The initial version of Summer AI struggled with a core requirement: Sound Natural.

Conversations felt robotic and unnatural, making it hard for businesses to trust the platform with their customer interactions. The system also lacked flexibility - adjusting voice tone, personality, or conversation flow required significant effort, and the system couldn't scale to handle multiple clients with different needs.

The client needed a rebuild that could deliver natural conversations while remaining flexible enough to customize for each business. Before committing to a full buildout, they wanted validation: an MVP that proved the new approach could solve these problems.

Project management Approach

Given the complexity of building a complete AI voice agent platform, we structured the engagement around rapid iteration and close collaboration.

Initial Milestone

• From the start, we set a fixed 1-week milestone to validate the AI voice agent solution using Retell AI. It helped us confirm technical feasibility and product direction.

1-Week Sprints

• We then decided to work in 1-week sprints, allowing us to validate features quickly and adjust our approach before investing heavily in any single direction. The client was deeply involved in sprint planning, reviews, and backlog grooming, guiding priorities and key decisions across the product.

• When larger features required deeper focus, we extended to 2-week sprints while maintaining the same collaborative rhythm.

Quick Feedback Loops

• Daily syncs kept us aligned and caught blockers early. This allowed us to validate each component incrementally and adjust when needed, rather than building for weeks and discovering issues late.

Testing and Iteration

• Testing and bug-fixing happened continuously throughout each sprint alongside development, ensuring quality was maintained as new features were added.

Engineering approach

The goal of our team was to validate the solution quickly with real users while building a foundation that could scale. Our engineering approach balanced these priorities: move fast to prove the concept, but build the architecture for the long term.

Modular Architecture

• We adopted a modular architecture from the start, ensuring key components could be swapped or extended as the product evolved.

• Core modules - voice engine, billing, data storage, and analytics - remained loosely coupled, allowing a future transition to other frameworks with minimal disruption.

Rapid Validation with Retell.ai

• We began by integrating Retell.ai for the initial voice agent implementation, allowing us to validate the product concept quickly and gather user feedback early.

• From there, we extended its capabilities rather than rebuilding from scratch. Features like SMS follow-ups, appointment scheduling, and context-driven agent instructions were layered on top of the base voice experience.

Fast Frontend

• The product's frontend, built in Next.js, emphasized speed and clarity with a responsive dashboard providing insights into call metrics, transcripts, and billing information.

We delivered a complete platform with intelligent voice interactions, business automation, and insights.

Voice & AI Engine

• Modular Architecture - Built on Retell.ai with abstractions in place to support future migration to LiveKit or other communication frameworks.

• Knowledge-Aware Agents - Connected agents to a knowledge base for contextual, informed responses.

• Agent Customization -  Businesses can tailor agent name, greeting, behavioral instructions, and questions to match their business.

Automation & Integrations

• Automated Onboarding - Collects details from the company's website and Google Business Profile, then parses, structures, and presents them for review and customization.

• SMS Messages - Extended the functionality with in-call actions like SMS follow-ups.

Dashboard & Analytics

• Responsive Dashboard - Intuitive Next.js interface optimized for desktop and mobile, managing analytics, calls, and billing.

• Post-Call Analysis -  Automated pipeline evaluates calls and tags insights for intelligent filtering and grouping.

• Interactive Call Player - Jump directly to key conversation segments with integrated recording and transcript navigation.

Billing

• Flexible Billing - Multi-tiered usage-based system with pro-rated adjustments and automated overage charges.

✔️ Rapid Validation - We validated the Retell.ai solution in 1 week by integrating the AI voice component into the existing architecture, proving the concept before full development began.

✔️ Speed to Market - From first commit to live alpha in 6 weeks, getting the rebuilt platform in front of real users quickly.

✔️ Early Traction - 2 paying clients signed on within 2 weeks of launching paid plans, demonstrating immediate product-market fit.

✔️ Technical Performance - Call summaries and classifications delivered with high accuracy, proving the AI could handle real customer interactions reliably.

✔️ Validated Foundation - The modular architecture supported early growth while maintaining stability, confirming both market need and technical scalability.