Inspiration

When I started out making my agentic framework for an NGO in Kenya, I noticed there is a lot of need for people over there trying to educate themselves on how to make AI agents. Today's framework is full of node and edges in graphs. It makes agents much more complicated to learn. My plan with the agentic framework is to simplify it to the parts which truly matters, which is making the agent itself.

What it does

My agentic framework NodeAI allows users with limited accessibility to constant electricity make agents directly in their mobile phones. They can easily deploy these agents on Telegram, WhatsApp, X, e.g. AND expose it as API endpoint or even connect it to their Raspberry PI.These allow them to easily let others use their AI Agents to do complex tasks like tool calls/web search

How we built it

I built this over the course of 1 year. It first started out as a WhatsApp RAG chatbot for a Kenya NGO, which audits the financial data of the government.It is now a production ready agentic framework that allow users to use different models through different providers

Challenges we ran into

Many to count, but the productionalizing of NodeAI was really hard.

Accomplishments that we're proud of

NodeAI is being used as the agentic framework for Temporai, a blockchain AI company that makes agents that replicate financial institutes. We have a financial analyst agent, executor agent, and manager agent behind the scenes running things.The agents can be created via endpoints and I've created a small open source library for people to be able to create their own agents using NodeAI.In addition, I have created a mobile app, the development version is accessible via Telegram, which opens up a miniapp for users to create and talk to their agents.

What we learned

A lot

What's next for Let’s learn ai

I am currently onboarding 2 teachers in Kenya to teach their students in the slums of Malthare. Alongside, I hope to work out a deal with the Kenya NGO to get their developers to create on it too.

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