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Technology executive · Co-founder & CTO

Mykola Svystun

Building the technology,teams and cadencethat take productsfrom zero to scale.

From one of the first Bitcoin exchanges to enterprise data platforms, cross-chain infrastructure and private on-premise AI. Eighteen years of shipping, leading and re-architecting under real load.

Selected impactConnect on LinkedIn
Mykola Svystun, portrait
Mykola Svystunsvystun.org

02Profile

I am a founder-operator who still writes the code that matters.

For eighteen years I have built and led software organizations at the point where strategy meets execution: building CEX.IO with four others out of a small apartment in the earliest days of Bitcoin, running engineering for IO-Tahoe through its acquisition by Hitachi Vantara, designing the platform behind LI.FI's cross-chain infrastructure, and taking Ociety from concept to production as CTO.

Today I am co-founder and CTO of Veltrix, where we build on-premise LLM and retrieval systems for organizations that cannot let their data leave the building.

Where I do my best work

  • 01Founding and early-stage companies that need a technology function built from nothing
  • 02Scale-ups where the platform has to survive real traffic across continents
  • 03Established products that need re-architecture without stopping delivery
  • 04Regulated or data-sensitive environments adopting AI on their own infrastructure

03Scale

Numbers that describe the rooms I have been in.

  • Years building software

    From JavaScript developer in 2007 to CTO

  • Registered users

    CEX.IO, which began as five people in a small apartment

  • Raised by LI.FI

    Including a $29M Series A, on a platform I architected

  • Acquisition

    IO-Tahoe, acquired by Hitachi Vantara

  • Months, concept to production

    Ociety consumer platform as CTO

  • Engineers led

    Teams of 10–20 across four organizations

04Experience

Companies founded, scaled or rebuilt across eighteen years. Several of them at the same time.

Each role is listed with the environment I entered, what I was accountable for and what changed. Open a row for the detail.

Career history

  • AI company building on-premise LLM and retrieval systems for organizations where privacy and compliance are non-negotiable.

    Mandate

    Technology strategy and end-to-end delivery. A team of 10–20 engineers.

    veltrix.com

    What changed

    • Retrieval-augmented generation systems that keep every byte of client data in-house.
    • A multi-agent framework for retrieval, extraction and validation that runs entirely on local infrastructure.
    • An OCR pipeline turning unstructured PDFs into structured data across Neo4j and PostgreSQL.
    • Production NLP pipelines and Kubernetes-based CI/CD on Azure.

  • Social platform for dog owners, built end to end as a founder project.

    Mandate

    Product, architecture and delivery of the whole platform, from first commit to production.

    doggs.life

    What changed

    • Next.js front end with server-side rendering and static generation.
    • GraphQL API on Apollo Server with custom schema stitching across microservices.
    • Real-time WebSocket messaging and TensorFlow.js-powered content recommendations.
    • CI/CD with GitHub Actions, Docker and AWS ECS.

  • Consumer platform using AI to connect people with businesses through shared interests and personalized offers.

    Mandate

    Joined as Architect, promoted to CTO. Led a 10–20 person engineering team.

    What changed

    • Took the product from concept to production release in six months.
    • Rebuilt a broken delivery process around Kanban and established a predictable release cadence.
    • Architected AWS infrastructure (Lambda, RDS, EKS), Node.js microservices and React Native apps with automated store releases.
    • Shipped ML-driven personalization and recommendation features.

  • Cross-chain swap and bridge-aggregation platform, later backed by $51.7M in funding.

    Mandate

    Platform, infrastructure and backend architecture during the company's formative period.

    li.fi

    What changed

    • Designed the DevOps platform: Kubernetes, ArgoCD, GitOps and fully automated environment creation.
    • Built a stateless backend serving high-load traffic across cross-continent EKS clusters on sharded MongoDB Atlas.
    • Migrated the API layer from Express to Fastify to raise throughput under load.
    • Infrastructure as code with Terraform and Helm.

  • Enterprise data-management and data-governance products. Joined as IO-Tahoe, acquired by Hitachi Vantara.

    Mandate

    Joined as Team Lead Developer, promoted to Engineering Manager. Led teams of 10–20 engineers.

    What changed

    • Re-architected the flagship product from a JVM/AngularJS stack to Node.js SSR and React, defining the target architecture and migration path.
    • Integrated ML-based cross-database data-sampling into the product.
    • Drove adoption of microservices, GraphQL and serverless patterns across the platform.

  • One of the earliest Bitcoin exchanges, today serving 15M+ registered users.

    Mandate

    One of five people building the exchange from a small apartment. Led development of the trading platform.

    cex.io

    What changed

    • Built a high-load trading platform on Node.js, Redis and MongoDB with real-time WebSocket order flow.
    • Integrated fiat payment systems and designed secure data-management flows.
2007 — 2013

Senior and lead full-stack roles at Svialcom, Softprom, Catapult Music and Galnaftogaz.

05Selected impact

Situations I was brought in to change, and what changed.

