CentraQL ComplianceProfile: Moving Regulation Into Runtime
Compliance is not a policy document — it is code enforced at runtime. How CentraQL's ComplianceProfile and EgressGuard pull regulation into the runtime.
Articles from the BIART team on data management, business intelligence, cloud and banking technologies.
Compliance is not a policy document — it is code enforced at runtime. How CentraQL's ComplianceProfile and EgressGuard pull regulation into the runtime.
For years the data lake and the data warehouse were two separate worlds and data was copied twice. The lakehouse collapses that duality into one layer with open table formats.
Before a card transaction is approved, the fraud score must come back in 100 milliseconds. Here is how that budget is spent and how the architecture is built.
Two executives walk into a meeting with two different 'active customer' counts, and both are right. The semantic layer is the architecture that ends that expensive chaos.
A data contract turns the unspoken expectation between producer and consumer into a written agreement and brings surprise pipeline breakage close to zero.
A generic 7B model often confuses 'tahsis' with 'allocation' instead of 'underwriting'. The practical plan to teach a model the bank's vocabulary with LoRA.
Watching 200 banking KPIs purely with rules — or purely with ML — never holds. The CentraQL hybrid approach.
From a natural-language question to an answer the regulator can read: every stage of the CentraQL Copilot pipeline, what gets logged, and why hallucination risk is zero.
Data quality is debated in every meeting and nobody quotes the same number. Trust Score gives the business one metric and the regulator a piece of evidence.
BI Copilots succeed not because of the LLM brand but because of a mature semantic layer. How to build a real natural-language analytics architecture.
In 2026 the LLM debate inside banks has shifted from cloud to on-prem. A practical comparison of three engines, GPU budget and compliance.
CentraQL is not a rule engine. It is a Data Trust Platform plus a banking-compliant, natural-language AI BI Copilot. What problem does it solve, and how?