We sell maker and STEM education electronics, but the profit margins on products like Raspberry Pis, Micro:bits, and Arduinos are, well, pretty slim. This has pushed us to become extremely efficient; so much so that we ended up creating our own AI-agent-based ERP platform called Koi [1]
In essence, our work is built on the shoulders of giants like OpenAI’s Assistant API, Anthropic and Rails.
One of our standout demos is that certain objects (Orders, Quotes, Supplier Orders, Customers etc) in our database are assigned their own email addresses (using Rails' Action Mailbox[2]). Emails can be forwarded directly to these objects-whether it’s an order, a customer, or a supplier order.
From there, our agent, “Koi,” automatically extracts relevant information from emails and takes appropriate actions. For example, Koi can create a quote, attach a purchase order PDF to an order, or extract tracking information from supplier shipping confirmation emails to provide live tracking updates.
It also works the other way around; you can ask Koi to send a customer their tax invoice or inform them that a product they were interested in is out of stock, seamlessly handling typical customer service tasks.
Previously, we integrated speech-to-text functionality using the Whisper API, which made for an impressive demo.
Now, we’re taking it a step further by rebuilding our speech system to leverage OpenAI’s new WebRTC-based Real-time API. The key advantage here is that it comes with function calling support[3]. We already support a variety of automation features using barcodes[4], allowing users to scan a barcode and have Koi perform specific actions. This has proven to be an ideal area in the application to integrate tool use with the real-time API, creating even more powerful and efficient workflows.
Our ultimate goal is to integrate this system with Bishop, our product-picking robot[5].
Your spiel here is much better than the website you've linked.
What you've linked sounds like you're selling a glorified shipping label printer.
I'm curious how this differs from standard TA/TMS systems that have been around for decades. I work in the space and there are plenty of TA/TMS systems that print shipping labels and fulfil orders, that update stock levels and send out tracking emails + SMS messages, integrate with carriers for shipment updates, that integrate with Shopify, eBay, Etsy, big commerce, etc.
They didn't need AI to do any of that. What's the advantage you're finding?
Here's an example that seems to operate in Australia:
Shipping is a fraction of what the system does. To completely automate shipping you need an understanding of inventory etc. To do automated customer service, you need knowledge of shipping, inventory etc.
Yes, we have and more!
We sell maker and STEM education electronics, but the profit margins on products like Raspberry Pis, Micro:bits, and Arduinos are, well, pretty slim. This has pushed us to become extremely efficient; so much so that we ended up creating our own AI-agent-based ERP platform called Koi [1]
In essence, our work is built on the shoulders of giants like OpenAI’s Assistant API, Anthropic and Rails.
One of our standout demos is that certain objects (Orders, Quotes, Supplier Orders, Customers etc) in our database are assigned their own email addresses (using Rails' Action Mailbox[2]). Emails can be forwarded directly to these objects-whether it’s an order, a customer, or a supplier order.
From there, our agent, “Koi,” automatically extracts relevant information from emails and takes appropriate actions. For example, Koi can create a quote, attach a purchase order PDF to an order, or extract tracking information from supplier shipping confirmation emails to provide live tracking updates.
It also works the other way around; you can ask Koi to send a customer their tax invoice or inform them that a product they were interested in is out of stock, seamlessly handling typical customer service tasks.
Previously, we integrated speech-to-text functionality using the Whisper API, which made for an impressive demo.
Now, we’re taking it a step further by rebuilding our speech system to leverage OpenAI’s new WebRTC-based Real-time API. The key advantage here is that it comes with function calling support[3]. We already support a variety of automation features using barcodes[4], allowing users to scan a barcode and have Koi perform specific actions. This has proven to be an ideal area in the application to integrate tool use with the real-time API, creating even more powerful and efficient workflows.
Our ultimate goal is to integrate this system with Bishop, our product-picking robot[5].
[1] https://www.koi.app
[2] https://guides.rubyonrails.org/action_mailbox_basics.html
[3] https://platform.openai.com/docs/guides/realtime-model-capab...
[4] https://help.koi.app/article/54-barcode-driven-fulfillment
[5] https://piaustralia.com.au/pages/the-raspberry-pi-that-ships...