Choosing the Best RFP Software for Finance Teams 2026

Transcript is auto-generated and may contain minor errors.

Hey, we're going to jump into the best due diligence questionnaire software that's currently on the market. We're going to look at those that are leveraging the latest AI as well as some of the more legacy DDQ software providers and how they all help you automate your DDQs. So, let's jump into it. Now, you're probably an investment fund manager or someone from security or compliance getting these constant questions asking a lot of the same questions. You have an answer buried somewhere. You know that on the website or in SharePoint, you have information on fund for and the relevant investments in that fund and all the other information that this DDQ is asking for, but it just takes so much time to find that answers. If that's

you, then DDQ's software and automation can be a real lifesaver to help you get your weekends back and automate the mundane that is DDQs sometimes. So, first of all, what is a due diligence questionnaire? Now, I think everyone here would have a solid understanding, but just in case, a DDQ stands for due diligence questionnaire. They come in various industries, but most common is a managed investment fund where effectively your institutional investors and limited partners would provide you a due diligence questionnaire for you to fill out to have that LP invest in one of your funds. The aim of the DDQ, a little bit different to an RFP, is you're trying not to get disqualified, which makes them very regulatory and complianceheavy. And in financial services need to make

sure that the information is correct. And often this involves subject matter experts from legal, marketing, investor relations all helping out on this due diligence questionnaire. and it becomes quite the process. So where software can help and here we have some of the best DDQ software currently on the market is not just in workflow management and process management for your DDQs and project management but collaborating with yourmemes as well as of course automating large swaves of the work. Now that automation comes into two main places. You've got automation with AI. So that's using your existing information whether it's past TDQs, your fund brochures, your website, publicly available information as well as fund specific information that can be

categorized and all that kind of context. So that context is then either used by a question and answer bank to copy and paste responses in that's how a lot of legacy DDQ software work or that context is used via AI to heavily automate the entire DDQ process. So let's look at some of these providers first. We're actually going to start with some of those legacy providers. So you've got responsive or responsive.io, also known as RFP IO, which they acquired a couple of years back, but effectively responsive is both an RFP software as well as a DDQ response software. on their website they're saying it's built for small business and yeah it effectively it's a useful tool for DDQ automation and effectively the way it works is based off you've got all your

organizational context and that could be through different integrations and different information through yeah SharePoint seismic and all these systems you might already be using and then it puts that into a library or like a question and answer bank. So you've got a question, a response, and it perfect effectively brings that all together. Then when you get a new DDQ, if you've had that same question or a very similar question before, it will use a keyword search to find the most relevant prior answer for that question and copy and paste it across, which is really useful. And then it has what you'd expect reporting project management features collaboration and be able to go in and you answer that DDQ really effectively. Some of its cons are it does have AI features. So more recently it's added AI.

My understanding at least that's mostly based on the response generation. So let's say you have that Q&A bank. It will then again based on its keyword search find a relevant answer and then maybe slightly generate it and change it slightly for your new answer if the question is slightly different. So copy and paste and sometime some AI generation there but yeah there are legacy RFP or DDQ software have been around for oh I think like 10 plus years. Yeah, really doing really well in the market. a lot of big logos known in the space. Their main competitor is another legacy RF software and that is Lupio. So Lupio similar to responsive for due diligence questionnaires will effectively have your context and your library of information that is then managed by your team. One caveat with DDQ software you

want to be cautious of is that management of content you you want to make sure it doesn't take too much time. I've heard stories of customers of legacy RF DDQ software where managing that library can take an entire wage like an entire person a full-time role or multiple people's roles which can be really important in highly regulated industries but again it's just a cost and timeintensive work managing a content of library to really help make that a software work for you. So, Lupio is yeah uses keyword search and also has some kind of AI top hat features where effectively it will also potentially generate responses. They call it magic and yeah helps with your DDQ responses as well. Then you've got some newer AI players like Inventive. So, Inventive have been

around I think for a couple of years now, but effectively they use their entire product is built on AI. So, like an AI native DDQ software. So, how it works is their products mostly used by technology companies, but I'm sure they've got some financial services customers, but effectively it will use things like competitor intelligence, your knowledge hub. So brings and integrates all the different sources and then brings that content and then uses like an AI semantic search and then generates responses based off your prior context and information about the funds and about the information. Yeah, it's an inventive I think newer player in the market. Definitely obviously wouldn't have as many customers as Lupio or Responsive but very AI native software. Similar to inventive you have Afy although Afy I would say is more positioned towards technology companies

