About

AI traceability for financial institutions

We develop Sigillum Finans so institutions can review AI-enabled financial transactions alongside their supporting records. Institution-hosted deployment, record integrity and standard integrations form the foundation of the product.

TEAM

Banking and technology experience

Our team combines experience in financial systems, enterprise software and machine learning to develop Sigillum Finans for institutional use.

Can Küçükgültekin

Co-founder

Distributed systems · Observability · Applied AI

Can Küçükgültekin works across distributed systems, observability and applied AI. His career includes Akbank, Doğuş Teknoloji and AXA Insurance, with work on API gateway architecture, enterprise logging, Turkish natural language processing and insurance applications. He holds a Computer Engineering degree from İstanbul Ticaret University and completed the University of Virginia’s The Economics of AI certificate program.

Murat Kırmazel

Co-founder

Banking technology · Payment systems · Systems development

Murat Kırmazel brings experience in banking technology, payment systems and systems development, having held systems development and account management roles at Akbank, Fintek and Intertech. His career also includes enterprise business solutions consulting and team leadership at Metasis Teknoloji, alongside an MBA from Kadir Has University.

Murat Özer Özaydın

Co-founder

Enterprise architecture · Service integration · Digital banking

Murat Özer Özaydın works on enterprise architecture, service integration and application platforms in banking, with software and architecture roles at Akbank, Intertech and Garanti Technology in his career. He holds a degree in Computer Engineering from Ege University, and his experience includes open banking, digital assistants and enterprise application frameworks.

Erkan Kıyak

Co-founder

Academic experience · Machine learning

Erkan Kıyak is a faculty member at Pîrî Reis University, with expertise in machine learning methods including decision trees, support vector machines and long short-term memory networks. He holds a PhD in Electronics and Computer Education and a master’s degree in Computer Engineering from Kocaeli University.

01 / Our focus

Technical and operational review of AI workflows

In financial institutions, AI, services and business rules operate at different stages of the same workflow. Evaluating a transaction requires reviewing the model response, source material, human intervention and resulting actions together.

Sigillum Finans addresses this need through record collection, correlation and evidence review. Technology, risk and audit teams can work from the same transaction records and supporting information.

02 / Our product approach

A shared product for institutional infrastructure

We develop the product for independent installations on financial institutions’ own servers and within their network boundaries. Shared service integrations can be reused across the institution’s applications.

We provide shared recording contracts, SDKs and configurable connections across languages and technologies. Institutional requirements are addressed within this common product infrastructure.

Institution-hosted deployment

An architecture that brings the portal, evidence store, witness and institutional services together within the institution’s own environment.

Record integrity

Signed receipts, an append-only record chain, separate witness comparison and offline verification.

Standard integration

SDKs, standard contracts and configurable connections to institutional systems.

03 / Development principles

Defined scope and verifiable behavior

We make each record’s provenance, scope and verification result visible. Service statements, framework observations and information produced from captured exchanges retain their own meaning.

Integrations are defined through supported runtimes and client methods. Assessment with real institutional application traffic establishes scope and operating conditions in the target environment.

AI traceability for financial institutions

Banking and technology experience

Can Küçükgültekin

Murat Kırmazel

Murat Özer Özaydın

Erkan Kıyak

Technical and operational review of AI workflows

A shared product for institutional infrastructure

Institution-hosted deployment

Record integrity

Standard integration

Defined scope and verifiable behavior

Evaluate Sigillum for your institution