Selected executive impact

  1. 01CEX.IO

    Building an exchange before the market had rules

    Founding · High-load systems

    Challenge
    In 2013 Bitcoin trading infrastructure barely existed. Order books had to stay consistent under bursty, adversarial traffic, and fiat rails had to be integrated where few banks would engage.
    Leadership action
    Joined as one of five people building the exchange from a small apartment and led the engineering team. Built the trading core on Node.js, Redis and MongoDB with WebSocket order flow, integrated fiat payment systems and designed the secure data-handling model.
    Outcome
    One of the earliest Bitcoin exchanges went live and remained operating. CEX.IO has since grown to more than 15 million registered users.

  2. 02IO-Tahoe → Hitachi Vantara

    Re-architecting the flagship product without stopping delivery

    Modernization · Enterprise data

    Challenge
    An enterprise data-governance product on a JVM and AngularJS stack was slowing the team down and limiting what the product could become.
    Leadership action
    Defined the target architecture and a migration path to Node.js server-side rendering and React. Led 10–20 engineers through the transition while introducing microservices, GraphQL and serverless patterns, and integrating ML-based data sampling.
    Outcome
    The platform was modernized in flight. IO-Tahoe was acquired by Hitachi Vantara, where I continued to lead engineering.

  3. 03LI.FI

    A platform that could grow with a cross-chain business

    Platform engineering · Scale

    Challenge
    A cross-chain aggregation business needs a backend that stays correct and fast across continents, and an engineering platform that lets a small team ship constantly.
    Leadership action
    Designed the DevOps platform on Kubernetes and ArgoCD with GitOps and automated environments. Built a stateless backend across cross-continent EKS clusters on sharded MongoDB Atlas, and migrated the API layer from Express to Fastify.
    Outcome
    Higher throughput under load and a delivery platform that scaled with the company. LI.FI went on to raise $51.7 million, including a $29 million Series A.

  4. 04Ociety

    Concept to production in six months, then a delivery turnaround

    Zero to one · Operating cadence

    Challenge
    A consumer AI product with no platform, no release process and a team that needed direction.
    Leadership action
    As Architect, then CTO, designed the AWS infrastructure and microservices backend, built the mobile apps with automated releases, and replaced the broken process with Kanban and a predictable release rhythm.
    Outcome
    Production release in six months, ML-driven personalization shipped, and a 10–20 person team with a cadence it could sustain.

  5. 05Veltrix

    Enterprise AI that never leaves the building

    Applied AI · Privacy

    Challenge
    Organizations in regulated and data-sensitive sectors want LLM capabilities but cannot send documents to a third-party API.
    Leadership action
    Co-founded Veltrix and own the technology. Designed on-premise retrieval-augmented generation, a local multi-agent framework for retrieval, extraction and validation, and an OCR pipeline that structures PDFs into graph and relational stores.
    Outcome
    Production NLP systems running entirely on client infrastructure, delivered by a team of 10–20 engineers.

06Expertise

Six things I am asked to do again and again.

Areas of expertise

  • 01

    Applied AI & private LLM systems

    Retrieval-augmented generation, multi-agent pipelines and document intelligence that run on infrastructure the client controls.

  • 02

    High-load distributed platforms

    Trading, cross-chain and consumer systems built to stay correct under bursty traffic across regions.

  • 03

    Cloud & platform engineering

    AWS and Azure, Kubernetes, GitOps and infrastructure as code that let small teams ship continuously.

  • 04

    Re-architecture & modernization

    Moving established products to new stacks and patterns without pausing the roadmap.

  • 05

    Founding & scaling engineering organizations

    Hiring, structure and operating cadence for teams of 10–20, from first engineer to predictable releases.

  • 06

    Blockchain & financial infrastructure

    Exchange systems, fiat integration, cross-chain protocols and the security discipline they demand.

07How I lead

Own the outcome, stay close to the work.

  • 01

    Hands-on to the end

    I have stayed technical through every leadership role. Decisions about architecture, hiring and roadmap are better when the person making them can still read the pull request.

  • 02

    Cadence over heroics

    At Ociety the fix was not more effort, it was a process the team could sustain. Predictable releases are a leadership deliverable.

  • 03

    Modernize in flight

    Re-architecting IO-Tahoe's flagship while it kept shipping taught me that the migration path matters as much as the target.

  • 04

    Build what has to be trusted

    Exchanges, cross-chain bridges and on-premise AI all fail in public. Security, correctness and data handling are designed in, not audited on.

08Organizations

Organizations and industries

Digital assets & exchangesEnterprise data & governanceCross-chain infrastructureConsumer AIPrivate enterprise AI

09Credentials

Education and credentials

Education

M.S., Mechanics and Mathematics

Statistics & Machine Learning

Ivan Franko National University of Lviv, 2009

Certification

OMG Certified UML Professional (OCUP)

Languages

English · Ukrainian

12Contact

Good conversations usually start with a short introduction.

If you are building something that needs a technology leader who will still be in the details, or you would like to compare notes on private AI, platform engineering or early-stage engineering organizations, I would be glad to hear from you.

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GitHub
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Miami, FL · Working globally