Christopher Jackson
Founder & CEO, Corvair Pte Ltd
35+ years at the intersection of enterprise data, analytics, and AI — from data warehousing and business intelligence through the big data era to the frontier of autonomous AI governance.
Founder & CEO, Corvair Pte Ltd
35+ years at the intersection of enterprise data, analytics, and AI — from data warehousing and business intelligence through the big data era to the frontier of autonomous AI governance.
Chris Jackson has spent more than three decades selling and delivering complex data, analytics, and AI solutions into banking, financial services, and highly regulated enterprises. His career has spanned the full arc of enterprise data — from the earliest data warehousing implementations through the analytics revolution, big data, machine learning, and now the frontier of autonomous AI agents.
As former Chief Solutions Officer at the National University of Singapore (NUS), Chris led the strategic positioning of research-driven AI and data capabilities for enterprise adoption. As former Field CTO at Teradata, he translated complex data and analytics technology into business outcomes for clients across the Asia-Pacific region, supporting a business with $200M+ in Cloud ARR.
An American citizen based in Singapore, Chris brings a dual perspective on Western and Asian regulatory environments — essential for institutions navigating the convergence of MAS AIRG, EU AI Act, US federal and state AI laws, and UAE frameworks simultaneously.
Corvair's advisory methodology is built on original intellectual property — three patent applications filed in Singapore that address the hardest unsolved problems in agentic AI governance.
Agent Governance & Cumulative Operational Authority — The agentic registry, ten-layer governance data model, dynamic risk scoring via blast radius calculation, just-in-time privilege brokering, and the application of DMAIC and Lean principles to AI governance.
Cognitive Validity & Reasoning Integrity — Epistemic drift detection, decision validity warrants, temporal truth filtering, causal dependency mapping, and source reliability assessment — ensuring agents reason on valid premises, not just produce statistically confident outputs.
Composable Auditable Reasoning — Composable lenses and points of view, the SCAR scoring rubric, veto lenses, machine-readable audit trails, and the work graph — enabling structured, multi-dimensional assessment of AI reasoning quality.
"When a bank asks 'why you and not Deloitte?' the answer is: Deloitte doesn't hold patents on agentic AI governance."
Augmentation over automation. The goal is not to replace human judgment but to concentrate it — removing coordination overhead so that the thin but critically important layer of genuine human judgment can operate at the speed of AI.
Architecture first, not policy first. Policy tells an organisation what it should do. Architecture tells it how to technically implement governance over systems that behave in emergent, non-deterministic ways.
Senior-only delivery. Every engagement is led and delivered by Chris personally. No juniors learning on your budget. No "our team will get back to you." The person who wrote the patents is the person in the room.
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