Transparency
Make the basis of important conclusions understandable and accessible.
BINarrator.ai is building verifiable credit intelligence for professionals who need to understand corporate risk, not just receive a summary. Our work is rooted in deep experience across enterprise data, credit risk, and responsible technology.
Founded in Utah, USA · Built for evidence-led decision-making
In consequential decisions, the question is not only “What does the data say?” It is also “How do we know?”
Credit professionals work with information spread across financial statements, regulatory filings, debt agreements, and subsequent announcements. Finding the right figures is difficult enough. Checking definitions, reconciling inconsistencies, and understanding what remains undisclosed can be even harder.
Our founder, Dennis Sebastian, encountered these challenges across more than two decades in enterprise data, financial services, and risk analytics. As artificial intelligence made information faster to produce, an important concern remained: speed does not make an unsupported conclusion reliable.
BINarrator.ai was founded to help close that gap. We are building credit intelligence that keeps the underlying evidence visible, treats uncertainty explicitly, and helps professionals apply their own judgment with greater clarity.
Built around traceability, not black-box answersOur approach brings together analytical capability and the disciplines that make information useful in high-stakes environments.
Make the basis of important conclusions understandable and accessible.
Preserve clear responsibility for the decisions people make with AI.
Separate reported facts, interpretation, assumptions, and unknowns.
Apply new technology where it solves genuine business problems.
Build for the real pressures, responsibilities, and needs of professionals.
Help professionals examine corporate credit information, trace important figures to their sources, and understand uncertainty before acting on a conclusion.
We envision systems that extend human capability without sacrificing transparency, sound judgment, or accountability.

Dennis is an enterprise technology and analytics leader with more than 22 years of experience across financial services, credit risk, data architecture, and decision intelligence.
Before founding BINarrator.ai, he held leadership positions including Director at American Express. His work has involved modernizing analytics environments and helping build platforms used by credit-risk and underwriting professionals across global operations.
That experience shaped his view that technology must be evaluated not only by how quickly it generates an answer, but by the quality, traceability, and practical usefulness of the information behind it.
He founded BINarrator.ai in 2026 to apply this perspective to a new generation of verifiable, governance-minded intelligence systems, beginning with corporate credit analysis.
The founder’s professional journey informs the problems BINarrator.ai chooses to solve.
Experience integrating complex information environments, modernizing analytics platforms, and making data more useful to decision-makers.
Work across credit-risk and underwriting contexts where definitions, source accuracy, reporting periods, and analytical consistency matter.
A commitment to explainability, evidence traceability, governance, and human oversight as AI becomes part of enterprise workflows.
Artificial intelligence can make information faster to obtain. Our responsibility is to make it easier to understand, challenge, and trust. We are building intelligence that earns confidence through the evidence behind it.
Dennis’s work extends beyond product development to technical writing, professional knowledge-sharing, and academic peer-review activities related to enterprise analytics, responsible AI, and data governance.
These activities reflect a broader commitment to advancing useful, accountable technology and exchanging ideas with the professional and research communities.
Articles on enterprise data, analytics modernization, and responsible AI.
Contributions to peer-review activities for technical conferences.
Presentations and professional conversations about AI in credit risk.
Exploring how emerging technologies can strengthen enterprise accountability.
Try the sample, examine the evidence behind reported facts, or tell us which public companies matter to your team.