# Márton Csernai, PhD Fractional CTO · AI Architect · Lead AI Engineer This is the text version of [martoncsernai.com](https://martoncsernai.com/). Hi, I'm Marci, ## I build verifiable AI with an audit trail, for regulated industries, that passes compliance review. When a customer or an investor asks how your AI reached an answer, you need to show them. I build it so you can: every answer cites its source, every action leaves a trail. I work hands-on inside your team, from designing the architecture to the conversation with your compliance lead. [Book an intro call](https://cal.com/martoncsernai) Previously led the research team behind [Deloitte's reusable KYC credentials](https://www.finextra.com/pressarticle/96717/deloitte-to-use-kilt-blockchain-to-issue-re-usable-digital-credential-for-kyc-and-kyb-processes). 15+ years building systems where being wrong is expensive. PhD in computer science, summa cum laude. ## Anyone who checks your AI asks the same four questions An auditor, a compliance lead, a customer's due diligence, your own board. I build systems that answer all four without you in the room. 1. **Where did this come from?** Every answer carries the passage it came from, in the document your team already works from. 2. **Who decided?** Where a decision needs a person, a named person approves it, as a step in the workflow, not a policy on a slide. 3. **What happened?** Every action is recorded: who, what, when, and on which evidence. 4. **What if the spec was wrong?** The rules live in a file your team can read and change. A correction becomes a rule, not a rebuild. Most systems stop at the first question. ## Work with me ### Build it to pass review "Our pilot works but would not pass review." 3-6 weeks, fixed scope. One workflow, built or hardened with the logging, evaluation and source tracking that let you prove what it does. Handed to your team with the documentation to run it. ### Lead the build "We need a senior lead who still builds" Part-time or full-time, by the month. Fractional or interim CTO or architect. I own the architecture and the delivery, write code with your engineers, and take the conversations with your auditors, customers and investors. ### Tell you where you stand "Would our AI hold up if someone looked closely?" 2-4 weeks, fixed scope. A review of one AI system or the whole estate: what it does, what it can prove, and where it would fail a customer's due diligence or a regulator's question. You get the gaps and a prioritised plan, mapped to the EU AI Act and ISO/IEC 42001 where they apply. ### How it starts 1. A 30-minute call. How you do it today, and where the risk sits. 2. A written scope with a budget estimate within one working day. 3. A first working slice in about two weeks, on your stack. 4. Handover with documentation your team can run. [Book a 30-minute intro call](https://cal.com/martoncsernai/30min). Tell me what you are building and who will use it. You get my honest read, including whether I am the right person for it. ## What I've built ### Compliance document analysis where every answer cites its source Fund-compliance RegTech, Australia. Fractional CTO, 2025 to 2026. The product reads fund documents for compliance teams, so an unsourced answer is a liability. I rebuilt how documents are split and searched, attached the source passage to every answer, and moved the agent steps into workflows where a person approves before anything is final. I also led the engineering team and the reliability work on the cloud platform (~180 managed resources), cutting service start-up from about nine minutes to under one. TypeScript · Python · Docling · LlamaIndex · pgvector · Temporal · Terraform · Google Cloud > "We ended up with a more efficient, production-suitable RAG pipeline and higher confidence in the system's outputs." > > Founder, fund-compliance RegTech - Every answer traces to a passage in the source document. - Human approval is a step inside the workflow, not a policy. ### Reusable KYC credentials with Deloitte KILT Protocol, Germany. Lead researcher, product owner, and software engineer, 2018 to 2023. A customer should not have to prove who they are from scratch at every institution. I led research and system architecture for KILT, an identity network where a credential is issued once and reused, from the whitepaper through the mainnet launch on Polkadot and a compliant token sale. Deloitte chose the network to issue reusable KYC and KYB credentials. TypeScript · Rust · AWS · Kubernetes · decentralized identity · token economics > "Márton is able to work seamlessly across teams - core devs to legal to marketing and business development, and his expertise was key to the rapid growth and success of KILT in the Polkadot ecosystem." > > Christine Mohan, former VP of BD at KILT Sources: [Finextra](https://www.finextra.com/pressarticle/96717/deloitte-to-use-kilt-blockchain-to-issue-re-usable-digital-credential-for-kyc-and-kyb-processes), [Deloitte on LinkedIn](https://www.linkedin.com/posts/deloitte_deloitte-integrates-kilt-identity-blockchain-activity-7059889405523611648-Ztjq/) and [Polkadot's Interview with Marton Csernai](https://www.youtube.com/watch?v=fCHsbs96lvE). ### New AI behaviour in days, in a form a compliance reviewer can read Mental-wellness coaching