ASTRINIX
WIRE-TO-WIRE 0.81 µs
SYSTEMS STUDIO
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ASTRINIX STUDIO
SYSTEMS STUDIO
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ASTRINIX
BESPOKE ENGINEERING · EST. IN THE HARD PROBLEMS
ONE COMPANY · TWO ENGINEERING DISCIPLINES

We do two very different kinds of engineering.

Astrinix builds the software other vendors avoid because it's hard. That work splits two ways: performance-critical systems where a microsecond is a specification, and custom software delivered fast across any industry. The teams, the standards, and the people are the same — the problems are not, so the two have separate homes.

Hover either card below to see that side in its own colours. Pick whichever is closer to what you came for — you can switch at any time from the header, and About, Careers, and Contact are shared.

One company
Same leadership, same engineering standards, one contract.
Same engineers
People rotate between both sides. Senior only, on either.
Two speeds
Deep and deterministic on one side, broad and fast on the other.
Not sure?
Start on either. The first call sorts out which side fits.
SYSTEMS HOVER

High-performance and low-latency engineering.

Real-time data and decision systems, deterministic transport, embedded systems, and operator-grade network infrastructure software. Narrow and deep.

<1 µs
WIRE-TO-WIRE
99.999%
AVAILABILITY TARGET
Enter Systems
MEASURED IN MICROSECONDS · BUILT FOR FIVE NINES
STUDIO HOVER

AI-native custom software, any domain.

The same engineering discipline, applied broadly and delivered on compressed timelines. AI is built into how we build. People own every judgment call.

Weeks
TO A WORKING BUILD
5 stages
NAMED AI OWNERSHIP
Enter Studio
WEEKS TO A WORKING BUILD · A NAMED ENGINEER ON EVERY MERGE
Both faces share one company, one standard of engineering, and one set of people. You can switch at any time from the header.
YOUR CHOICE IS REMEMBERED ON THIS DEVICE
BESPOKE SYSTEMS ENGINEERING

Engineering the software layer that can't afford to be slow.

Astrinix builds proprietary, high-performance software for fibre and cable network infrastructure, hardware platforms, and enterprise systems where milliseconds — and microseconds — matter.

LATENCY TRACE — 60 s ILLUSTRATIVE
0.81
µs MEDIAN
±38
ns JITTER
0
DROPS / 24 H
THE TARGETS WE ENGINEER AGAINST
<1 µs
WIRE-TO-WIRE, HELD AT PEAK LOAD
99.999%
AVAILABILITY THE DESIGN MUST MEET
Zero
DROPPED EVENTS UNDER BURST
p99.9
THE PERCENTILE WE COMMIT TO
01 / 07 THE CONSTRAINT

Our clients all share one constraint.

Live data arrives continuously, from many sources at once, and it has to be understood and acted on before the moment passes. Three kinds of engineering make that possible, and we treat them as one practice.

Understanding data as it arrives

Thousands of live streams, correlated in real time — and still correct when traffic spikes, not only at average load.

Moving it without delay

Channels where jitter, not average latency, is the failure mode. We measure continuously instead of claiming a number once.

Running it on real hardware

Software bound to the machine it lives inside, shipped on the hardware's schedule and maintained for its whole field life.

02 / 07 WHY IT MATTERS

Average performance is not the specification. Peak load is.

A stack benchmarked at steady state will pass its headline number and still miss its budget when the burst arrives. We design against the worst minute of the day, then prove it with continuous regression testing.

Astrinix-engineered stack — holds through the spike
Conventional stack — degrades and drops
EVENTS PROCESSED THROUGH A 4× TRAFFIC BURST ILLUSTRATIVE
03 / 07 WHAT WE DO

Four specializations, one discipline

Every one of them is deterministic performance applied at a different layer of the same system.

TOP LAYER 01

Real-time data and decision systems

Ingest, normalize, and correlate thousands of concurrent live sources, then act inside a strict latency budget — with replay and audit built in.

Correlation lag, p994.2 ms
Millisecond correlation across thousands of sources →
FOUNDATION 02

Low-latency communication channels

Kernel-bypass transport, NIC and driver tuning, FPGA-accelerated data paths, and jitter-controlled delivery between colocated or distributed endpoints.

