Investor FAQ (Why CueCrux Matters)

1. What market gap does CueCrux fill?

The generative AI landscape is saturated with models that produce fluent but unverifiable answers. Organisations in finance, law, engineering, medicine, and public policy cannot rely on such systems because they lack audit trails and provenance. CueCrux solves this by making every answer evidence-backed, cryptographically sealed, and reproducible. This shifts AI from a “best guess” tool into a trust-grade infrastructure layer, giving it a durable advantage in enterprise and regulated markets. It positions CueCrux at the forefront of the emerging “verifiable AI” category; a far more defensible segment than commodity LLM usage.

2. How is CueCrux different from other AI companies?

Most AI companies wrap existing models in a UX layer. CueCrux has built an end-to-end architecture for trust, including QUORUM (MiSES) evidence selection, the CROWN receipt format, provenance ledgers, hybrid retrieval, authenticated BFF patterns, ingestion pipelines, operator audits, and cost-conditioned compute governance. This creates a moat that is not reliant on model quality alone, but on structural, operational, and economic advantages. These components integrate tightly and are difficult to replicate without redesigning a company’s entire technical philosophy.

3. How does CueCrux monetise sustainably?

CueCrux monetises through CRUX credits, subscription tiers, ingestion workloads, enterprise tenants, and Private Stack deployments. CRUX pricing reflects real compute cost; verified queries, audit queries, storage, and ingestion pipelines all map directly to infrastructure spend. This yields inherently margin-predictable economics that scale with usage while avoiding runaway LLM billing. For enterprise customers, CRUX functions as a metered utility, ensuring Accountants and FinOps teams can forecast spend accurately.

4. What makes CueCrux defensible as a long-term investment?

CueCrux’s defences are fourfold:

  1. Technical moat: provenance, receipts, QUORUM (MiSES), hybrid retrieval, ATAM integrity controls.
  2. Economic moat: CRUX credit system aligns usage and cost predictably.
  3. Platform moat: WatchCrux + OpsCrux provide operator-grade observability and governance.
  4. Data moat: user-submitted artefacts, curated collections, ingestion pipelines, and evidence reuse build a proprietary knowledge graph with verifiable provenance.

This combination yields a strong retention loop and high switching costs.

5. How large is the potential target market?

CueCrux sits at the intersection of AI, compliance, legaltech, research automation, knowledge management, and enterprise process modernisation; a combined multi-billion-pound addressable market. Organisations in finance, insurance, law, consulting, healthcare, engineering, public sector, and academia all require trust-grade answers. As regulators tighten AI scrutiny, the demand for verifiable AI is projected to grow significantly faster than generic AI tools.

6. What stops a large AI provider from copying CueCrux?

CueCrux’s architecture is shaped around reproducibility, receipts, evidence, and provenance. This is at odds with the optimisation goals of most major AI vendors, who focus on throughput, cost reduction, and broad “chat assistant” usefulness.

CueCrux’s design requires:

  • different retrieval structure
  • deterministic execution pathways
  • provenance-aware ingestion
  • cryptographic signing infrastructure
  • operator independence
  • strict governance flows

Copying these features would require significant rewrites of existing architectures and business assumptions, making CueCrux’s model unusually defensible.

See also