Backend systems
Event-driven runtimes that sustain tens of thousands of operations per second without collapsing under backpressure.
Independent software studio / Remote-first
We build thethings behind the screen.
Veyrion is a hands-on studio for software, SaaS, games, security and the technical problems that do not fit inside a template. We build from scratch, fix what is broken and stay close to the details.
VEYRION / SYSTEM STUDYFIG. 001
API
DATA
AUTOMATION
CONNECTED SYSTEM06 LAYERSONE COHERENT WHOLE
DRAG TO ROTATE · TOUCH TO EXPLORE
One system. Your rules.EST. 2026
Good software should feel like it was always meant to work this way.
Backend✳Frontend✳SaaS✳Games✳Security✳Automation✳Phone repair
SecurityThreat models, access rules and audit trails are designed in.
ObservabilityLogs, traces and metrics are part of the delivery.
OwnershipClear boundaries for the teams that run the system.
PerformanceBudgets are set against the workload, not a template.
01 / Capabilities
Software is only part of the job.
Automation that earns its place
Deterministic workflows that replace fragile Zapier-style glue with observable, retry-safe orchestration.
Frontend people actually want to use
Internal and customer-facing products designed around your domain, not a generic CRUD template.
Security & cybersecurity
Hardened environments with least-privilege access, audit trails, and secrets that never touch application logs.
SaaS & product systems
Retrieval, inference, and evaluation pipelines wired into production systems — not a chatbot bolted onto a landing page.
Games, tools & experiments
Strangler-fig replacements for systems that still make money but can no longer be safely changed.
02 / Interactive system study
See what happens
under the surface.
Choose a system and follow the work as it moves. This is an illustrative model, not production telemetry.
VEYRION / SYSTEM PLAYGROUND INTERACTIVE STUDY
01TriggerIncoming event
02ValidateRules & permissions
03OrchestrateReliable workflow
04DeliverObservable outcome
RETRY-SAFE WORKFLOW01 — 04 / FLOW
A CONCEPTUAL INTERACTION · NO LIVE CUSTOMER DATA
03 / System architecture
Six layers. One system.
EXPLODED SYSTEM VIEWDRAG / SELECT
Move the structure with your finger or mouse. Select a layer to inspect it.
L3 / SERVICES
Domain services with explicit boundaries
Services own a domain. They do not reach into each other's tables. Failures are isolated; latency budgets are explicit.
04 / Services
Engagement surfaces
01 Custom Software +
Greenfield products and internal tools built against your domain language. We start from constraints (latency, audit, multi-tenant, offline) and design the system backward from those constraints.
02 Backend Systems +
APIs, service meshes, and data planes that other teams can build on without asking us for a meeting. Contracts first, implementation second.
03 Automation +
Replacing human-in-the-loop operations with durable workflows: retries, dead-letter queues, exactly-once effects, and an operator console.
04 AI Integration +
Models are components, not products. We wire inference into existing systems with evaluation harnesses, fallback paths, and cost controls.
05 Data Infrastructure +
Warehouses, streaming topologies, and CDC pipelines that keep operational systems and analytical systems honest with each other.
06 Cloud Architecture +
Multi-account AWS/GCP layouts, network isolation, and delivery pipelines that a two-person team can still operate at 3 a.m.
07 Security Engineering +
Threat modeling, secrets architecture, key rotation, and audit log design — done before the first feature ships, not after the first incident.
08 Legacy Modernization +
Coexistence, not big-bang rewrites. We put a facade in front of the system that still prints money, then replace it in slices with parity tests.
05 / SCOPE
Plan the engagement
06 / Tools
Tools we reach for first
RustGoC++TypeScriptPython
PostgreSQLRedisDockerKubernetesWebAssembly
LinuxTerraformGraphQLRESTgRPC
RustGoC++TypeScriptPython
PostgreSQLRedisDockerKubernetesWebAssembly
LinuxTerraformGraphQLRESTgRPC
07 / Representative builds
Illustrative system studies, not client case studies or endorsements. Any sample metrics are conceptual, not verified production results.
Distributed Operations Platform
Problem
A multi-region operator ran plant scheduling in spreadsheets and three disconnected vendor tools. Night shifts could not see live capacity. Incidents were reconstructed from chat.
Architecture
Event-sourced operations log, regional read models, a single operator console, and a write path that survives partition.
Implementation
Go services, Postgres + logical replication, NATS for fan-out, a TypeScript console with optimistic concurrency on every mutation.
Outcome: Scheduling and incident timeline live in one system. Regional lag under 400ms. Spreadsheets retired from the critical path.
Automation Orchestration Engine
Problem
A marketplace team had 70+ Zapier zaps, no retries they trusted, and a weekly ritual of re-running failed jobs by hand.
Architecture
Durable workflow engine, idempotency keys at the edge, dead-letter with operator replay, and a typed connector SDK.
Implementation
Temporal-style orchestrators in TypeScript, Redis for leases, Postgres for history, OpenTelemetry on every activity.
Outcome: Failed work became a queue with an owner, not a Slack thread. Replay is a button. New connectors ship without touching the core.
Real-Time Analytics Infrastructure
Problem
Product and finance disagreed on revenue because three pipelines defined "paid" differently, each with a 12-hour delay.
Architecture
Canonical event bus, exactly-once loaders into a warehouse, streaming aggregates for the operator view, dbt for the semantic layer.
Implementation
Kafka, Flink-style jobs, ClickHouse for hot reads, Snowflake for finance, one metrics catalog both teams query.
Outcome: One definition of paid. Operator dashboards in seconds, finance in minutes. The argument moved from "which number" to "what to do."
AI Workflow System
Problem
A support org pasted tickets into a public chatbot. Answers drifted, no evaluation, and PII left the perimeter.
Architecture
Retrieval over an internal corpus, tool-calling into the ticketing API, an eval suite on golden tickets, and a human-confirm step on any write.
Implementation
Python inference workers, a permissions-aware retriever, streaming responses over gRPC, traces stored for weekly eval runs.
Outcome: Suggested replies stay inside the VPC. Write actions require an agent click. Quality is a number that can get worse — and we notice.
08 / Approach
How an engagement runs
01
Discover
Constraints, failure modes, and the current system's real shape. We read the code and the incident history, not just the deck.
02
Architect
Boundaries, data contracts, threat model, and a delivery sequence that can be stopped without leaving a mess.
03
Engineer
Thin vertical slices, production-like environments from week one, and interfaces frozen before internals are clever.
04
Validate
Load, failure injection, security review, and parity tests against the system being replaced. "It works on my machine" is not a gate.
05
Deploy
Progressive delivery, rollback that has been rehearsed, and on-call that includes the people who wrote the code.
06
Optimize
Latency budgets, cost, and operability after the applause. We stay through the first real traffic, not just the launch.
09 / Principles
Non-negotiable engineering
"Performance is a feature."
If a screen takes 800ms, users invent workarounds. We budget latency the way we budget scope.
"Complexity should be earned."
A new service, queue, or language is a liability until it removes a larger one. We can explain every moving part on a whiteboard.
"Security is architectural."
Authz, tenancy, and audit are designed with the data model, not bolted on as middleware the week before launch.
"Operability is the product."
A system you cannot see, stop, or roll back is not in production. It is a demo that happens to have users.
10 / Contact
Start with an architecture call
45 minutes. Technical conversation, not a sales pitch. We talk about your constraints and whether the work is in our range. If it's not, we'll tell you.
STUDIO TIME
Remote studio · --:--:-- · --
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