We are building a SaaS platform that helps small teams index, search and interact with their documents using AI. MVP in development. Contact us to request early access.
What we do
Simple architecture to validate quickly and scale on AWS:
Store documents and assets on Amazon S3
Index vectors using OpenSearch / FAISS
Run inference on EC2 GPU or SageMaker for experiments
Expose APIs through API Gateway / Lambda or ECS
Current stage
MVP development — functional prototype available. Seeking early users for feedback.
AWS gives us the tools and flexibility to iterate fast on infrastructure, experiment with GPU instances, and scale as customers grow.
Demo (coming soon)
Demo coming soon — screenshot / prototype will appear here
Team
Founder & CEO — Founder with background in software engineering and AI research. Responsible for product, backend and model experiments.
Company Overview & Usage Plan
Fenllymei is an early-stage technology startup based in the United States.
We are developing a SaaS product focused on AI-assisted knowledge management, workflow automation,
and knowledge monetization for small teams and businesses.
Our mission is to make it easier for organizations to store, search, retrieve, and monetize their knowledge using AI.
We are currently in the MVP development stage and plan to use AWS as the core infrastructure.
Initial usage will include Amazon S3 for document storage, Amazon EC2 (including GPU instances) and AWS Lambda for model inference and backend services,
Amazon OpenSearch for vector search, and Amazon RDS for structured data. We will also leverage CloudFront and API Gateway to serve a lightweight frontend and public APIs.
Beyond internal knowledge management, our roadmap includes features for monetization — enabling teams to share or sell knowledge-based insights and digital assets,
such as premium content access or subscription-based APIs.
AWS Activate credits will allow us to reduce the cost of early infrastructure and GPU experiments, validate our product-market fit, and onboard early adopters.
As our user base grows, we plan to scale fully on AWS and become a long-term AWS customer.