Key takeaways

• Sovereignty Starts Where Data Lives
  AI sovereignty in Capital Markets is not merely about models; it is about retaining total control over your data stack, proprietary knowledge, and operational IP.

• The 80/80/20 Rule of Workloads
  Over 80% of Capital Markets workloads do not require AI at runtime once established. Of the remaining 20% that do require AI, 80% can be handled efficiently by open-source models, reserving frontier LLMs for less than 10% of highly complex, novel queries.

• Temporal Integrity & Bitemporal Data
  General-purpose AI platforms lack inherent time awareness and state tracking. Capital Markets decisions depend on bitemporal precision and temporal integrity to prevent lookahead bias in trading models.

• The Power of the AI Harness
  An AI Harness serves as the connective layer between existing data platforms and model estates, offering guardrails, lineage, governance, and cost control without platform lock-in.

• Rapid Deployment & Value Focus
  Rather than spending months on open-ended pilots or accumulating token costs, firms can achieve production-ready, front-office outcomes in 2 to 6 weeks by targeting specific daily desk workflows and prioritising measurable business value over token usage.