Interview with David – Co-Founder and CRO of Vendorful

Vendorful.ai provides an AI-powered solution for Strategic Response Management. This means it offers a tool that helps businesses respond to various documents and requests, such as RFPs (Request for Proposals), RFIs (Request for Information), and Security Questionnaires, with a focus on increasing revenue and efficiency.

Here’s a breakdown of what Vendorful.ai is doing:

• AI Assistant for Faster Responses: Vendorful.ai’s AI Assistant takes on the task of answering these business questionnaires and documents. It does this in a matter of minutes, significantly reducing the time and effort traditionally required to respond to such requests.
• Efficiency and Time Savings: By using this AI tool, businesses can complete the task approximately 10 times faster compared to manual efforts, and with just a fraction of the work. This means that you can allocate less manpower and still achieve quick and accurate responses.
• Streamlined Onboarding: The onboarding process is simplified and quick. You can start using the tool by simply uploading your data, which means you can get started without a lengthy setup process.
• Answer Flexibility: Vendorful.ai allows you to choose from different types of answers. You can use generated responses provided by the AI, select from previous responses, or create custom answers, giving you flexibility in tailoring your responses to specific requirements.
• Export and Access: You can easily export the responses to Excel, preserving the original formatting. The tool also provides quick access to past responses and content from your library, making it easier to locate and reuse relevant information.

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In essence, Vendorful.ai leverages AI to streamline and automate the process of responding to business documents and requests, making it faster, more efficient, and less labor-intensive, ultimately helping businesses increase their revenue while reducing the workload associated with such tasks.

Chris: Hi! Can you tell us more about yourself and the role you’re playing in that blooming project?

David: Hello, my name is David Wadler and I’m the co-founder and CRO of Vendorful. Immediately before this, I was the GM of Rich Media and Cloud at Lexmark. I landed there when they bought the previous company I had co-founded, Twistage.

Chris: Can you share the story behind the creation of Vendorful AI and what motivated you to develop this AI-powered response management platform?

David: When my partner, Peter Bonney, and I decided to start Vendorful, our focus was very clear; we wanted to streamline and simplify the b2b buying process. Businesses will regularly spend more money on a one-year contract than people spend on their homes. And these expensive and complex decisions have historically been built on email exchanges and the occasional steak dinner.

We began by building software for procurement departments to help them source, onboard, and track their vendors. Our vision was always to build software for both sides of the engagement, but it’s only been in the past year that we feel the AI tooling has been robust enough for us to implement a questionnaire response tool that functioned as we originally imagined. We wanted it to feel like magic.

Chris: How does Vendorful AI’s artificial intelligence generate custom responses to RFPs and other business questionnaires? What machine learning or natural language processing techniques are involved?

David: From the perspective of the user, it’s extremely straightforward. You just add content to your content library. These include completed questionnaires, white papers, product overviews, web pages, etc. Then when you get a blank questionnaire, you upload it, tag it, and then the AI will generate a first draft in a few minutes.

What’s happening behind the scenes is extraction, vectorization, and labeling of the content. Then, when questions come in, we identify the most relevant bits – particularly those pieces which are semantically similar – and pass that to an LLM, which synthesizes an answer based on the context that we’ve provided. It’s important to note that none of this data is used to train a 3rd-party LLM. Customer data strictly remains customer data.

I’ve distilled down what’s happening so your readers don’t fall asleep, but I should note that the most common discussions involve developing techniques to improve the context and therefore the quality of the answer. We’ve made significant strides since we’ve started.

Chris: Could you elaborate on the response library and how it assists businesses in responding to RFPs and DDQs? What kind of content is available in the library?

David: The content library should consist of true and accurate data of the type that a human would reference in responding to a questionnaire. Generally, we recommend that people avoid documents that are “marketing fluff.” That doesn’t mean that marketing documents aren’t useful, but the best ones for a system like ours deal with facts rather than aspiration.

