FurFriend — pet care on Bee

Inspiration

We noticed that many pet owners struggle to track complex medical care schedules and behavioral needs across different platforms. We wanted to show how the Bee track could host a specialized, AI-driven assistant that makes pet ownership less stressful.

What it does

FurFriend automates pet care tasks by tracking health reminders and providing instant behavioral advice. It uses the Bee surface interface to process user queries and deliver real-time insights based on specific pet data profiles.

How we built it

We used Python as our primary language and deployed our logic via aws-lambda for serverless execution. We integrated the strands-agents-sdk to orchestrate workflows and utilized amazon-bedrock to handle natural language processing tasks.

Challenges we ran into

We initially struggled with mapping the specific pet data schemas to the Amazon Bee interface requirements. We also had to refine our prompts in Bedrock to ensure the pet advice remained both safe and accurate.

Accomplishments that we're proud of

We are proud of successfully integrating the strands-agents-sdk with the Bee environment to create a responsive agent. Seeing the pet care workflow autonomously was a major milestone for our team.

What we learned

We learned a lot about how to structure agentic workflows within the Amazon Bee track constraints. We also gained deep experience in optimizing aws-lambda functions for low-latency AI-driven applications.

What's next for FurFriend

We plan to add advanced image recognition capabilities for skin health checks using AWS models. We also hope to integrate with wearable pet devices to provide even more accurate health data through Bee.

Built With

• amazon-bedrock
• amazon-bee
• aws-lambda
• furfriend
• pet
• strands-agents-sdk