General
How do we get started with Response360?
- If you would like to learn more about this product or request a demo, please reach out to your account manager or email ‘product-updates@oncentrl.com’. Our team will organize a demo and give you the opportunity to try the product yourself.
Does Response360 use AI? How can we benefit from using Response360?
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Yes. Response360 stands out as an AI-native solution that optimizes your entire response process. In addition to standard RFP and DDQ functionalities like response management, workflow automation, and collaboration, Response360 offers several unique features.
- Uses AI to seamlessly convert all incoming RFPs, DDQs and questionnaires in Word, PDF, and Excel format into digital questionnaires, eliminating the need for manual data entry.
- Completes questionnaires in minutes vs hours/days by automatically finding highly aligned matches from your Answer Library to populate, as well as generate answers from your supplemental documents (policies, reports, etc.)
- Response360 is developed and tested with content specific to the Financial Services Industry and therefore generates responses for RFPs and DDQs with unparalleled accuracy and speed
- AI-powered automation updates your Answer Library with proprietary answers, freeing your teams from the burden of manual content maintenance
Can Response360 integrate with our existing content management system?
- Response360 can replace your existing content management system. Not only does it have an Answer Library that stores all of your past responses, it automates the update and maintenance of content in the Answer Library as you complete new questionnaires. Response360 does not currently integrate with other content management systems.
Our firm has multiple products and we sometimes need to maintain different answers for different products. How do we manage this in the Answer Library?
- The Answer Library supports a list of standard attributes such as product that can be utilized to maintain your unique answers for each product.
- You can also add custom attributes for your Answer Library to meet your specific needs for organizing your content.
How accurate are the results? We have heard that these generative AI models are prone to hallucinations. Have you done any analysis?
- Our results are highly accurate, and we've made intentional decisions to avoid hallucinations. Hallucinations often result from writing open-ended queries or asking the model to generate large amounts of text. Instead, we ask the model a very specific question with a list of relevant passages from your sources to ensure focused and accurate responses.
- We've also integrated hallucination detection mechanisms into our system.
Are there any constraints to the types of documents I can utilize to generate answers?
- We currently support any Word or PDF document as source content for answer generation. It is on our roadmap to extend the list of supported documents to include Excel and PowerPoint in the future.
- Additionally, we do not currently analyze content in images within documents. This is another enhancement we will be looking at in the future.
Roadmap and Feedback
What is the roadmap for Response360?
- We're excited to make Response360 even more powerful. Our immediate roadmap includes broadening its capabilities to export RFPs, DDQs and questionnaires in their original format, generate answers for table-type questions, and add more granular assignment and approval workflows for questionnaires. We also highly value user feedback, which will help shape our future roadmap.
How can I suggest a feature or improvement and provide feedback?
- In-App feedback: you can provide feedback directly in the CENTRL platform as you review the AI generated answers by giving the answer a thumbs up or down. This information is used to help improve the accuracy of responses over time.
- If you see gaps in our product or have suggestions to improve the existing features, we would love to hear from you!
AI Model and Training
What AI tool are you using?
- We use OpenAI, the most prominent Large Language Model (LLM). We continue to update to the latest model offered by OpenAI and testing is done before every release.
How are you training the model?
- The Large Language Model is pre-trained on tens of gigabytes of data. We leverage this existing model to generate responses to your questionnaires. Additionally, we employ a method known as Retrieval-Augmented Generation (RAG). RAG integrates a retrieval mechanism with the model, enhancing its ability to generate responses by retrieving relevant passages from your provided sources and using them to inform the generated text. This approach enriches the model's understanding and enhances the quality of its responses based on retrieved information.
Do you plan to add or use other open-source models?
- The AI market is rapidly changing, and we are evaluating whether to use an open-source model in the future.
Related Articles
This article covers frequently asked Questions & Answers about our Response360 product for users. Please see our other Response360 help articles here:
To contact us to arrange a demo, request more information, or provide feedback email us at product-updates@oncentrl.com