Who Are Our Customers?

Target Market & Customer Strategy for Agentic Commerce

Audience: CEO, Sales Leadership, Business Development, Chief Product Officer
Version: 1.0 | July 2026

The Market Has Changed

For most of the history of the background screening and identity verification industry, the customer was clear: a human being at a company who needed to run background checks on employees, tenants, or contractors. The sales motion was equally clear: find the HR director, pitch the product, negotiate a contract, close the deal.

That model still exists. But it is no longer the whole story — and it is no longer the growth story.

The new customer is an AI agent. Not a human being who uses AI tools, but an autonomous software program that makes decisions, takes actions, and purchases data without any human involvement. These agents are being deployed right now, at scale, across every industry that touches identity, employment, and compliance data.

The question for any data company is not whether to serve AI agent customers. It is how to position for a market that now has two fundamentally different customer types — and how to serve both without sacrificing either.

The Three Customer Segments

Segment 1: Data Companies & Background Screening Providers

Who they are: Companies that own large databases of criminal records, employment history, identity verification data, sex offender registries, and other compliance-critical information. They currently sell this data through annual licensing contracts to enterprise customers.

Their pain: They are sitting on enormous data assets that they can only monetize through slow, expensive, human-driven sales processes. Their data acquisition costs are $6–12M per year. Their revenue model is constrained by the contract overhead that makes small customers uneconomical.

What 0x307 does for them: Transforms their data operation from a cost center into a revenue engine. Reduces acquisition costs by 60–80%. Opens their data to AI agent customers who can query it automatically, 24 hours a day, without a contract.

Deal size: $500K–$5M in Year 1 value creation (cost savings + new revenue). Grows to $10M+ annually by Year 3.

Sales motion: Executive-level (CEO, CPO, CFO). Lead with cost reduction story. Close with revenue opportunity. Use the ROI Calculator to personalize the numbers.

Buying trigger: A competitor deploys 0x307 first. Or a major customer asks for AI-agent-compatible data access. Or a regulator asks for provenance documentation they can't provide.

Segment 2: AI-Native Platforms

Who they are: Companies building AI-powered applications that need data automatically — hiring platforms, tenant screening services, compliance tools, financial underwriting systems, gig economy platforms, insurance underwriting, fraud detection.

Their pain: They are building AI agents that need to query data in real time, but the data they need is locked behind annual contracts and human-driven sales processes. Their AI agents hit walls. Applications queue up. Customers wait.

What 0x307 does for them: Gives their AI agents instant, automatic access to the data they need — at the moment they need it, at a price that makes per-query economics work. No contract. No sales cycle. No human involvement.

Deal size: $50K–$500K annually in query volume. Grows as their AI agent deployment scales.

Sales motion: Technical buyer (CTO, VP Engineering, Head of AI). Lead with protocol compatibility (we support all 12 — including whatever they're using). Close with time-to-first-query (same day vs. 6–18 months for a contract).

Buying trigger: They are building an AI agent that needs data. They hit the contract wall. They search for an alternative.

Segment 3: Enterprise Customers with Compliance Requirements

Who they are: Large enterprises — banks, insurance companies, healthcare systems, government contractors — whose AI-powered decision systems need data that comes with provenance documentation and audit trails.

Their pain: Regulators are asking hard questions about AI-generated decisions. Where did the data come from? Who authorized its use? Can you prove it was accurate at the time? They cannot answer these questions with their current data providers.

What 0x307 does for them: Provides data with built-in provenance documentation — every record comes with a complete audit trail that satisfies regulatory requirements. The compliance infrastructure is not an add-on; it is built into every transaction.

Deal size: $1M–$10M annually. Premium pricing justified by compliance documentation.

Sales motion: Compliance buyer (Chief Compliance Officer, General Counsel, Chief Risk Officer). Lead with regulatory risk story. Close with the audit trail demonstration.

Buying trigger: A regulatory inquiry they can't answer. A new compliance requirement. An AI governance policy that requires data provenance documentation.

Go-to-Market Sequencing

Phase 1: Land with Data Companies (Months 1–12)

The highest-value, highest-leverage entry point is data companies themselves. A single data company deployment:

• Generates $500K–$5M in Year 1 value (cost savings + new revenue)
• Creates a reference customer that validates the platform for every other data company
• Populates the marketplace with data products that attract AI-native platform customers
• Demonstrates the compliance infrastructure that closes enterprise deals

Target: 3–5 data company deployments in Year 1.

Phase 2: Activate AI-Native Platforms (Months 6–18)

Once data products are available in the marketplace, AI-native platforms can self-serve. The sales motion shifts from enterprise to product-led growth:

• Developers register with the gateway and run test queries
• No sales involvement required for initial adoption
• Revenue scales automatically with query volume

Target: 100–500 AI-native platform customers by end of Year 2.

Phase 3: Close Enterprise Compliance Deals (Months 12–24)

With reference customers and a proven audit trail, enterprise compliance deals become closeable:

• Use data company reference customers to validate the compliance story
• Use AI-native platform volume to demonstrate market traction
• Close 3–5 enterprise compliance deals at $1M–$5M each

Target: $10M+ in enterprise compliance revenue by Year 3.

The Ideal Customer Profile

The highest-probability, highest-value customer has all of these characteristics:

The more of these boxes a prospect checks, the faster the sales cycle and the larger the deal.