesforce, HubSpot), field service management (ServiceTitan, Jobber), EHR systems, and custom databases. We've built connectors for dozens of platforms and can work with APIs, webhooks, or direct database access.
What happens after deployment?
We provide 30-60 days of post-launch support for bug fixes and minor adjustments. Your team owns the code and infrastructure, so you can maintain it independently. Many clients engage our Operate & Scale service for ongoing monitoring, optimization, and feature development.
Do we need internal AI/ML expertise to work with you?
No. We've successfully delivered projects for organizations with no internal AI expertise. You need a product owner who understands the business problem and can make decisions, plus technical resources for integration support. We handle all AI/ML engineering and train your team on system operation.
How do you handle data privacy and security?
Security and compliance are built in from day one. We implement encryption (at rest and in transit), proper authentication/authorization, audit logging, and follow industry best practices. For regulated industries (healthcare, financial services), we ensure HIPAA, GDPR, or relevant compliance requirements are met. All deployments use your infrastructure—we don't store your data.
What if the AI doesn't perform as expected?
We validate performance during Phase 2 (MVP) before committing to production build. If the prototype doesn't meet success criteria, you can pause or pivot without investing in full production engineering. We define clear KPIs upfront and measure against them throughout the project.
Ready to build production AI?
Schedule a consultation to discuss your use case, review our case studies, and explore how custom AI can deliver measurable outcomes for your business.
No obligation. We'll provide an honest assessment of feasibility and approach.