with like sales engineers and go to market teams like salespeople and it's really built around that that shared knowledge hub so that all that context from your past DDQs from your past from your fund information and so on it will use that information and not just be able to help answer DDQ QS new DDQs with responses but also answer questions from your team whether that's in Microsoft Teams and so on. I think they have a Microsoft Teams integration. Definitely have a Slack integration I believe. But yeah, it'll integrate with SharePoint and Seismic and Highspot and so on to bring in all that knowledge information where Afy again similar to Inventive AI native software. So built AI from day one and inventive uh smaller player in the market as it just doesn't have as much brand recognition or as many customers

but yeah great product and the project management and kind kind of collaboration features might be a little bit less than say your loopio or responsive but some really good AI features in there as well. Then you got Ombbud. Ombbud are an interesting one. They're one of those kind of legacy RFP software, but have probably applied the AI features a lot better than say your lupios or responsives. So, OMBbud again has some large technology software providers like Sage and UKG and effectively integrates and they're going more of like that agent framework I guess where different like sales engineering and response management agents kind of work alongside your team to answer different questions. So yeah, a bit more of an RFP like technology and not as much of a investment management DDQ software but can be useful for DDQs.

Soian I would say Cvidian so is one of Upland software one of their products is very much built for DDQs and has a lot of managed investment companies very much a legacy DDQ software where I think they have an AI add-on now but it's like an add-on so it doesn't come natively in the product you may already be using potentially a little bit more dated UI I UX in terms of using the platform but really strong project management theme collaboration features can do like things like PowerPoint. So really useful across different modes that investment managers might find useful, not just DDQ response, but has like a plethora of different features that can be useful in relation to investment managers and how they manage LPS. But yeah, useful product,

really well known in the market in terms of has quite a lot of managed investment funds, but like I said, one of those more legacy providers and yeah, has less of an AI focus. But there you go. You can see it just has a lot of different kind of features that can be really useful across answering DDQs and managing LPS as well. Now, one that's a little bit different, but I thought I'd throw in there is TrustCloud. So they are more of like a GRC platform which is governance risk and compliance. So more like a DRA or a Vanta again more of a technology focus but I put it there just in case you are working at a technology company and your DDQs are more security focused the security questionnaire automation software is going to be really useful to help answer that. I wouldn't say it's as useful though for manage investment funds specifically for DDQs. Then you've got Hey Iris. Iris they're again another AI native player just like Ry and Inventive

but yeah more of that like technology lens as well and you can yeah view their website to find out more information like they can really contextualize all that different context make it a bit of a knowledge map as well but there's all the information there. Then you've got auto RFP. So that's where I work, auto rfp.ai. So we are a DDQ software with a large number of managed investment fund customers, those that are some of the largest in the top 20 in terms of asset under management in the globe all the way from we have customers in Switzerland to Singapore to the United States in that manage financial services, manage investment funds industry. Now where we really shine is with regards to our features is specifically yes a great import features. So things like ILP formats your standard industry formats

pre-built to be able to easily load into our system. So very little or no work on the investment fund manager or on the RFP professional or DDQ professional in terms of uploading that information. So really easy to use on uploading DDQs. Then we also have a browser extension. So if you do get any DDQs in different portals where this is useful is answering within the portal like it scrapes the portal and then automatically starts generating the answers and then you can just copy and paste them back into that portal and easily answer any portal questions. But once you've imported that blank DDQ whether it's Excel, PDF, Word doc, then you have our AI search. So legacy DDQ software generally would use like I said like that keyword search to look across their kind of content uh database whereas we and a lot of AI native DDQ

software use semantic search. So effectively it's not just someone typing in the words trying to find similar words. It is actually an LLM like a large language model providing all its context across an embedded database to find like a vector database to find the relevant query with the context. So for instance, semantic search would understand the difference between real estate assets and questions and answers that discuss that versus infrastructure assets. even though they might have a lot of the same words, it understands contextually they're different things and whether it's commercial and so on. So that's where semantic search and the power of AI not just in generating a response but in finding the relevant content can be really powerful across your AI native DDQ software. So the AI finds the relevant content then whether it's multilingual and so on. So it does AI

optimized translations as well. It then generates a response or provides a verbatim response. So if your content has the exact right response to use and you've done that previously, let's say it's your 15th Ilpa DDQ, it will just copy it will verbatim that response with its AI semantic search and then verbatim it effectively copy and pasting it, which is a lot better than just always trying to generate new responses. But when it can't verbatim response, it will then use AI to generate a response and provide different trust scores, effectively showing you how relevant the content it used is for that response and how trustworthy it thinks it does and uses a specialized reranker model here and that trust score. Then it generates the response. Of course, you've got different features to help collaborate across subject matter experts. You can have unlimited number of users with an order RFP. We don't we do not charge

