TRUFLOW is a data trust platform designed for regulated banks to safely power AI applications. It certifies source data for accuracy, lineage, and auditability, then enriches it with banking‑specific semantics and regulatory knowledge graphs to make AI decisions explainable and compliant. The platform also provides a governed control layer that creates approved, fit‑for‑purpose data products, minimizing rejections and ensuring continuous regulatory confidence.
Funding
Funding not disclosed
Founders
Product
Problem
Regulated banks face difficulty ensuring that AI models only consume data that is accurate, auditable, and compliant with financial regulations, leading to costly model rejections and opaque decision-making.
Solution
TruFlow offers a data trust platform that certifies source data for accuracy, lineage, and auditability before it is accessed by AI. The platform embeds banking‑specific semantics and regulatory knowledge graphs, providing context‑aware AI outputs that are explainable. Automated governance controls define and enforce fit‑for‑purpose data products, limiting AI access to approved datasets. Continuous regulatory posture intelligence evaluates model outputs against relevant rules and generates evidence to support compliance reviews. By integrating these layers—trusted data foundation, context‑aware AI, governed data products, and regulatory intelligence—TruFlow enables banks to operationalize AI with confidence and reduced rejection risk.
Target Audience
Primary customers are compliance, risk, and data science teams within regulated banks that need trustworthy data pipelines for AI-driven decision making.
Features
- Data certification engine that validates accuracy, lineage, and auditability of source data
- Finance‑domain knowledge graph that maps banking entities, relationships, and regulatory concepts
- Contextual AI layer that applies banking semantics to make model decisions explainable
- Governance module that creates and enforces approved, fit‑for‑purpose data products for AI consumption
- Real‑time regulatory posture monitoring that checks AI outputs against compliance rules and produces audit evidence
- Integrated trust scoring system that quantifies data reliability for downstream AI models