I often joke that if I took the questions from ten RFPs for a product category, I could construct any possible future RFP for that category. To be clear, I’m not sure that ten is the magic number, but one of the things that makes RFPs frustrating for vendors is that it takes a lot of time to answer many of the same questions repeatedly. When they use our system, previous answers can be automatically leveraged to generate new answers.

Chris: In your experience, how has Vendorful AI transformed the way businesses respond to RFPs and questionnaires in terms of efficiency and effectiveness?

David: While we’ve been around for a while on the procurement side, we’re pretty new to market with our AI Assistant product. The thing that has struck me, initially with prospects and now with customers, is that our implementation is radically different from incumbent solutions. Peter and I feel strongly that this stems from having an AI-first approach.

Go back in time a year or two and if you want to solve the problem of responding to these business questionnaires, you have to think in terms of both content management and project management. Humans are still dividing up the work of drafting new responses, based on previous answers. And those previous answers are tied to keyworks, not semantic similarity. For example, “headcount” and “size of staff” have no words in common but mean the same thing.

But the big change is that project management, which adds all sorts of complexity, is no longer required. The Vendorful AI Assistant generates a draft response in minutes. There is no need to set up a multi-week or multi-month project plan. As a result, our approach to building the product is radically different.

Chris: Can you provide some examples or case studies of businesses that have seen significant improvements in their response rates and contract wins after implementing Vendorful AI?

David: As we’re conducting this interview, we are still under two months in market. Without spending marketing dollars, we’ve had over 200 organizations sign up to use the product and have built – much to our surprise – a pipeline of enterprise opportunities. (We thought that this was going to be a pure PLG motion but are very pleased to have been proven wrong.)

Anyway, my point is that we’re still way more focused on building features than marketing collateral. In fact, due to the enterprise interest, we just launched an Enterprise Design Partner Program to help guide our roadmap for customers in this segment. But early feedback validates what we’ve experienced, which is around a 90% reduction in time to turn around a questionnaire.

Chris: What is the typical learning curve for businesses adopting Vendorful AI, and how quickly can they start benefiting from the platform?

David: A customer can load in some content in a few minutes and be ready to rock and roll immediately after that. The biggest problem for customers is usually digging completed questionnaires out of their email sent folders!

Ultimately, lots of companies are going to have access to similar AI tools. We feel that the winners and losers in software that leverages AI will be determined by user experience and go-to-market. Our number one goal with user experience is simplicity. We want to make it really easy and shorten time to value.

Chris: Are there any plans to expand the scope of Vendorful AI to include support for other types of business documents or questionnaires beyond RFPs and DDQs?

David: Given our focus on simplicity, there is a natural tension here. The answer is “yes,” though. In fact, we have already rolled out a Slack-based AI Sales Assistant. Imagine you’re in sales and are working on a deal and the prospect sends a bunch of technical questions your way. Today, you might look through documentation, ping an internal subject matter expert like a sales engineer, or reply with an email along the lines of, “Thanks for sending these questions. Give me a couple of days and I’ll get back to you.”

The passage of time is one of the biggest sales risks. With the AI Sales Assistant, you can simply paste in the customer questions and get answers immediately. No waiting. No bothering a colleague. No buying time with the prospect. Our near-term plan is to extend this functionality to Microsoft Teams. And we are looking for other use cases that naturally fit with our product’s capabilities.

Chris: Looking ahead, what are some of the key features or improvements you have in the pipeline for Vendorful AI as it continues to evolve and grow?

David: We have loads of ideas but are particularly excited to see what comes out of the Design Partnership Program. Despite just having kicked it off, we’re getting lots of interest in integrations. Any time our product can enhance an existing workflow and/or product, we view that as a huge win. The ultimate simplicity is not introducing new interfaces, but helping companies get more value out of their existing processes.

Chris: Thanks for being with me, any last words? Where can our readers follow you?

David: You can check out Vendorful and follow me on LinkedIn.