Engineering digital systems that accelerate enterprise scale on the next technology wave.

Deploying low-latency edge AI inference, reactive microservices meshes, and resilient event streaming backbones that empower enterprises to surf exponential technology transformations.

1.4B+

Daily Stream Events

p99 < 2.4ms

Edge Gateway Latency

40+

Modern Enterprise Stacks

Powering Modern Infrastructure Across Leading Enterprise Ecosystems

AWS Advanced Tier
Microsoft Azure Cloud
Google Cloud Partner
CNCF Kubernetes Certified
Snowflake Data Platform
Apache Kafka Streaming
Terraform IaC

Core service capabilities

From building greenfield platforms to re-architecting systems that have accumulated years of technical debt, our teams work across the full software engineering stack.

Sector-specific technology delivery

The technical and regulatory demands of each industry shape how systems must be built. We work within those realities, not around them.

Engineering outcomes that matter

A selection of recent engagements where technical decisions translated into measurable operational and business improvements.

Financial Services

Banking Platform Modernization

99.97% UPTIME DAILY RELEASES

A regional bank operating on a monolithic core banking platform needed to support a new portfolio of digital products without disrupting existing operations.

Challenge 12-year-old monolith with shared schema, 0 test coverage, 4-week release cycles
Approach Strangler fig migration to Java microservices on Kubernetes
Outcome Deployments from 4 weeks to daily. 99.97% availability in production.
Java Kubernetes Kafka AWS
Healthcare

Healthcare Data Platform

3 DAYS → 4H REPORTING 14 SITES

A multi-site health network needed a unified patient data platform to support clinical analytics and regulatory reporting across 14 facilities.

Challenge Patient data in 6 disparate systems, manual reporting processes, HIPAA constraints
Approach FHIR-compliant data lake on Azure with dbt transformation layer
Outcome Unified patient view across all sites; reporting time reduced from 3 days to 4 hours
Azure dbt FHIR Spark
Retail & E-Commerce

Retail Cloud Migration

11× PEAK CAPACITY -34% INFRA COST

A mid-size e-commerce retailer needed to migrate their on-premise order management and fulfillment systems ahead of a major seasonal traffic peak.

Challenge On-premise infrastructure, inability to scale for seasonal demand, high ops cost
Approach Lift-and-modernize to AWS ECS with event-driven order processing
Outcome Platform handled 11× peak traffic. Infrastructure cost reduced 34%.
AWS ECS Node.js SQS Terraform

Production-grade technologies at enterprise scale

We work with proven, stable technologies engineered for scale and long-term maintainability. Our teams maintain active production systems across these stacks.

Languages & Runtimes

Core runtimes & type systems

LTS Stacks
Java v21 LTS • Spring
Python 3.12 • AsyncIO
TypeScript 5.4 • Strict
Go 1.22 • Microservices
.NET / C# .NET 8 LTS
SQL PostgreSQL • ACID

Backend & APIs

High-throughput microservices

High TPS
Spring Boot v3.2 • WebFlux
Node.js 20 LTS • NestJS
FastAPI Pydantic • Async
gRPC Protobuf RPC
GraphQL Apollo Subgraphs
REST OpenAPI 3.1 Specs

Cloud Platforms & IaC

Landing zones & automation

Multi-Cloud
AWS EKS • Aurora • S3
Azure AKS • Cosmos DB
GCP GKE • BigQuery
Terraform IaC • Cloud Module
Docker OCI Containers
Pulumi Code-Based IaC

Data Platforms & Streaming

Distributed lakehouse & pipelines

Petabyte Scale
Kafka Event Mesh • 1M/s
Snowflake Data Cloud
Spark Distributed ETL
dbt Analytics Eng.
Redis Sub-ms Cache
Airflow DAG Workflows

Platform & DevOps

GitOps, orchestration & telemetry

Zero Downtime
Kubernetes Cluster Scaling
Helm Package Manager
Istio Zero-Trust mTLS
Prometheus Metrics & Alerting
ArgoCD GitOps Pipelines
Telemetry OpenTelemetry

Modern Web & Frontend

Component systems & SSR

Sub-1s LCP
React 18 / 19 • Components
Next.js SSR • Edge Runtime
Angular v17+ • Signals
Vue Vue 3 • Pinia
Tailwind Design Tokens
Web Comp. Shadow DOM

What distinguishes how we work

Most technology problems that look like technology problems are actually team, process, or delivery problems. Our engineers are hired to think past the immediate task and understand the systems context they're working within.

Engineers embedded in delivery, not benched

We don't maintain a large bench. Our engineers are engaged on real problems, and the people who scope your work are the people who will build it.

We work in mixed teams with your engineers

Rather than taking over systems, we prefer to integrate into your teams — transferring patterns and practices alongside the delivered work.

Architecture decisions are explained, not handed down

Every significant design choice comes with documented trade-offs and a rationale. Clients shouldn't need to reverse-engineer why their system was built the way it was.

Defined scope of work before any engagement starts

We don't start with vague retainers. Every engagement begins with a scoping phase that produces clear objectives, milestones, and success criteria.

The AlgoDomain Briefing

Architectural teardowns & enterprise engineering field notes.

Join 12,000+ technology leaders, principal engineers, and architects receiving our monthly briefing. No vendor hype, no sales decks — just concrete systems architecture, migration patterns, and hard-earned delivery lessons.

Issue #42 · Data Platforms

Strangler Fig Migrations in Core Banking at Scale

Issue #41 · Cloud Architecture

Multi-Region Kafka: Latency vs. Consistency Trade-offs

Have a technology challenge to solve?

We start every engagement with a scoping conversation — no sales pitch, no slide deck. Tell us about the problem and we'll tell you what we'd actually do about it.