Tender Bidding: Key Steps, Process, and Best Practices (2026)

Transcript is auto-generated and may contain minor errors.

Hey, have you ever wanted to use Gemini for your AI go no go analysis? We're going to jump into it today using Gemini to do our tender analysis to understand if we want to bid on this tender or not. I'm going to be using Gemini Flash 2.5 Pro which currently available on the paid Gemini plan. Uh, and we're going to be looking at a tender actually from the Australian government. Uh, so this one specifically is the ATO, the Australian Tax Office. And interestingly enough, this tender is for a coding assistant. So like an AI coding software SAS application. I use an AI coding SAS application that I love to use every day and that's cursor. So we're going to look at cursor who have an enterprise plan. So making a pitch for the likes of the ATO's and we're going to look at this publicly available atto tender and

whether cursor should bid on it. So we're going to be using our AI go no go analysis tool with Gemini. So let's jump into it and and wait until the end because the results of the AI go nogo analysis may actually surprise you. So, first of all, um I've got this prompt, and I'm going to leave a Google doc uh or page where you can download this uh prompt and then customize it for your business down in the description below. Uh but of course, um you know, I you can customize to your heart's content. When we're prompting, it's really important to a make it contextual to our business, which is where we have the inputs here. So, I'm going to enter the cursor URL. Uh we have our persona. So effectively that's telling the Gemini flash 2.5 what you know what kind of uh person is going to be what skill set should it have what context should it have when it answers this question in this case it's an expert RFP manager uh then we have

our context and objective so what are we asking the prompt effectively to do what are the instructions and then what should the output be so from this case I want a comprehensive document detailing against my red flags or amber flags or green flags around whether cursor should bid on this tender or not. So, I'm going to just, you know, copy and paste that prompt, chuck it in here. Then, uh, really cool thing is I'm actually going to turn on deep research. So, deep research is a tool readily available in a lot of your uh common LLMs whether that's uh Gemini as I'm showing here, Chat GPT or Claude. Gemini's deep research can be used not only to search the web but also search your documents. So, with Gemini, you can upload up to 10 documents. And for this, I'm actually going to be using my own go nogo

template. The go no-go template. Again, I'll chuck a link in the description below where you can download that from our website at autoirfp.ai/d downloads, but effectively this will have information. And this is my go no-go framework. What I'd recommend is downloading the template, changing the go no-go framework uh to make it more relevant for your business as needed. But it's a good starting point. Uh for for instance, this really focuses on RFP origins and relationship. uh it looks at resource requirements from our team and then effectively it gives you a scoring matrix and depending on that scoring matrix matrix should tell me whether we should proceed or not uh as well and it has all the different information you can like play around with your hearts content it's just an Excel spreadsheet um but really useful for your go no-go decision framework all righty so jumping back uh I've turned my deep research on and now I'll upload my documents from drive. And so

here are my tender documents. Uh just clicking shift, I'm just going to select all the relevant ones. I can only upload maximum of 10 documents. So I'm actually going to upload the original tender documents, not the indenments. We'll up upload those later. So I'm going to insert those documents. And there's one other document I want to add from my drive. And that actually is that go no-go decision template. So now I have my go no-go decision template. I've got my atto documents uh for the tender and I've got my prompt of what I want Gemini Flash 2.5 Pro to do for my AI go no-go analysis strap in it's pretty cool what you're actually going to see here as well all my tender documents and it's deep researchers on but before I submit this I want to make sure here in the prompt that you can download below is I'm going to update this information so uh tender documents uh see attached As you can see, I've attached them. And in terms of the company URL, well, here

I just want to make sure I I'm just going to enter cursor here. This is a AI coding assistant tender for the Australian tax office. And you know, in this example, we're being cursor. I do not work at cursor. I work at autofp.ai. But for my example, I click submit. And then what I really like about Gemini is it's going to provide a research plan for my AI go no-go analysis. So with that plan, it'll provide a lot of details in terms of the steps it's going to take to try to answer my prompt. And then I can actually edit that plan if I'd like to. And here we have our plan from Gemini. So clicking through I can go through I can read this information. First it's going to browse the cursor docs and all the information regarding cursor. It's going to go and analyze all the tender documents and then it'll make its way through and start to answer my go no-go questions. So, what I recommend here again is a edit the analysis template, the go no-go decision

