Every pricing decision can reach the quote with the data, the range and the approval it needs. Relevant connects ERP, CRM and CPQ data, builds price guidance and approval rules into the tools sales already uses, and flags the deals that need a pricing review.
You need price guidance and margin control across regions. A leading platform vendor lists subscriptions at $100k to $3.5M a year before implementation. For mid-sized companies, a custom layer built around current systems can carry the same pricing logic for roughly the cost of [one to two years] of licence and implementation, with no annual subscription after launch.
You chose a platform and want it in daily use. A small working group with AI-assisted engineering structures the master data and builds the connectors, so the rollout reaches Sales sooner.
Your platform holds the data and the rules, and you want more value from it. A pilot on one workflow adds the context the platform lacks, such as external signals or an explanation behind each recommendation, and leaves building blocks for the next workflow.
Get an independent answer on whether to buy a pricing platform, customize one or build around your own systems.
Relevant engineers trace one pricing decision from source data to the signed quote and put a cost on the hours and margin it consumes.
A two-to-four-week audit shows whether your product, customer and price data across ERP, CRM and CPQ is ready for a pricing platform or model, and what to fix first.
Relevant builds the pipelines and quality checks that bring them into one data layer, so every price is set on the same numbers.
A custom pricing engine holds your own price logic, segment rules and floor prices and serves them to the CRM and CPQ screens your sales reps already use.
A focused Relevant team prepares the data for a [Pricefx, PROS or Vendavo] rollout and connects the platform to SAP, Salesforce and your CPQ, drawing on software integration services for the interfaces.
Our data integration services bring ERP list prices, CRM discounts and CPQ quotes into one decision-ready record per product and customer.
Approval routing sends each deal to the right approver by margin, size and segment, while routine deals inside guardrails go straight to the quote.
On a platform that is already live, our engineers add anomaly detection, deal scoring and margin leakage alerts and run the models through the deployment and monitoring setup of AI integration services.
Our AI-assisted development brings up to 50% faster delivery and up to 20% fewer bugs, with every release passing senior code review.
96% employee retention keeps the engineers who learned your pricing logic on your project.
[SAP, Salesforce and CPQ integrations in production] connect the pricing layer to the systems your teams use every day.
97% of clients continue working with Relevant after their first project, often moving from a pilot to the next phase.
Delivery experience in [retail, marketplaces and consumer goods] pricing and data projects.
Engineers in [Central European time zones] join your pricing team’s calls on the same day.
Both routes work, and the deciding factor is how much of your pricing logic is specific to your business. A platform pays off when its standard models cover most of your rules. A custom layer pays off when your price logic, approval paths or data sources need heavy configuration anyway, because that configuration effort becomes the build.
Company size moves the answer too. Pricing leaders we interviewed at large enterprises lean toward specialized vendors once a capability reaches scale, while AI-assisted development has made custom builds competitive for mid-sized companies.
Count three things today: the pricing rules a vendor would need to customize, the licence quote for two years and the implementation quote. If customization covers most of your rules, price out a build before you sign. If the rule count is unclear, Relevant runs the count with you during discovery from your current price lists.
Cost follows four variables you can count before a call: the number of source systems, the number of regions or business units, the number of exception types in scope and the state of your product master data. A pilot on one exception type with two or three source systems sits at the low end. A multi-region rollout across several ERP instances sits at the high end.
After kickoff, Relevant delivers a [costed roadmap in 14 days], with a fixed scope for the pilot. Bring your system count and the decision you want to speed up, and contact us for an estimate built on those numbers.
A pilot starts with the exception type that combines high volume with long waiting time. Pull last month’s deals that went to Pricing for review and mark the ones Pricing changed. Deals that passed review unchanged are the first candidates for automated approval inside guardrails.
If those records are hard to pull, Relevant extracts them from your CRM and ERP logs during discovery, with nothing for your team to prepare.
Reps trust a range when they can see why it applies to their deal. The quote screen shows the comparable won deals behind each range, the floor price and the approver for anything below the floor.
Trust builds faster when the first release offers guidance and leaves the final price with the rep, while the system records every override. Override rates by rep and segment then point to the cause. A cluster of overrides on one segment usually means missing data or context, such as a competitor move the model never saw. Overrides spread across experienced reps on sound recommendations point to adoption, where coaching works better than a new model.
No, it doesn’t. Pricing managers set the guardrails, and reps or approvers make every final price decision. The models rank deals, suggest ranges and flag margin leakage, and every change to a guardrail goes through your pricing team’s approval.
Enterprise buyers usually score six things: data accuracy, data security, algorithm quality, integration feasibility, the product roadmap and commercial terms. A custom layer answers each with evidence from your own systems: accuracy measured against your historical deals, security reviewed inside your cloud tenant, model results on a holdout period and integration proven on a live connector during the pilot.
Mature pricing organizations also limit the number of tools they run. Relevant extends the platforms you already own, so the approval covers new capability inside an existing system instead of one more vendor.
Yes, it can. In FMCG part of the decision data sits with your retail partners: sell-out data, promotion results and competitor shelf prices. Relevant joins those sources with your own sales and trade spend data, so RGM teams see price, promotion and mix effects per channel in one view.
The first use case usually covers one channel and one category, which keeps the data agreements with retailers manageable.
Start with one pricing decision, and the map shows which path fits your stage.
SaaS
AI
Fintech
