AI-Driven Software Development: Custom Tools for Pricing and Sales

Until recently, companies with specific pricing and sales logic had two unsatisfactory options: generic standard software with high licensing and customization costs – or an Excel solution that becomes more fragile with every extension and eventually can only be understood by one person. Modern AI coding tools such as Claude Code now open up a third path: lean, focused tools that cleanly map one specific process – more robust and team-ready than a spreadsheet, lighter and more cost-effective than a standard software product. Roll & Pastuch translates your pricing and sales models directly into working tools together with your business teams – precisely aligned with your logic, terminology, and way of working.

Our Approach: Turning Models and Methods into Tools

For more than 15 years, Roll & Pastuch has worked on pricing, sales, and strategy topics. Every project creates models, logic, and decision rules – condition systems, pricing waterfalls, commission models, target-price logic. With AI-supported software development, we can translate these models directly into working tools without turning them into large-scale IT projects. The business depth remains at the core of our work; AI tools such as Claude Code support the technical implementation.

Advantages Compared with Standard Software and Excel

Lean and focused: Less code means less maintenance, less training effort and faster onboarding.
Tailored to your logic: Terminology, workflows and decision steps follow the way your organization works – not the customization logic of a standard solution, but an application designed for your use case from the start.
Significantly more cost-effective: Licensing costs for generic platforms are eliminated; development costs are typically only a fraction of what a comparable standard software implementation would require.
You keep the code: Source code, data model and documentation belong to you – without vendor lock-in and without roadmap risk.

Typical Use Cases

The following examples show where we already use AI-driven tooling today. They all have one thing in common: a clearly defined scope, business logic that can be precisely formulated and a direct link to pricing, sales or condition-related decisions.

Starting point: Complex, individually configurable products and projects are priced by sales teams using Excel sheets, list-price PDFs, and manual discount logic. Quotes take days and prices vary across salespeople and regions. Approach: We build a configuration tool based on your value drivers, country and customer segments, and order-specific factors such as quantity or express surcharges. Instead of adapting a generic CPQ platform to your company, we develop a tool that cleanly reflects your exact configuration and pricing logic. Typical potential: • Quote preparation reduced from days to hours – and to minutes in standard cases • Consistent price relationships across configuration variants and regions • Margin impact through the elimination of “just-to-be-safe” discounts and more consistent target prices • Full traceability of every special condition

Starting point: For every request, sales teams face the same question: What price is plausible and enforceable for this deal? Answers are drawn from old quotes, personal experience, and quick checks with the pricing team – leading to high variance and long response times. Approach: We develop a tool that displays an empirically grounded target price and negotiation ranges for each request – based on your historical quote and order data, with clear guardrails. Typical potential: • Target-price response in seconds instead of hours • Reduced variance for comparable requests • Higher margin discipline without additional approval effort • Learning recommendations that improve with every completed deal

Starting point: We build a condition calculator that immediately makes the financial impact of every special condition visible and guides requests through a clear processing status in line with your approval logic – more robust than a spreadsheet, more focused than a BPM platform. Typical potential: • Approval time for special conditions significantly reduced • Full transparency on ongoing and completed requests • Consistent application of approval logic across all sales areas • Margin impact by preventing concessions without a sound business case

Starting point: Commission and bonus models in complex sales structures are maintained in Excel. With every extension of the model, error risk, effort, and discussion loops with sales increase. What-if analyses for new models take weeks. Approach: We develop a commission calculator that cleanly reflects your incentive logic – including multi-level structures, tiered bonuses, and special promotions. Sales teams receive transparent, individual statements; management receives simulations for model changes. Typical potential: • Settlement effort drastically reduced • Model discussions with sales based on facts rather than Excel suspicion • Fast what-if simulations for new incentive logic • Avoidance of overpayments and recalculations caused by Excel errors

Starting point: Salespeople enter complex negotiations with a mix of personal experience, hastily gathered notes and gut feeling. Arguments, concession strategies and success patterns from similar deals are scattered across people’s heads, win/loss notes, old quotes and battle cards. Approach: We develop a Negotiation Copilot that supports sales teams before and during negotiations. The tool combines a customer-specific dossier, a searchable argumentation and objection-handling library (fed by win/loss analyses, value-based selling content and battle cards), as well as a concession calculator that checks the value of individual demands (price, volume, term, service level) against your defined margin logic. Typical potential: • Preparation time for major deals reduced from hours to minutes • Consistent negotiation approach across salespeople and regions • Improved concession discipline – lower concessions at comparable win rates • Argumentation library grows systematically with every completed deal

How We Work: The R&P Approach to AI-Driven Tooling

Phase 1:

Business Concept and Use-Case Sharpening

We do not start with code, but with the business logic. Together with your business teams, we sharpen the use case, model the underlying decision rules and define the requirements for data and usability. The result: a precise business blueprint.

Phase 2:

Iterative Prototyping

Within a few weeks, a working version is created – focused on the core purpose, tested with real data and real users. Feedback from the business team flows directly into the next iteration until the tool reliably fulfils its purpose in day-to-day use.

Phase 3:

Handover and Enablement

Code, data model and documentation are handed over to you in full. If desired, we continue to support the tool through a maintenance and further-development partnership – you decide how the tool is rolled out within your organization and how deeply you want to remain involved.

The R&P USP: Consulting and Tooling – Under One Roof

While other providers offer either pricing and sales consulting or software development, Roll & Pastuch combines both worlds:

More than 15 years of consulting experience in pricing, sales and strategy – with deep industry expertise in mechanical engineering, chemicals, electronics, consumer goods, and software.
In-house Data Science Unit with dedicated AI expertise under one roof – not a subcontractor.
You retain the code, the data model and full control – pragmatically, in weeks rather than quarters.

Let’s Talk About Your Tool

Do you have a pricing or sales process for which no standard software really fits – or an Excel solution that no longer scales? In a 60-minute initial consultation, we clarify whether a lean AI-driven tool is suitable for your use case and what a first pilot could look like.

Schedule an initial consultation

Your contacts

Managing Partner

Karsten Konrad ist Senior Project Manager von Roll & Pastuch

Dr. Karsten KonradSenior Director Data Science