based off of users. So seatbased pricing is the norm across RFP or DDQ software. We just charge based off number of DDQs you would do every year. But yeah, then the team can collaborate, understand the different responses within there, mark compliance records, assign editors, reviewers, do sequential reviews if you require different teams and people to review answers before they go to the LP for that DDQ response. You can really easily manage different attachments and add attachments. the im the response can add in images from your content add in tables and you can manage that all really easily in order RFP so it's very like intuitive you userface as well then yeah unlimited collaborators also we integrate with Microsoft teams or slack although in this case probably more relevant is teams and effectively those team members will then get notified and just notifications and managing a DDR process is a lot more streamlined line

with a dedicated AI DDQ software. And the big thing is, yeah, we don't think AI should be an add-on. So, it's not like a bolt-on to our software. It is our software. And our pricing, we don't charge for different features or add-ons or plans. The pricing is really straightforward, which I'll cover off shortly. And like I said, integrates with Microsoft Teams as well as translations and then a lot of different integrations whether it's across SharePoint or 20 Salesforce or 20 plus integrations as well as real-time web scraping for context as well there. And then of course when you are doing hundreds or thousands of DDQs, you want reporting that really helps understand the DDQ process, the time and the cost it takes to do DDQs as well as the impact AI is having on your DDQ process. That's why we provide AI

automation reports and a lot of other different information as well as in just general kind of managing that DDQ process. So, in terms of our pricing, yeah, you can find that on our on our website. Really straightforward. Like I said, all the plans are effectively the same. The only different thing is the price and the number of DDQs per year. So, that's order RFP.ai. And I covered eight other of the best DDQ software in the

Transcript is auto-generated and may contain minor errors.

Hey, we're going to jump into how you can use AI to automate your DDQ process. Let's jump into it. We're going to be using AutoRFP.ai, where an AI software application cloud-hosted across the globe with hundreds of customers, everyone from Silicon Valley startups to some of the largest managed investment fund companies in the world across managed investment funds with portfolios and offices across Switzerland, United States, and Singapore using our product every day to answer hundreds and thousands of DDQs. Let's jump into it. So, AutoRFP, you can upload diff- you can upload different DDQs that you might get. This might be your LP DDQs or just any from

your LPs that are coming through and you want to highly automate that process. You can also upload your RFPs and any other kind of compliance questionnaires you'd like. Really, what AutoRFP is Really, what AutoRFP is effectively you create an AI knowledge lake with your relevant context. This could be information from your website, whether that's fund information like investment performance over time and other relevant public information. AutoRFP can scrape that information automatically or it could be technical documents or fund documentation in relation to your products and services and so on. But effectively, all that information, as well as integrating with 15 plus other systems like Google Drive, SharePoint, Microsoft Teams.

We pull that together into an AI knowledge lake, which is a vector database. Then AI starts to do its work across two different ways to generate DDQ responses en masse. First is the AI semantic search which uses embedding models and re-ranker models to effectively site the most relevant context. That's how we have customers in Auto RFP that have hundreds and thousands of or tens of thousands or hundreds of thousands of pieces of content in their Auto RFP library with specific categorization in relation to tagging. For instance, here I have tagging. If I was a managing investment fund, I could go all the way down to particular asset-backed credit and

different investment platforms and all different funds and effectively that relevant context is provided to the LLM. So then it knows what is the right information for automating DDQs. So then you have an AI response agent that takes that relevant context and across a series of LLMs, whether it's Gemini, OpenAI, and Anthropic, generates a response. That can then be collaborated across the team as well as translated to 50 plus languages with translation and AI optimization for localization of translation as well. English US, English Australia, and English UK, and so on. Then within the product, you have workflows, whether it's integrating with your CRM like Salesforce for intakes of new

DDQs, importing via portals, AI analysis, and a lot more. And let's jump into that. So, within AutoRFP, you have your different projects that might be a RFP, a due diligence questionnaire, and so on. We create those projects, load the relevant files. That comes in, whether it's a zip file, Excel, PDF, Word doc, and we import that information. First, we do a project analysis. Imagine this LP, this is the first time you're working with them, and the first time they've sent you a due diligence questionnaire. You may have specific questions that you want to understand before responding to that DDQ based off the context and content in the due diligence questionnaire itself. That's where we leverage an LLM AI to analyze that relevant DDQ and provide any answers to our questions, and it'll provide sources as well a confidence

scoring based off that information. So, now I've looked through that, and I've read through the DDQ, it's time to start answering. First, here our software will automatically mark up the document with AI and OCR to effectively specify what are the requirements and what are the responses that it needs to then generate answers for. So, you can see here it's done multiple Excel tabs. It's looked at the PDF and pulled out the requirements there from the DDQ, whether it's tables and so on. It's also done that in a Word doc, other information that might be relevant. Then, we can choose what content is most relevant. So, here I might say, "Okay, this is a fun four, and this information's relevant, and that's the kind of content that I want to use to answer this our DDQ.