Wire-to-wire, peak load<1 µs
Sub-microsecond wire-to-wire latency →
SILICON LAYER 03

Silicon-adjacent systems software

Firmware, drivers, and protocol stacks co-designed with your silicon and ODM partners from first bring-up — then owned through tape-out, qualification, and the product's full field life.

Supported field life5–10 yr
Protocol stacks from Ethernet PHY to SDN control plane →
NETWORK LAYER 04

Operator-grade network infrastructure software

NFV and SDN implementations, real-time monitoring and deep packet inspection, self-healing orchestration, and fibre access and edge network software.

Availability target99.999%
Engineered to 99.999% availability targets →
04 / 07 WHO WE BUILD FOR

Three kinds of client, one engineering team

Each engagement starts from the work that matters most to that client, and rests on the same foundation.

CLIENT TYPE 01

Network and connectivity providers

Fibre and cable network providers, ISPs, and edge or colocation operators moving from fixed appliances to virtualized, software-defined networks — without giving up five-nines reliability.

Fibre access networks NFV migration NOC tooling
Where we usually start
Operator-grade network infrastructure software
NFV and SDN, real-time network monitoring, self-healing orchestration.
Always underneath it
Low-latency communication channels
CLIENT TYPE 02

Hardware and server manufacturers

Network equipment vendors, server OEMs, and ODMs who need software as long-lived as their silicon — and data center operators who need one real-time layer across many facility systems.

Switch & router firmware Driver stacks Facility monitoring
Where we usually start
Silicon-adjacent systems software
Firmware, drivers, and protocol stacks co-designed with your silicon and hardware program.
Often alongside
Real-time data and decision systems
CLIENT TYPE 03

Enterprise and critical infrastructure

Financial infrastructure, industrial, logistics, and critical-infrastructure operators whose systems need real-time multi-source processing or a genuinely low-latency path.

Market data paths Industrial control links Event correlation
Where we usually start
Real-time data and decision systems
Ingestion, correlation, and automated decisioning with full auditability.
Always underneath it
Low-latency communication channels
05 / 07 WHAT THAT PRODUCES

Outcomes we engineer for

ILLUSTRATIVE — REPRESENTATIVE ENGAGEMENTS

Client names are withheld. The figures are the engineering targets these systems were built and measured against.

NATIONAL FIBRE NETWORK OPERATOR
0.6 s
Time to detect a cascading network incident, down from minutes.
BEFORE — 4 min 20 s
AFTER — 0.6 s

Network operations intelligence platform

Telemetry from tens of thousands of network elements, fused with operational event streams into one live picture.

DATA DISTRIBUTION NETWORK
<1 µs
Wire-to-wire latency, held at peak burst load rather than on average.
LATENCY BY PERCENTILE
p50p90p99p99.9max

Deterministic transport layer

A kernel-bypass, FPGA-assisted transport path for a high-frequency data distribution network.

NETWORK EQUIPMENT MANUFACTURER
9 months
Firmware delivered in lockstep with the hardware program's tape-out schedule.
PROGRAM PHASES
BRING-UP
DRIVERS
STACK
SHIP

Next-generation appliance firmware

Firmware and driver stack co-designed with the manufacturer's silicon partners.

06 / 07 HOW WE WORK

Architect, build, operate

Read the full approach →
01 — ARCHITECT

We establish what the system must guarantee, then design backwards from the guarantee.

TYPICALLY 3–6 WEEKS
02 — BUILD

Every increment reports its own latency, throughput, and availability numbers before it ships.

2-WEEK CYCLES, GATED
03 — OPERATE

We stay accountable past go-live, under an SLA, for as long as the system runs.

MULTI-YEAR, SLA-BACKED
07 / 07

Talk to our engineering team about your system.

Contact Astrinix
EXPERTISE

One discipline. Four places it matters most.

Deterministic, high-performance engineering applied at every layer: from the communication channel, to the firmware running on the box, to the software correlating everything happening across a network in real time.

