The Good Tech Companies - The Art & Science of Crypto Market Making: Inside Kairon Labs

Episode Date: August 27, 2025

This story was originally published on HackerNoon at: https://hackernoon.com/the-art-and-science-of-crypto-market-making-inside-kairon-labs. Discover how market makers power crypto markets with institutional liquidity. Check more stories related to web3 at: https://hackernoon.com/c/web3. You can also check exclusive content about #web3, #blockchain, #crypto, #dlt, #kairon-labs, #good-company, #market-making, #investing, and more. This story was written by: @ishanpandey. Learn more about this writer by checking @ishanpandey's about page, and for more stories, please visit hackernoon.com. Discover how market makers power crypto markets with institutional liquidity.

This audio is presented by Hacker Noon, where anyone can learn anything about any technology. The art and science of crypto market making, inside Karon Labs, by Ashan Pondi. The crypto markets live and die on liquidity, yet few people see how bids and asks become price. Keron Labs, founded in 2018 by Yenz Willamann, CEO, and Matthias Beek, CTO, builds systems that quote, fill, and hedge across venues. Willamon leads the business and client side, while Beek focuses on proprietary trading systems and algorithms. Today, we go behind the order book to see who actually moves the coins. Ashand Pondy. Hi, Yenz, it's great to have you on our Behind the Startup series.

Let's start with your journey. What first drew you into crypto and whatled you to co-found Keron Labs in 2018, Yenz Willamon. We started Keron Labs after seeing an obvious gap. Projects needed transparent, professional liquidity so real users could transact with tight spreads and reliable depth. Matthias and I had been close friends for years. In 2017-2018, we bootstrapped the company, kept it profitable from day one, and built around a simple ethos. Do things correctly, legitimately, and sustainably, with clear client communication.

That combination of self-custody values and execution discipline remains the foundation of how we operate today. Ashand Pondi, with global market abuse rules tightening and surveillance becoming standard, in plain terms, how do you define ethical market making, what practices are in, what's out, and which internal controls and client disclosures are required as per industry standards, yen's williamen. For us, ethical market making means fair, responsible liquidity that protects market integrity, no wash trading, no conflicts of interest, and abvious toward transparency. We've stated publicly that our goal is founder and project-centric liquidity that builds trust. Trust is liquidity, underpins

our brand and risk posture. Ashan Pondi, because founders need apples to apples comparisons between offers, could you walk us through the commercial model, retainers, performance fees, risk sharing and how you align incentives with founders, avoid conflicts with venues and differentiate with competitors, Yenz Willamon. We support both structures, a straightforward retainer and a loan-based model, and our job is to educate founders on the trade-offs so they John choose what fits their treasury, timeline, and risk tolerance. Retainer Simple budgeting, cleaner governance, and strong independence from venues.

You keep control while we're measured on execution quality, spread, depth, uptime, not vanity volume. Loan model reduces upfront cash needs and can jump-start liquidity, but comes with covenants, repayment terms and potential alignment questions you should weigh carefully. We walk teams through those pros, cons transparently. For context, we also publish comparisons of market-making models and why neutrality matters for fair price discovery. Ashan Pondi, since raw volume can mask poor execution quality, what does good liquidity

look like in numbers? Which weekly KPIs should teams track, spreads, top of book depth, slippage, adverse selection, and how do you surface these in the client dashboard, yen's Willamon? We define good liquidity as tight, spread, resilient, depth, and consistent. execution, impact. Concretely, we monitor and report. Order book depth at key bands. Bid-ask spread as percent of mid-execution quality, slippage on standardized trade sizes. These are the same levers we teach publicly and the core of our weekly dashboards to founders. As venue microstructure drive strategy, how does your system differ for C-EX order books

versus AMM-based D-EXs and what adaptations matter most as you work on Solana, Radium, Yens Willamon. On centralized exchanges, CEXs, we work on an order book. Place, refresh bids and asks across multiple price levels, manage Q priority and tick size, and target measurable spread and depth so takers get consistent execution with minimal slippage. That's the classic microstructure we educate founders on publicly. On decentralized exchanges, DEXs, most venues use automated market makers, AMMs. Prices are set by pool balances, E, G, Uniswops XY equals K, trades pay protocol fees into the pool, and there's no native limit order book. The operational levers are range, fee placement and re-centering to manage inventory

drift and impermanent loss. We pair that with cross-venue hedging, arbitrage between decks and C-EX when appropriate. For context, Radium on Solana is an AMM-based decks, alongside Uniswap, curve, balancer, etc. So the same AMM principles apply. there, just optimized for that chain's tooling and throughput. Bottom line. C-EX equals quote management, order books, spread, depth, uptime. Dex equals range management, pools, fees, recentering, with hedging across venues to keep prices aligned. Ashan Pondi. Given the lessons from 2022 exchange failures, how do you manage inventory and counter-party exposure across many venues, capital segregation, limits, cross-exchange hedging, and what changed in your playbook after FTX,

Yens Willemann, our published stance is to treat regulatory and operational clarity as a competitive edge, audit-ready data, integrity first execution, no spoofing, wash-trading, and classification-aware models aligned with Micah. We combine that with a risk management program that emphasizes market risk tooling and ongoing work on counterparty, credit processes, all with a compliance builds confidence, mindset. We also educate on real exchange protocol risks in our market updates. Ashan Pondi. Since token launch outcomes hinge on fit and planning, how do you decide which projects to work with tokenomics, unlocks, liquidity budget, what's your first 90 days plan for a new token, when do extra listings help versus fragment liquidity and where do you

intentionally differ from peers versus where standardization is healthy? Yens Willamon. We select teams that treat liquidity as user experience, sound to conomics, realistic budgets, compliance posture, and a plan for organic demand. The first 90 days focus on, one, pre-launch calibration and venue mix, two, day one stabilization with spread, depth baselines, and three, capital efficiency optimization with measured venue expansion. Our public checklist stresses ethical liquidity practices and structured order book building. We also explain why strategies must be tailored pervenu, pair, a point we've addressed repeated L.Y. Ashon Pondi. Finally, for founders choosing a marketmaker for the first time. What's your practical

advice and what's the one question they should ask that almost nobody asks? Yen's Willamon. Ask any market maker to define the KPIs they'll report, spread, depth, slippage, and to show you their written policies on ethics and conflicts. Also, ask how they stay neutral relative to exchange run programs and why that matters for your token. Our articles clearly articulate our core principles, independence, transparency, and measurable execution serve as the foundation O4 approach. Don't forget to like and share the story. This author is an independent contributor publishing via our business blogging program. Hacker Noon has reviewed the report for quality, but the claims here and belong to the author. Hashtag D.Y. Thank you for listening to this Hackernoon story,

read by artificial intelligence. Visit hackernoon.com to read, write, learn and publish.