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The team

We craft the wings.And we tell you how high to fly.

Two founders who’ve been building together since 2017, and the engineers they trust to do it with them.

The founders

Tesh works out what’s worth building. Kaz works out how, and whether AI belongs in it.

Between them they’ve built a bank, a lender, an ESG data product and a HealthTech, raised money before there was a product, and taken a client to a liquidity exit.
Tesh, Co-founder and CEO of Daedalus

Tesh

Co-founder & CEO. Product, capital and regulation.

Venture capital, then KPMG financial services, then fintech founder, COO and Head of Product. Across that career and Daedalus, Tesh has built a banking platform for family offices, an FCA-regulated consumer lender and blockchain proofs of concept with Credit Suisse, BNP Paribas, Sainsbury’s and Unilever, and raised money for all of it.

“Ask me what your regulator will ask first, and what your investors will ask next.”

Kaz, Co-founder and CTO of Daedalus

Kaz

Co-founder & CTO. Data, AI and operations.

A string theorist who became a data scientist, which turned out to be the more practical career. Across that career and Daedalus, Kaz has built a global customer service engine and predictive call routing for a multinational telco, advised FTSE 250 brands on data and run operations for a London SME.

“Ask me whether you actually need AI, and where your data is worth more than your model.”

  • They argue so you don’t pay for it

    An unresolved disagreement once cost them a company. Now they settle it first, and you get one answer, tested from two sides.

  • Commercial and technical in one room

    What to build, how to fund it and whether the tech will hold, answered together rather than handed between departments.

The Wingman Rule

“Have you seen Top Gun? You never leave your wingman.”

After Wathe, Tesh and Kaz interviewed at the same corporate, on the promise that they’d be hired at the same time. It turned out the corporate only wanted Kaz. Both had mortgages due and empty bank accounts.

Friday

Kaz turned the offer down.

Monday

Tesh and Kaz started Daedalus.

The founder story

Nine years, two companies lost, and a lot of results since.

Tesh and Kaz learned what getting it right first time means the expensive way, which is why Daedalus insists on it now.
  1. 2017

    Tesh and Kaz meet at a startup.

    A product-and-capital operator from KPMG and venture capital, and a theoretical physicist turned data scientist. They knew within weeks that they’d build together.

  2. 2017–2020

    Datawok: 50 paying users in four months.

    You chuck your spreadsheets in and forecasts come out, hence the name. There were term sheets on the table, then Covid arrived and Shopify swallowed the market.

  3. 2021–2022

    Wathe: £500k raised in six weeks.

    Making money from day one, sold to SME lenders and FCA-authorised. Then government bounce-back loans wiped out the market overnight. To lose one start-up to a pandemic is unlucky. To lose two feels as if the universe is making a point.

  4. 2022

    Daedalus begins.

    A favour for a friend became a proof of concept built in five 20-hour days, then a seven-figure annual retainer. Debt-free in twelve months.

The expensive mistakes, so you can skip them.

  • They built machine learning where something far simpler would have got them to market in half the time.

  • They gave two early engineers 10% each, and top-tier VCs read the cap table as inexperience. The VCs were right.

  • They raised 12 months of runway when they needed 18 to 24.

Why Daedalus?

In the myth, Daedalus built the labyrinth for King Minos, then the wings that carried him and his son Icarus out of Crete. He gave Icarus one warning: not too low, and not too close to the sun. Icarus flew too high and the wax gave way. Daedalus landed.

  • The labyrinth. Complex, regulated systems, designed so that the right path through them exists and is written down.
  • The wings. Engineering that carries real weight in production, built by people who put their names on it.
  • The warning. We’ll tell you where the heat starts, even when that means telling you not to build at all.

Named engineers

When we started Daedalus, we called the best people we’d ever worked with.

Tesh and Kaz have worked with these engineers across their careers, long before Daedalus existed. They’re the people we trust, so we asked them to come with us. They’ve been here since the beginning, and they’ve been moving the needle for clients ever since.
  • We already knew what they could do

    Nobody here was hired off a CV and a good interview. We’d seen their work for years before we asked them to join.

