Why We Built Mondrio: Pricing Needs to Evolve With Your Product

Today we're proud to announce a $3.75 million round led by Heartcore Capital, with participation from Pretiosum Ventures, Hersir Ventures, Cambrena Capital, Momo VC and a group of angel investors who have built and led companies in pricing, CPQ, AI and payments. We’re also showing our platform publicly for the first time.

Funding news usually centers on the money, but we'd like to explain the problem that made us leave consulting and start a company.

Every Pricing Project Has a Shelf Life

We have spent more than 25 combined years advising tech companies on pricing in Europe and the U.S. We've worked with scale-ups, unicorns and listed companies, and the engagements tended to follow a familiar pattern. We would research the market, interview customers, model the options and deliver a recommendation.

A few months later, calls would start coming in: a competitor had changed its model, the product team added three new features, or leadership wanted to enter a new segment.

What did all of that mean for pricing?

Sometimes we’d revisit a client a year later and find a pricing structure that had been patched so many times nobody could explain the logic anymore. The analysis started soundly, but the format failed. It sounds obvious, but a strategy delivered every year or two can’t keep up with a product that changes every few weeks.

AI Turned a Slow Problem Into an Urgent One

Pricing has always mattered, but three changes make it impossible to manage the old way.

1. Products move faster. A chief product officer at a large tech company told us recently that AI coding tools had made his engineering teams far more productive. But it has also turned other parts of the business into bottlenecks, including pricing.

2. The economics shifted. Software companies used to enjoy high gross margins and almost no marginal cost. Charging something usually meant making money, but AI has changed that. Every model call carries a real cost, and a poorly priced AI feature can lose money as customers use it more.

3. Most teams can’t keep up. Roughly three-quarters of tech companies lack a centralized pricing function, according to McKinsey. Companies that do have pricing teams often don’t have enough people to handle the volume of decisions that need to be made. Talent is scarce; some of the best-funded companies in AI have had pricing roles open for months.

Buying is changing as well. B2B buyers already use AI to research and compare software. Soon their agents will request quotes and negotiate terms, meaning sellers will need pricing that machines can read and negotiate, within guardrails the company sets.

Ten Reps, One Deal, and Ten Different Prices

Pricing strategy is half of the battle; in a sales-led company, pricing gets decided in the deal.

We used to run an exercise with sales teams where we’d give 10 reps the exact same deal parameters and ask two questions: What would you quote? And how confident are you? The answers were all over the map, on both price and confidence.

That gap costs companies money, and it also costs them trust when two similar customers compare notes and you can't explain why one paid more. Every price has to have a rationale a rep can stand behind.

Strategy and execution have been historically separate; pricing teams set the rules and hand them to sales without the reasoning behind them. Reps, rewarded for closing, rarely send back what they learn about competitor prices, objections or why a deal was lost. Most of that knowledge is lost in call transcripts.

Here’s What We Have Built

Our goal with Mondrio is to help businesses build the pricing team of 2030. AI agents handle much of the day-to-day work across pricing strategy and deal execution, and human experts focus on strategic calls, complex problems and oversight.

The platform has two products:

Pricing Studio helps companies design and optimize packaging, pricing models and price levels. Agents pull in customer research, willingness-to-pay surveys, competitive intelligence and commercial performance to recommend changes and simulate their impact.

Meanwhile, Deal Engine brings pricing intelligence into every quote, negotiation and renewal. It recommends a price for each deal, explains why, guides discounting and automates approvals within guardrails defined by the company.

The two products share a feedback loop, and strategy shapes every deal. What reps learn in negotiations, discounts and outcomes flows back into Pricing Studio so the strategy keeps improving.

Every agent works from three sources of context: the company’s objectives, its customers and their willingness to pay, and pricing best practices for that industry and segment. A company focused on adoption should price differently from one focused on monetizing its installed base.

The agents know that difference.

We also know that not every company has a pricing team. For those that don’t, our pricing experts can serve as that function. For those that do, our experts help with onboarding and step in for big projects, such as a customer research program or a pricing redesign.

Better Pricing Doesn’t Always Mean Higher Prices

People often assume our job is to raise prices, and sometimes it is. But more often, the value shows up elsewhere, as consistent pricing customers can understand, quotes that are right the first time and shorten the sales cycle, and models that help companies adopt usage- or outcome-based pricing with confidence.

For many AI products, the right move is a land-and-expand motion that earns less upfront and grows with the customer. The goal is pricing that serves the business, segment by segment.

Heartcore Capital shares our ambition to build a category leader on both sides of the Atlantic. And that matches how we’re built, with teams in Amsterdam and San Francisco.

We assembled the rest of the round deliberately. Our investors include people who have led pricing at major companies, built and scaled CPQ platforms, worked on AI at the frontier and built payments infrastructure. Each group understands a different piece of the system we’re building.

What Comes Next

This round of funding will go toward three priorities:

• Product: Growing our AI and engineering teams to advance our agents, our synthetic customer capabilities and the link between strategy and deal execution.
• Pricing expertise: Adding pricing architects who work directly with customers and whose expertise shapes our AI models - see our career page.
• Go-to-market: Deepening relationships with B2B tech companies and private equity firms in the U.S. and Europe, and preparing to serve manufacturing and professional services firms as AI reshapes how they make money.

We’re also building for a future where buyers send agents to negotiate on their behalf. Companies that can price, quote and negotiate with those agents will create a competitive edge.

Pricing used to be something companies revisited every few years; we think it should run every day. If your products are moving faster than your pricing, we’d like to talk. Click here to book a conversation with our team.