We build the systems
where bugs cost real money

High-assurance software engineering in Haskell and Rust,
backed by formal methods when correctness matters most.
For fintech, blockchain, and deep tech.

Across Industry & Academia

IOG
Midnight Network
icp-alliance
Ton
Tezos Foundation
Ligo
Genesis Digital Assets
Biocad
Brightspec
1inch
21Shares
Gonka AI
Symbiosis finance
B2BInPay
Coffer
Blooper AI
Opium Finance
Haskell Foundation
NLNet Foundation
ITMO University
JEI
Bioinf
nixfmt
deploy-rs
GHC
10
years shipping production FP code since 2015
$25B+
combined client valuation
80
engineers
$600M+
raised by our clients
8+
blockchain networks, protocol level

Custom Software Development

What teams come to us for

Build it right the first time

Greenfield systems in Haskell and Rust, designed so whole classes of bug cannot be expressed.

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Prove it's correct

Formal methods and machine-checked proofs, for the parts of a system where nearly right is not good enough.

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Rescue what's already built

Legacy Haskell nobody can maintain, performance bottlenecks, infrastructure that doesn't scale. We take over and stabilize.

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Add capacity you can't hire

Functional programming and protocol engineers, embedded in your team, on the problems you cannot staff for.

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Where we go deeper than anyone

Haskell

We sponsor a full-time team of GHC contributors — we help build the compiler itself.

Rust

Our Rust flies on drones, powers biotech labs, and moves millions through DeFi.

Formal verification

Mathematical proofs of correctness for smart contracts and critical systems.

Blockchain

  • Canton
  • Solana
  • Cardano
  • Ethereum
  • Midnight
  • TON
  • Tezos
  • DFinity
  • Bitcoin

AI / ML

From RAG systems to distributed GPU computation protocols. Backed by our in-house science lab.

Developer tooling

We wrote nixfmt and deploy-rs — the official Nix formatter and deploy tool, running in CI across thousands of repositories.

Industries

Fintech & Banking

Payment systems, trading platforms, and Canton/DAML smart contracts for institutions.

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Web3 & DeFi

Protocol-level engineering across 8+ networks: DEXs, bridges, wallets, audits.

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Deep Tech & Hardware

Rust for devices that can't fail: drones, lab instruments, embedded systems.

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Biotech

Software for research hardware and data pipelines, from spectroscopy to drug screening.

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Dev Tools

Compilers, build systems, and developer infrastructure — including GHC itself.

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What our clients say

30+ verified reviews on Clutch

  • Solana
  • DeFi
We hired Serokell to access their expertise and to co-develop a Solana smart contract with our engineers, while also bringing Solana best practices into our team.
Product Owner1inch 5.0 · Feb 2026
  • TON
  • Cross-chain bridge
A project manager oversaw the process, while the CTO supervised and reviewed every step. All the agreements were kept. The deadlines were met.

The solution has been launched and has successfully passed a security audit.

CPOSymbiosis Finance 5.0 · Mar 2025

How we work

  1. Technical from day one

    Step 1

    Our first conversation includes people who can actually evaluate the problem.

  2. Project management included

    Step 2

    Every engagement has a bill. You don't pay a separate management markup.

  3. Close communication

    Step 3

    Shared Slack, weekly calls, clear ownership and status.

  4. A team, not a talent marketplace

    Step 4

    Typically 2–4 engineers working under Serokell technical supervision.

Latest News
& Posts

  • BlogNovember 5th, 2026 • 7 min read

    deploy-rs in 2026: reviving our Nix deployment tool

    deploy-rs kept deploying our infrastructure while its maintenance backlog grew. This year, we returned to that backlog and tagged version 1.0.0, the first versioned release of the Nix deployment tool we introduced in 2020. Here’s what changed, how we use it to deploy systems and individual services, and what we plan to tackle next.

  • BlogNovember 5th, 2026 • 5 min read

    What Anthropic's AI Proofs Mean for Formal Verification

    Some of the bugs Claude found in open-source libraries had survived trillions of fuzzing runs. It found them while trying to prove that the code could never crash on inputs within a specified size limit. Anthropic and Theorem used this approach to produce machine-checked proofs for 239 fuzz-test entry points across 123 libraries. The interesting question is what those proofs buy you. A proof can rule out a crash within the limits of its specification and machine model. Deciding whether those limits make sense for the software you actually run is a separate engineering job. We look at what Claude proved, what it took to get there, and where the work goes when proofs get cheaper.

  • NewsNovember 5th, 2026 • 2 min read

    Serokell to Take On Cardano Consensus Development

    Serokell will take on the development and maintenance of Cardano’s consensus implementation as part of Input Output’s ongoing effort to decentralize the network’s core engineering..

Talk to us

Tell us what you're building. We'll tell you honestly whether we're the right team for it — on a 30-minute technical call.

Contact us

Paris, France52 boulevard de Sébastopol, 75003

Tallinn, EstoniaPille tn 7/5-13, Kesklinna linnaosa,
Harju maakond, 10135

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