  • You get a team, not a bench

    Everyone has shipped together before, so a pod starts as a team. You don’t pay for the introductions.

  • They move the needle

    Multi-million deals now run on a football-finance platform they built. And in a live run of a real-time calculation engine, with every worker killed mid-stream, every result still matched.

Meet them.

Book one engineer for a focused problem, or a pod shaped around the skills it needs. How engineer engagements work
Edward

Edward

Head of Engineering. Fintech, distributed systems and AI engineering. London, remote, hybrid or on-site.

One of the first hires at Ethereum. Specialises in systems where being wrong is expensive, owning architecture, infrastructure and delivery from the first requirements call.

Bring Edward in for a demanding platform build, a critical system that needs technical ownership, or a team adopting agent-driven engineering safely.

  • Led engineering, directly with the client, on a multi-party football-finance platform that now runs multi-million deals.
  • Architected a fault-tolerant real-time calculation engine: with every worker killed mid-stream in a live run, every result still matched an independent reference.
  • Designed an AI engineering system where many agents work in parallel on one codebase, with architecture enforced by machine.
  • TypeScript
  • Kotlin
  • Kafka
  • Flink
  • PostgreSQL
  • AWS
  • Pulumi
  • Claude Code
  • Codex
Patrik

Patrik

Forward Deployed Engineer. Fintech platforms and data integration. Remote.

A full-stack engineer who works directly with clients and has delivered across the entire stack of two complex financial platforms, working AI-first with Claude Code and Codex.

Bring Patrik in for a remote assignment spanning complex product workflows, identity, data integration and the tools your operators depend on.

  • Built the core deal machinery of a football-finance platform running multi-million deals: contracts, negotiation, virtual data rooms and a bidding room.
  • Modelled five types of football financing in the application schema and clause seeder.
  • Built change-data-capture and calculation services, then the authentication and design system, for a real-time market-data platform.
  • TypeScript
  • Next.js
  • React
  • GraphQL
  • PostgreSQL
  • Kafka
  • Debezium
  • Pulumi
  • Keycloak
  • Claude Code
  • Codex
Dylan

Dylan

Forward Deployed Engineer. Fintech workflows and product engineering. London, remote, hybrid or on-site.

A full-stack engineer who works directly with clients and AI-first with Claude Code and Codex, with a computer science degree and an enterprise IT background at an international law firm.

Bring Dylan in for a complex finance journey, account security or billing that needs building across product and backend, especially inside an established organisation.

  • Delivered rule-heavy financing workflows on a football-finance platform running multi-million deals, including financier matchmaking and league rules.
  • Built financing offers, payables and calculated fields, plus one-time passcodes, recovery codes and an identity provider upgrade.
  • Built subscription, usage and payment flows, and live data delivery over WebSockets, for a real-time market-data platform.
  • TypeScript
  • Python
  • Next.js
  • React
  • GraphQL
  • PostgreSQL
  • Kysely
  • WebSockets
  • Keycloak
  • Claude Code
  • Codex
Ken

Ken

Data Lead and Forward Deployed Engineer. Data engineering and quantitative analysis. Remote.

A data-focused engineer who works directly with clients and builds the parts of a platform where data has to be right, working AI-first with Claude Code and Codex. With Daedalus since 2023, and holds an MSc in Mathematics and Computer Science.

Bring Ken in for third-party data that has to land in your platform correctly, live calculations on streaming data, or market data that needs turning into models you can test.

  • Built the sports-data synchronisation layer of a football-finance platform running multi-million deals, and designed its contract data model with versioned clauses.
  • Built and tuned the live-calculation operators of a real-time market-data platform, with load testing and dashboards for the engine.
  • Built the platform’s quantitative research notebooks and the Python library behind them, including models fitted on more than a million trades per asset.
  • Python
  • SQL
  • PostgreSQL
  • Kafka
  • Flink
  • Kotlin
  • Protobuf
  • pandas
  • AWS
  • Claude Code
  • Codex

Get both founders from the first call.

A free hour with Tesh and Kaz. If a spreadsheet and two rules would do the job, we’ll say so.