AI Voice Assistant for Everyday Tasks
The platform turns everyday tasks into voice-activated commands, connecting users with AI that books flights, finds deals, and delivers results across phone, SMS, and apps — powered by real-time research.
Our Collaboration Story
The project began with an ambitious idea: create a voice assistant that fits into daily life – something you could call or that could call you back. More than just a chatbot, this assistant needed to remember past conversations, take notes, and carry out tasks during live interactions.
That idea became the personal assistant platform, which supports phone calls, SMS, and a mobile app. Users speak to it directly to handle tasks such as finding the cheapest flight or setting reminders, while the request is processed in the background. Once the task is completed, the result is sent back through whichever channel the user prefers. Our work focused on building a system that feels natural to talk to, remembers context, and responds in real time, making the assistant feel less like a tool and more like a thoughtful companion.
Challenges
Multi-Channel Interaction
Needed a system to process user tasks via voice, SMS, and app inputs without delay or confusion.
Voice Call Integration
Required smooth integration with telephony systems (Twilio, SIP) to allow real-time conversations with the AI assistant.
Real-Time Task Execution
Had to research and complete user tasks immediately through AI without noticeable lag.
Scalable Deployment
The platform needed a backend capable of rapid scaling to handle spikes in concurrent calls and requests.
Voice Assistant: Features Breakdown
Voice-Activated AI Assistant
Users interact with the platform by speaking directly to the platform via phone calls, enabled through Twilio and SIP integration.
Multi-Channel Task Delivery
The platform receives tasks via voice, SMS, or mobile app and sends back results through the user’s preferred communication method.
Real-Time AI Research and Execution
Powered by a large language model (LLM), the assistant conducts live research and completes tasks such as finding flight options or local services.
Personalized Task Management
The assistant adapts responses based on user preferences, history, and task context to deliver more accurate and helpful outcomes.
Cloud-Native Scalability
Deployed on Kubernetes, the platform adjusts automatically to handle growing numbers of users and tasks without service interruptions.
Cross-Platform Accessibility
The assistant is available across web, mobile, and traditional telecom channels, making it accessible anytime, anywhere.
Real-Time Web Search & Research
The assistant can search the web live to answer user queries.
Personal Notes & Summaries
During a conversation, users can request the assistant to send notes or summaries via SMS.
Flexible Interaction Modes
The assistant supports both SMS communication and voice interruptions, allowing users to switch between input methods naturally during a conversation or task.
Solutions
01
Unified Task Processing Engine
Built a system to receive, interpret, and execute tasks across multiple channels, with real-time status tracking.
02
Telephony-Connected AI
Integrated Twilio and SIP protocols to enable users to interact naturally with the AI through voice calls.
03
LLM-Driven Research Capabilities
Connected the platform to a large language model (LLM) to research tasks dynamically and deliver personalized results.
04
Kubernetes-Based Scalability
Deployed the platform with Kubernetes, allowing fast scaling based on usage patterns without downtime.
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Max Tatarchenko
CTO with 14 years of experience in solution architecture and engineering, specializing in blockchain and smart contracts. His broad expertise drives innovation across diverse technology projects.
CTO with 14 years of experience in solution architecture and engineering, specializing in blockchain and smart contracts. His broad expertise drives innovation across diverse technology projects.
PLANNING A NEW PRODUCT?
