AI-based CPQ process

Speed up your Quotation Process with GenAI

Is your manufacturing company facing challenges in providing timely offers for highly configurable products? Our GenAI-enabled CPQ (Configure, Price, Quote) tool automates the process, reducing costs and delays, and generating accurate quotations.

Our CPQ expertise

Many manufacturing companies offering highly configurable products strongly rely on the experience of their sales back-office personnel to service the customers. Starting from the getting the “right” product configuration which ideally fits the customer’s requirements and creating a quotation for it via order processing and inventory management to customer support and sales reporting, all these steps are still mostly executed manually by sales support.

This high manual workload leads, however, often to longer and less efficient quotation creation, order processing resulting in an increased risk of errors, delays in fulfillment, and ultimately, loss of customers.

Specifically, for the CPQ (Configure, Price, Quote) process, we have seen such manufacturing companies often struggle to provide high-quality offers in a timely manner due to the complexity and the significant manual effort required. This leads to increased personnel costs, extended delays—sometimes by weeks—in the sales cycle, and opportunities lost to faster competitors.

Our CPQ tool helps you to take a step towards a more efficient sales back office by integrating this process in one window and leveraging the GenAI capabilities to take over all repetitive work and administrative burdens from your experts.

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How your company can benefit from our CPQ solution

You will get a solution for automated proposal generation that extracts functional and technical requirements from any notes or transcripts or document drafts, finds similar configurations or projects in your database, and drafts new offers based automatically while at the same time allowing granular control for the sales (back) office users at any step. Our tool enables you to carry out the typical steps of the CPQ process in one GUI within minutes rather than within days or weeks.

Automate CPQ Process

and manage them efficiently from an integrated CPQ tool which bundles all relevant systems (CRM, ERP, …)

Suggest product configuration

and generate quotations on-the-fly based on customer input and your historical data using AI-enabled product configurator

Efficiently store

and manage all documentation

Our CPQ tool has moderate costs with a short payback time as the calculated expected return on investment is usually within 1 year. The expected business case is profitable for all companies with an annual revenue of 50 Mio. CHF or more.

How our CPQ solution will increase your revenue

Higher Number of processed Quotes

Shorter processing times per offer mean increased number of quotes that can be processed by the team.

Higher Win Probability

The probability of closing each deal increases, as customers receive high-quality initial offers ahead of the competition.

Scalability

PoC/MVP should initially be implemented in one area and gradually expanded to other products and regions. Ideally, the customer establishes a unified AI ecosystem with the concurrent projects.

Customer Self-Service

Give prospective clients directly access to the tool. This results in a self-service option which enables clients to perform highly complex customization configurations independently and prior to any contact with sales personnel.

"Harnessing GenAI’s full potential means thinking in terms of automating entire processes, not just specific steps or use cases."

Mykhailo SaienkoSenior Manager Applied AI, PwC Switzerland

How does it work?

We use a modular architecture which provides flexibility for extensions and the possibility for further configuration of the product matching module.

Key features within our interactive CPQ GUI:

Key product characteristics such for your product or project are automatically extracted from unstructured information, such as conversation transcripts, notes, drafts, etc.
The user has the option to validate and adjust the extracted characteristics.
The chatbot is built like a virtual assistant that recognizes the user's intent and calls specialized workflows (find similar configurations, perform pricing, create quotation, etc.).
The matching algorithm is modular and can be product-specific, customer-specific, or employee-specific.
The results of the workflows are context-based and are either displayed in specialized components (e.g. the results of the matching search) or directly in the chat (answers, analyses, follow-up questions, or graphics).
The user can always refine the results, add additional filter criteria, and provide other feedback on the search results.

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