HeyBuddy mobile app development
HeyBuddy mobile app development
HeyBuddy mobile app development
An AI Companion chat app built for iOS on a scalable Serverless backend
An AI Companion chat app built for iOS on a scalable Serverless backend
An AI Companion chat app built for iOS on a scalable Serverless backend
The Brief
Build a strong foundation of an iOS chat app for AI companions that stands out among its competitors in price efficiency and scalability.
The Brief
Build a strong foundation of an iOS chat app for AI companions that stands out among its competitors in price efficiency and scalability.
The Brief
Build a strong foundation of an iOS chat app for AI companions that stands out among its competitors in price efficiency and scalability.
Sound unit economics
LLM API costs are significant and quickly add up. This is especially true in the context of an AI chat interface with frequent interactions. Our goal was to establish a backend infrastructure that remains cost-efficient irrespective of usage volume. At the same time we aimed to optimise LLM prompting, while balancing the contextual information an LLM needs for genuine dialogues.
Sound unit economics
LLM API costs are significant and quickly add up. This is especially true in the context of an AI chat interface with frequent interactions. Our goal was to establish a backend infrastructure that remains cost-efficient irrespective of usage volume. At the same time we aimed to optimise LLM prompting, while balancing the contextual information an LLM needs for genuine dialogues.
AI that feels human
Often chatbots have an "at your service" attitude. This is great for utility workers, but conversations aren't one-sided, and require a kind of push and pull. Both conversation partners should be able to initiate the conversation and introduce topics freely. Our goal was to create this calibre of AI. One that has a point of view and can talk to you at any time they wish.
AI that feels human
Often chatbots have an "at your service" attitude. This is great for utility workers, but conversations aren't one-sided, and require a kind of push and pull. Both conversation partners should be able to initiate the conversation and introduce topics freely. Our goal was to create this calibre of AI. One that has a point of view and can talk to you at any time they wish.
The Serverless Architecture
We built a native iOS app written in Swift, connected to a fully serverless backend on AWS that will scale with use on demand. We offload operational complexity, and ensure our backend can scale with unknown demand by choosing a serverless approach to building our platform. All of this while having a pay per use cost structure for the backend, so we’re not paying for resources that aren’t being used. The architecture enables us to rapidly deploy discrete instances of the application for development and testing purposes, and in the future it will unlock the ability to provide HeyBuddy as a white labeled dedicated platform for B2B customers.
The Serverless Architecture
We built a native iOS app written in Swift, connected to a fully serverless backend on AWS that will scale with use on demand. We offload operational complexity, and ensure our backend can scale with unknown demand by choosing a serverless approach to building our platform. All of this while having a pay per use cost structure for the backend, so we’re not paying for resources that aren’t being used. The architecture enables us to rapidly deploy discrete instances of the application for development and testing purposes, and in the future it will unlock the ability to provide HeyBuddy as a white labeled dedicated platform for B2B customers.
The Serverless Architecture
We built a native iOS app written in Swift, connected to a fully serverless backend on AWS that will scale with use on demand. We offload operational complexity, and ensure our backend can scale with unknown demand by choosing a serverless approach to building our platform. All of this while having a pay per use cost structure for the backend, so we’re not paying for resources that aren’t being used. The architecture enables us to rapidly deploy discrete instances of the application for development and testing purposes, and in the future it will unlock the ability to provide HeyBuddy as a white labeled dedicated platform for B2B customers.
Technical Highlights
Fully managed GraphQL API via AWS AppSync including real time updates
A normalised cache in a local SQLite database on the client
Integration with OpenAI and Amazon Bedrock enabling multi-model inference
DynamoDB implementing Single Table Design for performance and cost
Event Driven architecture with Amazon SNS and Amazon EventBridge
Data Lake implemented with Kinesis, AWS S3 and Amazon Athena
Defined using Cloud Development Kit (CDK), allowing consistent deployments and flexibility
The App
We designed and developed a native iOS chat app for AI companions. The robust backend implementation and intuitive frontend design enables us to offer an immersive chat experience.
The App
We designed and developed a native iOS chat app for AI companions. The robust backend implementation and intuitive frontend design enables us to offer an immersive chat experience.
The App
We designed and developed a native iOS chat app for AI companions. The robust backend implementation and intuitive frontend design enables us to offer an immersive chat experience.
An intuitive chat experience
The chat interface shares a user experience similar to other communication platforms such as Whatsapp and Telegram. All messages are updated in real time, whether the app is open or closed.
A catalogue of curated AI companions
Users can discover new companions in a swipe-style interface. Each companion has a detailed profile and is built carefully according to their unique persona.
A catalogue of curated AI companions
Users can discover new companions in a swipe-style interface. Each companion has a detailed profile and is built carefully according to their unique persona.
An AI that feels real
AI companions aren't limited to respond to messages from users. They proactively send thoughts of their own, drawing on previous dialogue. In conversation they go beyond just responding to users, towards a deeper understanding of the conversation.
An AI that feels real
AI companions aren't limited to respond to messages from users. They proactively send thoughts of their own, drawing on previous dialogue. In conversation they go beyond just responding to users, towards a deeper understanding of the conversation.