app, Germany. Fractional CTO and AI architect, 2025. Every change to what the coach says took more than two weeks and a deployment. I moved the coach's rules out of code into one file the team owns and a reviewer can read, behind a four-agent backend with a safety mode for overwhelmed users. Every rule change is scored against ten test personas by an automated evaluation. Flutter (iOS/Android) · TypeScript · multi-agent LLM backend · Promptfoo · Langfuse · OpenTelemetry · AWS > "Especially as a non-technical founder, I felt very well guided and supported." > > Founder, mental-wellness coaching app - The non-technical founder ships new features in days instead of weeks. - No lengthy app deployments to change how the AI behaves. - Ensuring GDPR-compliance by having the privacy policy verified against the code and resolving any discrepancies. ### Angel deals run over WhatsApp, from pitch deck to confirmed payment, where the AI drafts and the partner decides Angel club and early-stage fund, France. Solutions architect and engineer, 2026. The fund is placing two deals a month with its angels, chosen from hundreds of pitch decks, and was doing it by hand, one WhatsApp message at a time. Now one partner runs a round without leaving Airtable. The model drafts the investment memo from the pitch deck and marks every gap instead of filling it and the partner approves it. The chosen angels get the deal on WhatsApp, their commitments are counted against the allocation, and when the round is covered each investor confirms and is handed to the fund's SPV platform for KYC, signing and the wire transfer. The angels never install anything or learn a new tool. The partner can answer every open question personally and the system handles the rest. The first working loop ran on WhatsApp two weeks after the first call, and the fund runs it without me. Airtable · n8n · WhatsApp Business API · Claude API > "Very professional work. At every step Márton was patient and listened to what we needed, and we are really happy with what he delivered." > > Partner, angel club and early-stage fund - Gaps in a memo are marked, never filled by the model. - Only exact keywords change an investor's status; everything else goes to a person. - Every message to and from an investor is logged with its delivery status. - First working loop on real WhatsApp two weeks after the first call. ## About I hold a PhD in computer science (summa cum laude) and spent years in research before I spent years in startups. My experience spans data-centre networks, neuroscience data pipelines, identity systems, and most recently AI for regulated industries. So I work in two modes and know which one a problem needs: when to stop and think in front of a whiteboard because it saves months of work later, and when to ship by Friday. On an engagement I write the architecture, run the infrastructure, ship the code, and sit in the room with your compliance lead. I can discuss retrieval methods with your engineers and how to present evidence with your auditor in the same meeting. What I don't do is policy slideware. If an AI system cannot produce the evidence someone will ask for, I don't consider it done. Python · TypeScript · RAG · agents · evaluation · Temporal · Terraform · Google Cloud · Kubernetes ### Where I've built - 2023 to now: Independent consultant: fractional CTO, AI systems architect, lead engineer - 2024 to now: Gigentic (escrow and agentic-payments lab), co-founder and CTO - 2018 to 2023: KILT Protocol (BOTLabs GmbH): lead researcher, product owner, software engineer - 2014 to 2018: Hungarian Academy of Sciences: postdoctoral fellow, data systems and applied statistics - 2010 to 2014: Budapest University of Technology and Economics (High Speed Networks Lab): research assistant - 2012 to 2013: Telekom Innovation Laboratories, Berlin: research intern ### Selected publications - Sleep spindle dynamics is coupled to brain temperature on multiple scales. Journal of Physiology, 2019 - Simultaneous in vivo recording of local brain temperature and electrophysiological signals with a novel neural probe. Journal of Neural Engineering, 2017 - Towards 48-fold cabling complexity reduction in large flattened butterfly networks. IEEE INFOCOM, 2015 - Incrementally upgradable data center architecture using hyperbolic tessellations. Computer Networks, 2013 - KILT Protocol white paper. BOTLabs, 2020 ### On record - PhD, computer science, summa cum laude. Budapest University of Technology and Economics, 2015. - 16 peer-reviewed papers, with 100+ citations, listed on [ResearchGate](https://www.researchgate.net/profile/Marton_Csernai). - Pro Progressio Fellowship for top final-year PhD candidates, 2014. DAAD scholarship, 2006. - Code on [GitHub](https://github.com/csmarc), writing on [LinkedIn](https://www.linkedin.com/in/martoncsernai/). - English, German, Hungarian. ## Contact Dr. Márton Csernai. [hello@csernai.com](mailto:hello@csernai.com) · CV and references on request. Based in Berlin, frequently in London, working remotely. [LinkedIn](https://www.linkedin.com/in/martoncsernai/) · [GitHub](https://github.com/csmarc) · [ResearchGate](https://www.researchgate.net/profile/Marton_Csernai) · [Impressum](https://martoncsernai.com/impressum) · [Privacy](https://martoncsernai.com/datenschutz)