01 / 04 THE STACK

Top to bottom

Each specialization sits at a layer. Most vendors take one of them. Because we span all four, the layers can be designed against each other rather than around each other.

TOP LAYER

Real-time data and decisions

Make sense of everything happening, while it's still happening.

Multi-source, multi-protocol ingestion at high throughput
Stream correlation and enrichment across mixed sources
Automated decisioning and action-triggering
Every decision can be explained, replayed, and audited
NETWORK LAYER

Network infrastructure

Operator-grade software for networks that can't go down.

NFV and SDN implementations replacing fixed appliances
Real-time monitoring, deep packet inspection, self-healing
Fibre access and edge network software
Integration with operational and business systems
SILICON LAYER

Silicon-adjacent systems software

Written against the datasheet, the errata, and the tape-out schedule.

Custom firmware and RTOS for line cards, optical platforms, and appliances
Hardware-software co-design from first silicon bring-up
Protocol stack implementation (TCP/IP, OpenFlow, DPDK/SPDK)
Maintenance and field upgrades across a 5–10 year lifecycle
FOUNDATION

Low-latency communication channels

Every microsecond is a design decision. This layer carries the other three.

Kernel-bypass networking (DPDK, AF_XDP, RDMA) and NIC tuning
FPGA-accelerated data paths, nanoseconds to low microseconds
Deterministic, jitter-controlled transport design
Latency benchmarking and continuous regression testing
02 / 04 WHERE THE LATENCY GOES

Every stage has a budget

NETWORK CARD KERNEL BYPASS FPGA DATA PATH APPLICATION
Card to bypass 180 ns
FPGA processing 290 ns
Normalization 220 ns
Handoff to app 120 ns
Total, wire to wire
0.81 µs
Jitter
±38 ns
Measured
Per commit
ILLUSTRATIVE FIGURES
03 / 04 HOW A SPECIALIZATION BECOMES A SYSTEM

From constraint to production

STEP 01

Name the guarantee

The latency, throughput, or availability figure the business actually depends on — written down as a number, not an adjective.

STEP 02

Find the ceiling

We benchmark the riskiest assumption on real hardware before scope is committed, so nobody discovers the limit in production.

STEP 03

Build to the budget

Every stage of the data path gets its own share of the budget, and every commit is measured against it.

STEP 04

Hold it in production

Regression testing, observability, and an SLA that keeps the guarantee true after the launch week.

04 / 04 WHY IT'S HARD

Access to speed is not the problem. Deploying it is. A stack can be benchmarked to a headline number and still miss its budget under burst load, on the third rack, after a firmware update. We name the real constraints — jitter, determinism, backward compatibility, five-nines uptime — and engineer against them explicitly.

APPROACH

Architect. Build. Operate.

We work alongside your team and stay accountable past go-live. Engagements are structured as managed engineering, not fire-and-forget delivery.

STAGE 01

Architect

Discovery, constraint-mapping, and architecture design before a line of production code is written. We establish what the system must guarantee, then design backwards from the guarantee.

Constraint map

Latency budget, throughput floor, availability target, protocol surface, hardware envelope.

Reference architecture

Data paths, failure domains, and the measurement points that will prove the design works.

Feasibility spike

The riskiest assumption gets benchmarked on real hardware before scope is committed.

STAGE 02

Build

Iterative delivery against measurable performance targets, with benchmarking inside the process rather than after it. Every increment reports its numbers.

Performance gates

An increment ships when it meets its latency, throughput, and determinism gate.

Regression harness

Latency regression tests run per commit on representative hardware, not in simulation.

Embedded with your team

Our engineers sit in your review process, your standups, and your hardware bring-up.

STAGE 03

Operate

Post-launch accountability: SLA-backed support, ongoing performance regression testing, and long-term ownership of how the system evolves.

Managed engineering

We keep responsibility for the system's performance envelope, not just its bug queue.

Lifecycle maintenance

Firmware and systems software supported across a hardware product's full field life.

Evolution roadmap

Multi-year planning against your network, silicon, or platform roadmap.

What a first year looks like

ILLUSTRATIVE SCHEDULE

A typical engagement on a real-time platform. Dates move; the sequence does not.