template. Make that really relevant for your company and when you decide to bid or not to bid for tenders uh and RFPs. And then second is uh in this prompt, make sure you update what questions you're asking. if there's any specific questions like red flags you want for cursor. It might be well cursor doesn't do uh on premise hosting. So want to make sure that's flagged and then uh there's the information and then I can click start research and Gemini flash is going to start doing our AI go no-go analysis. All righty. I've given it some time. time it probably took oh jeez uh maybe about 10 minutes all up which is what you expect for the deep research uh especially for something that goes through you know 10 different tenor documents probably hundreds of pages and uh uses the organizational context that we provide it in the website of cursor to then run a go nogo analysis against that go no-go decision template. So jumping into it, uh before I show kind

of the output, what you have here for deep research is you can look at the thoughts. And so this kind of explains or at least in some cases LMS do hallucinate their thoughts, but in this case we can hopefully trust it and see that what it kind of looked to and what it did uh in completing that analysis. So it looked at the different websites. It then uh looked at the research uploaded folder files and then use that against the decision template to then try to provide an overall go no go as well. Here are the sources it used. Again, it can refer to those Google Drive documents I provided which is really powerful for that Gemini has such a good integration. Obviously, probably no surprise with Google Drive. And then scrolling up here is our analysis. So Gemini has provided an AI go nogo analysis based off the ATO tender documents for an AI coding assistant which we've mocked up as cursor.com to

reply and say should we bid on this where AI go nogo is powerful is it does help with that cursory first look whether this is worth it to look what information should I understand before diving to it further um as well certification gaps um you know goes through all the different information there and effectively it's going through that spreadsheet the decision template that we have for our go no-go analysis you can see here strategic alignment competitive landscape commercial viability legal and security and it's now providing that information there as well so it's it's kind of looked over those different clauses uh I mean here if that's true the the clause grants the AT the right to terminate the contract at any time for any reason for its own convenience that's a pretty you usually don't want that in your legal contracts with the three year plus one plus1 contracts. That's pretty rude. Uh but yeah, anyway, you can have a look at that and uh obviously make up your own mind as well for uh the different information. Uh then you have kind of the different scoring of waiting and that's the powerful thing about a go no-go decision

template is to um use it as a I guess take the emotion out of RFP response. You might have an enterprise AE salesperson run up to you and say I have to bid on this RFP. we have to do it. Uh and if you kind of boil it down to just numbers and what the scoring is, then you can make a more informed decision hopefully without the emotion of that uh as well. Uh and then so it kind of does that scoring for me that I provide in the spreadsheet. And then that's why it's a no-go is because the weighted score was 44.3%. Uh and so told me to go not go for it. I can actually then expand on this. And in the drive there's actually three indentments. And so uh I'll say uh please find attached I'm typing here. Please find attach uh some addendments for the tender and use that to update the

the analysis. So and that's a great thing. You have this chat. You might have Q&A later. You might have addenments. might have uh mistakes in the original tender that are provided to you and with that chat history you can then come back to it and provide additional documents to then do the further analysis with the context of your original. Now with uh LLMs you will uh hit like a token limit for that. For instance I I believe Gemini's token limit is around 1 million uh for Gemini 2.5 Flash Pro. Uh so it's a very fast model but effectively it's going to start start forgetting the original context that you provided. Uh and so you need to be cautious of that. It's good for initial we think of this AI go no go analysis initial cursory first look. It's it's not going to be our full in-depth look. Effectively it's it's saving me time of places I need to look at uh and so on before we kind of get into it. So I it's not going to replace the human to do the go no-go. This is going to help uh help the human do the

go no-go as well. Hope that this video was really useful for you on how to do an AI go nogo analysis with Gemini Flash 2.5 Pro. Uh you can use this for all your tendering needs. Uh make sure to still have the human in the loop. AI can hallucinate. And then final just that last privacy and security uh comment on making sure that the training is turned off. This is a that you're using a paid subscription. Do not upload private RFPs into an LLM because that maybe then you send into uh training data uh without you make sure that the training is turned off. You're paying for your subscription uh as well. Uh, and then yeah, this one, my example is a public tender, uh, but you can, of course, uh, use it as well. So, I'm Rob from Auto RFP. Uh, we're actually an AI RFP software. We actually have a go no-go analysis feature really similar to

what I showed you before, but a lot less of the leg work uh in our software that also uses Gemini Flash 2.5, which is why I had a lot of confidence that could kind of handle the large documents that you would often find in tenders. So yeah, if you're interested, find us at auto rfp.ai. You can pick a book a demo and learn more about us as well. I thanks.