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by idkwhattocallme 531 days ago
sales ops here. I was just tasked with figuring out how to use AI to use previous quotes to generate new quotes so sales people don't spend so much time creating quotes. Seems like the perfect thing for an agent. Anyone done this?
5 comments

Replace the word “agent” with algorithm and I agree. Why overcomplicate things?
Cause he can say he used AI and get a promotion and the company can put AI on the website and make stock price go up.
The difference is that algorithms have known inputs and “agent” implies a a greater level of adaptability to unforeseen inputs.
That sounds alright, but I'm having difficulty imagining a situation where a business wants to produce a quote with novel element types / parameterizations not yet seen before without a human hand in the loop.
I’m way out in assumption-land, but I’m guessing all quotes would be reviewed by humans, and the goal is to take the drudgery out of first drafts.

For that it would be fine if the AI took a stab at something novel like a faster than usual delivery timeline or higher than usual part tolerances. It might get the economics wrong, but just by including them it would be easier for a human to adjust.

In my pre-sales career, we just did copy and paste for spreadsheets and docs. Most quotes only require finding the nearest recent one and a replace-all for key bits of information followed by careful proof-reading.
Sounds like a poorly thought out requirement. If you are tasked with speeding up the generation of quotes and find that AI can do the job well, that is perfectly reasonable. But if you are told what tool to use to make it happen, whomever tasked you with it doesn't understand that AI is a tool, not a goal. (I say that often enough, I may need to put it on t-shirts.)
For him and his boss and the boss of his boss it may well be a goal to use more AI in business processes. It may be decided in the strategy to spend X% on AI in the next 3 years. So you will do exactly that and not question if it makes sense at all.
I disagree here. It sounds to me like the requirements are clear: Use some AI "agent" to perform this task. That means it should be trained on a particular dataset, and it should perform a particular function. This would be in place of trying to write software to directly do this, just let the AI perform task processing, proposal drafting, document formatting.
>> Anyone done this?

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...

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:

https://www.shipstation.com/

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.
That's why they call it logistics and not shipping.
curious what is this in context to, and which industry? I assume this isn't SaaS sales?