WORKSTREAM
Q1Q2Q3Q4
Constraint mapping
Feasibility benchmarks
Transport layer build
Correlation engine build
Regression harness
Production cutover
Managed operation

Support tiers

ILLUSTRATIVE TARGETS

Every engagement is contracted at one of three tiers. The availability figures are what the system is engineered and monitored against.

Critical
Sustained
Advisory
Availability target
99.999%
99.95%
99.5%
Downtime budget / year
5 min
4.4 h
1.8 d
Coverage
24/7 on-call, named engineers
Extended hours, follow-the-sun
Business hours
Performance testing
Per commit, on client hardware
Weekly benchmark cycle
Release-gated
Who owns it
Astrinix, whole performance envelope
Shared with your platform team
Your team, with our review

What you hold at the end

Source and toolchain

Full source, build system, and reproducible environment. The system is yours, not licensed back to you.

Benchmark record

Every performance number, with the harness that produced it, so your team can reproduce and defend it.

Architecture record

Decisions, rejected alternatives, and failure-domain analysis written down where the next engineer will find it.

Operating runbook

Alert semantics, escalation paths, and the remediation steps we use ourselves while on call for it.

TECHNOLOGY

What we actually work in.

The protocols, frameworks, and standards our engineers use daily. Filter by the specialization you care about.

01 / 03 CAPABILITY GROUPS

Kernel bypass and networking

Getting packets to the application without paying for the operating system.

DPDK AF_XDP RDMA eBPF NIC tuning

FPGA and hardware acceleration

Data paths where the work happens on the wire, not in software.

VHDL / Verilog HLS SmartNIC PTP time sync

Embedded and RTOS

Firmware for platforms that ship once and stay in the field for a decade.

Zephyr FreeRTOS Embedded Linux Yocto U-Boot Bare metal C

Protocol stacks

Implemented at the systems level, from the physical layer upward.

TCP/IP Ethernet PHY / MAC OpenFlow SPDK DPI

NFV, SDN and orchestration

Network functions as software, orchestrated and self-healing.

ONAP OSM Kubernetes OVS Fibre access

Stream processing and correlation

Where many live sources become one coherent picture.

Kafka Flink Redpanda ClickHouse Rust / C++20

Multi-protocol ingestion

The standards a real network or facility actually speaks.

gNMI SNMPv3 Redfish IPMI Modbus BACnet OPC-UA

Observability and benchmarking

How we prove a claim instead of asserting it.

OpenTelemetry Prometheus Hardware timestamping Latency regression CI

Languages we build in

Chosen per layer, for control over memory and timing.

C C++20 Rust Go Python (tooling)
02 / 03 HOW WE MEASURE

We report the tail, not the average

A median latency figure hides the cases that actually break a system. Every benchmark we publish internally is a distribution: p50 through p99.9, with the maximum observed value named.

Hardware timestamping

Measurement taken on the NIC, not in the application, so the number includes the parts software can't see.

Representative load

Replayed production traffic including its bursts, not a synthetic uniform stream.

Regression as a gate

A commit that moves p99.9 the wrong way does not merge.

LATENCY DISTRIBUTION, ENGINEERED VS CONVENTIONAL ILLUSTRATIVE
p500.81 µs · 14 µs
p990.94 µs · 62 µs
p99.91.2 µs · 180 µs
max observed1.6 µs · 410 µs
Engineered Conventional
03 / 03 STANDARDS AND PRACTICE

Security and compliance posture

We work inside client security programs — secure development lifecycle, signed firmware images, dependency provenance, and audit trails on every deployed build.

Hardware partners and platforms

Co-design alongside semiconductor and ODM partners is normal for us. We work to their reference designs, bring-up schedules, and errata.

Long-lifecycle discipline

Reproducible builds, pinned toolchains, and documented upgrade paths, because firmware written this year still has to build in eight.

ABOUT

Astrinix engineers proprietary software for the systems that cannot afford to be slow, wrong, or down.

Why we exist

Most software vendors stop where the hard part begins. When a system has to hold a latency budget under burst load, or ship firmware on a silicon schedule, or stay up to five nines, the work stops looking like application development and starts looking like engineering against physics.

