Results from a 3-month Al discovery engagement with a $20B portfolio investment firm.
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For Halo, a UK autonomous vehicle innovator, we designed an AI Architecture that ingests, processes, and auto-deletes fleet video data, allowing them to train AI models while improving cloud and AI cost management at this same time.
Insights for IT leaders
Frontier AI Is Changing Cybersecurity, Remediation Needs to Move Faster
Vulnerability exploitation is now the top initial access vector for breaches, at 31%, while the median time to fully remediate has slipped from 32 days to 43 (Verizon 2026 DBIR). Frontier AI cuts both ways. Defenders surface exposure faster, and adversaries compress the time available to respond. CrowdStrike recorded a 27-second fastest breakout in 2025. The constraint has moved from finding vulnerabilities to fixing them. A longer findings list does not make an enterprise safer. AI earns its place in four steps: validation, prioritization, fix generation and verification. Security and engineering teams still approve every change that reaches production. Presidio […]
AI Tokens: The Next Differentiating Employee Incentive
Tokens are becoming workplace infrastructure. Like laptops and mobile stipends, AI access is moving from a competitive perk to a baseline expectation for knowledge workers. AI spend is reshaping the cost-per-hire equation. Token budgets could become a meaningful part of an employee’s fully loaded cost—not just another software line item. “No Hire, No Fire” is emerging as a workforce strategy. Organizations may use AI capacity to absorb growth while headcount stays flat or gradually declines through attrition. Token spend must be tied to measurable productivity. The advantage will go to companies that connect AI usage to defined workflows, trained employees, […]
One Foundation, Every Outcome: Why Data Modernization Runs Backwards
DATA & ANALYTICS | POINT OF VIEW For two decades, building the platform first was the right call. AI moved where the hard part lives, and the old order no longer makes sense. Most enterprise data modernization is built in the wrong order. And hardly anyone stops to question it. Here is how it usually goes. A program is funded, and a roadmap is drawn up carefully, layer by layer: land the sources, stand up the lake, build the pipelines, model the warehouse, wire in the governance, and then, at the very end, deliver something the business can actually use. […]