Once we have our content selected with your tagging and hierarchy that makes the most sense for your kind of large waves of context for the LLM, we then can provide what kind of style responses we want, and we can change anything here later, and what languages. Now, the fun begins. So, this is pretty cool. So, we have generate we have pulled in all those responses. So, now the fun begins. The AI, as you can see, it's ticking up along the top is automatically generating responses for those questions based off our context. Everything's going to come in here from rich text formatting to tables to images. Anything that you have in your content that was relevant for that answer, it will then effectively, like I said, use a re-ranker and embedding model to source the relevant information, and then use AI to generate those responses. Any of these responses I can go in and click here and understand the trust

score. And so, that will provide whether it's a tag level match across our context. So, for instance, our information and the confidence of that response as well. Clicking in edit here, I can see more relevant information. It hasn't pulled from This is actually expired two months ago. So, our content features have expirations and teams to review content and all the kind of information you provide you can do in the content. If then I want to say this content looks great, but I actually want to suggest any changes or flag it for review, the content owner would then get information for that content. Let's say instead I actually wanted to add in this relevant information and this relevant information, but then I want to add a prompt to edit that with the AI or just use a little prompt here to shorten that response and effectively AI now will again answer and edit that response according to my prompts that I've used there.

I I can see the changes and then I can accept those changes and of course there's revision history and AI assistant so I can ask it questions to help me understand that requirement in more details. Like I maybe I don't know what an SAP Ariba is. Sadly I do, but maybe I don't and it can tell me more information there. So that's a bit of our response editor and now all those different responses have come through. I can go to my different sections within the DDQ like my artificial intelligence section. I can select all those requirements and I can start assigning those to relevant team members. So I might assign this to the legal team as reviewers and so anyone from the legal team now has the opportunity to review those responses once I start submitting them and they will get Microsoft Teams notifications or Slack about that workflow and get updates on the process of the project as it goes.

Let's take a step back and say I was now project managing this DDQ response because I'm the investment manager for that fund. I can click on the project overview, quickly see how many responses are left to complete, who they've been assigned to, send reminders to those team members, again Slack, Microsoft Teams, and I can also see when the project is due and how our overall progress as time goes on. We can add additional attachments as well. So, I might want to add this attachment and this attachment. So, when I export my completed project, that will then include any attachments that either myself or the AI has added. Let's take a step forward and go back to now answering those responses. Here, of course, I can make any changes as I want and submit that and work through my task list of different tasks for those responses until it's done.

Looking through, we can also look at any low trust score ones we have or any that are empty, which might which will require human intervention to answer. So, looking at this low trust score, I can see, okay, why is it low? And then I can go in and I can edit and make changes to that response. You also might notice there's a second AI score here, and this is the AI feedback score. The AI feedback score will tell me if how well that response, whether it's AI or human generated, will is answering that DDQ requirement. Okay, so we've just finished editing our responses, we've reviewed the trust scores, filled everything out that needs to be filled out. We can regenerate responses, write additional feedback like and so on. Now, we're ready to export. So, once everything is approved, and what we can

do there is then mark the project as completed and then export that entire project, and that can include any proposal templates that you have. So, that might be executive summaries and other relevant information that is in your firm's tone and marketing collateral and that and then you can have the requirements and relevant context auto-generate into those export templates. And then we can export that and then submit the DDQ. So, that's a lot of it. So, we're AutoRFP.ai. We're a DDQ software and RFPs that helping global technology and fund manager companies all around the globe automate the mundane when it comes to DDQs and RFPs. And not just automate, but really help free up people to write better responses to win more faster. In terms of our pricing and all our

information, you can find out more information. If you're doing more than 50 DDQs per year, recommend getting in touch with us by booking in for an online demonstration. And you can find all about us at AutoRFP. ai. Well, thank you. I'm Rob from AutoRFP and I'm glad I could show you how to leverage AI to automate the DDQ process. Thank you.