Java · Elixir · Blockchain

Three ecosystems.
Built for different problems.

We work with Java, Elixir, and Blockchain because they solve genuinely different problems. We don't pick a stack for every project — we match the technology to what the system actually needs to do.

Core ecosystems

The three stacks we know deeply, with the specific patterns and tooling we use day-to-day.

data_objectJava · Spring Boot

Java / Spring Boot

Our go-to for systems with complex domain logic, strict transactional guarantees, or large teams working on the same codebase. The JVM ecosystem gives us mature tooling for observability, testing, and long-term maintenance.

  • check_circleProject Reactor — reactive, non-blocking I/O
  • check_circleVirtual Threads for high-concurrency workloads
  • check_circleGraalVM Native Image for fast startup
boltElixir · OTP

Elixir / Erlang VM

The right choice when you need to handle many concurrent connections, build real-time features, or want a supervision model that recovers from failures without manual intervention.

  • check_circleOTP supervision trees for fault isolation
  • check_circleGenServer and GenStage for workload distribution
  • check_circlePhoenix LiveView for real-time interfaces
linkSolidity · Rust · EVM

Blockchain & Web3

Smart contract development and the off-chain infrastructure that keeps protocols running. We bring distributed systems rigor to on-chain design and the backend services DeFi applications depend on.

  • check_circleSolidity and Rust/Anchor smart contracts
  • check_circleThe Graph subgraphs and custom on-chain indexers
  • check_circleKeeper bots and cross-chain bridge infrastructure
How we structure systems

Patterns we apply regularly

Not every project needs all of these. We apply them when the problem calls for it, not to add complexity.

database

Event Sourcing

Store state as a sequence of events instead of overwriting it. Useful when auditability, replayability, or temporal queries matter to the business.

splitscreen

CQRS

Separate the write path from the read path when they have fundamentally different scaling or consistency needs. Avoids the trade-offs of a single model trying to do everything.

lan

Saga pattern

Manage long-running transactions across services without distributed locks. Keeps services loosely coupled while handling partial failures explicitly.

swap_horiz

Circuit Breaker

Prevent cascading failures when a downstream service degrades. Standard in any multi-service system where one slow dependency shouldn't take down the rest.

Infrastructure we work with

KubernetesOrchestration
Apache KafkaEvent streaming
PostgreSQLPrimary datastore
RedisCache / pub-sub
OpenTelemetryObservability
TerraformInfrastructure as code
DockerContainerization
PrometheusMetrics
HardhatEVM testing
The GraphChain indexing
FoundryContract testing
IPFSDecentralized storage
ChainlinkOracle network
OpenZeppelinContract security

Cloud providers

AWSGoogle CloudAzureFly.ioHetzner
Core Tech Stack
JavaSpring Boot
Elixir / OTPPhoenix · BEAM
KubernetesCloud Native
Apache KafkaEvent Streaming
Solidity / RustSmart Contracts

Not sure which stack fits your problem?

Tell us what you're building and what's breaking. We'll give you a straight answer on approach before any commitment.

Talk to an engineer