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Pricing principles

The enterprise software industry has trained its customers to accept a perverse bargain: pay before you understand, commit before you have evidence, and negotiate a renewal before the first deployment is complete. We reject every part of that model. The pricing philosophy at Nexma begins with a simple premise — if the product delivers value, the customer will pay for it, and if it does not, no contract structure on earth will make the relationship sustainable.

We do not publish pricing tiers in this document because pricing will evolve as we learn from early customers. What does not evolve are the principles. Let users experience value before asking for payment. Self-serve access, no mandatory sales call, no artificial trial limitations. An operator who discovers the platform should be productive before the procurement cycle even begins. Enterprise purchasing timelines are a reality of large organizations, but they should never prevent an individual from doing better work today than they did yesterday.

And then there is the question of how to price what Nexma delivers. Spatial work that takes an operator two weeks of manual labor costs their employer thousands in loaded salary, software licenses, and opportunity cost. The same work produced by Jax in minutes costs a fraction of a dollar in compute. The gap between those two numbers is enormous. We price between them — far below the cost of manual work, far above the cost of compute — and the customer keeps the vast majority of the savings. That is not generosity. It is the only pricing model that makes adoption frictionless and expansion inevitable.

Platform and data

Revenue comes from two sources, and both are designed to compound. The first is platform access — a per-seat subscription that scales based on the capabilities enabled, from spatial design through optimization, field operations, and multi-domain access. The second is premium data feeds: satellite imagery, real estate intelligence, threat data, and specialized geospatial intelligence that integrates natively with the platform without additional development work on either side. These feeds carry high margins because the integration cost is near zero. The data simply appears in the environment the operator already inhabits.

Legacy platforms treat data integration as a professional services engagement — weeks of custom development, schema mapping, pipelines, testing. At Nexma, a new data feed integrates through configuration, not engineering. The architecture that makes the product skill-driven also makes data monetization structurally efficient in a way that conventional approaches cannot replicate.

The cost comparison

The structural argument for what Nexma has built is economic, and it is difficult to argue against. Manual spatial operations require skilled operators working sequentially — site surveys, design work, constraint checking, revision cycles, field documentation. Each step takes days. The total cost in labor, tools, and time is measured in thousands of dollars per engagement. Yet Jax performs the same work in minutes. The compute cost is negligible. The gap between what organizations currently pay and what the work actually costs to perform is not incremental. It is structural. We capture a fraction of that gap. The customer keeps the rest.

This is not a cost reduction pitch. This is a statement about the fundamental economics that Nexma exploits: the economics of spatial work in an era when an AI agent can reason about constraints, optimize across variables, and produce validated designs faster than a human operator can open their legacy software.

Expansion revenue

Revenue grows within each account through mechanisms that are native to the architecture itself, not bolted on as upsell tactics after the fact. A customer that uses the Nexma platform for defense operations can load a telecom agent skill and apply the same system to network design, or a logistics agent skill for fleet optimization, without a new contract negotiation — just a new agent skill. This is domain cross-sell, and it works because the platform is genuinely domain-agnostic, not because a sales team has repackaged the same product with different branding.

Adoption spreads from planning to operations to field teams. Each department that adopts increases the seat count without increasing the sales effort. And as teams rely on the platform for more decisions, they consume more data feeds, each one incremental revenue at high margin. The Nexma expansion model is not a strategy we impose. It is a consequence of building something that works.

Capital efficiency

Nexma is built by a small team augmented by AI development tools. The same architecture that makes the product skill-driven makes the company capital-efficient. We do not hire a team per domain. We write an agent skill per domain. This means the ratio of revenue per employee scales differently than it does at conventional enterprise software companies, where each new vertical requires a new engineering team, a new set of domain consultants, and a new eighteen-month integration roadmap.

We intend to reach meaningful revenue before raising again. Not because we must, but because building a capital-disciplined company from the beginning is a strategic advantage that compounds over every year of operation. The industry has spent two decades proving that burning capital faster than your competitors is not a strategy. It is a habit. We do not intend to acquire it.