We built Astrinix to take that layer. We don't sell a product. We engineer the specific system a client needs, from architecture through production operation, and we stay with it.

How we work as a team

Depth over breadth

Four specializations, deliberately narrow. We decline work that would dilute them.

Specifications, not adjectives

Every claim we make about a system is a number someone can check.

Accountability past go-live

The team that architected a system is the team still answering for it in year three.

Careers

Deterministic systems, silicon-adjacent co-design, operator-grade network infrastructure. If those are the problems you want on your desk, we should talk.

Get in touch
CONTACT

Tell us what the system has to guarantee.

An engineer, not a salesperson, will respond.

All enquiries, including careers
contact@astrinix.com
Typical first response
One business day
Registered office
Astrinix LLC
Floor No. 8, The Gate Tower 2, QFC, Doha, Qatar

What happens next

01 — FIRST CALL

Forty-five minutes with the engineer who would lead the work. We want the constraint, the current architecture, and what has already been tried.

02 — WRITTEN VIEW

Within a week you get our read on feasibility, the risks we would attack first, and whether we think we are the right team at all.

03 — SCOPED START

A short architecture engagement, priced and time-boxed, ending in a constraint map and a benchmarked feasibility spike.

Where we work

On your hardware

Bring-up and benchmarking happen on the real target — in your lab, your colocation cage, or your data center hall.

Inside your process

Your repositories, your review rules, your release train. We do not run a parallel project on the side.

Across time zones

Follow-the-sun coverage for Sustained engagements, and a named on-call engineer for Critical ones.

AI-NATIVE CUSTOM SOFTWARE

Any idea. Any domain. Built fast, built right.

Astrinix Studio is the AI-native half of Astrinix — the same engineering discipline behind our low-latency systems work, applied to custom software for any industry, at a fraction of the usual timeline.

IDEA → WORKING SOFTWARE ILLUSTRATIVE
5
PIPELINE STAGES, EACH NAMED
3 wks
TYPICAL DISCOVER → PROTOTYPE
100%
MERGES REVIEWED BY A NAMED ENGINEER
Senior
ONLY STAFFING MODEL
01 / 05 THE TRADE-OFF WE REMOVE

Custom software usually means choosing between fast and good.

Fast normally means thin: a prototype that has to be thrown away, or a template with your logo on it. Good normally means slow: months of discovery before anything runs. AI-native delivery removes the trade-off by compressing the manual-labour phases — not by lowering the engineering standard.

What AI compresses

Requirements synthesis, prototype generation, boilerplate and integration code, test coverage, and release monitoring.

What people own

Architecture, the shape of the product, every merged change, the QA gate, and accountability after launch.

What you receive

A production-grade codebase you own outright, with the architecture record and test suite that make it maintainable by anyone.

02 / 05 THE METHOD

Five stages. AI named at every one.

See the full method →

AI compresses the manual-labour phases. People own every judgment call. Here is exactly where the line sits.

01

Discover

AI: requirements synthesis from conversations, documents, and domain research.

Owner: a senior product lead who validates the brief with you before anything is built.

02

Design

AI: rapid prototyping of UX flows and architecture options.

Owner: a designer and architect who pick the direction and shape the one that ships.

03

Build

AI: agentic code generation across the stack, continuously supervised.

Owner: senior engineers. Nothing merges that a named engineer has not reviewed.

04

Verify

AI: generated test coverage and regression suites.

Owner: a human QA gate. An automated pass alone does not release.

05

Ship & operate

AI: monitoring and iteration support once live.

Owner: a named engineering contact who stays accountable post-launch.

03 / 05 ANY DOMAIN, ONE METHOD

We don't need to have built in your industry before

The method is domain-agnostic by design. Domain fluency comes from the discovery stage, not from a vertical practice we happen to have staffed.

Healthcare

Intake, triage support, clinical workflow tools.

Retail

Inventory unification, personalization, storefronts.

Logistics

Route and load planning, dispatch tooling.

Manufacturing

Shop-floor tracking, quality and defect capture.

Finance ops

Reconciliation, reporting, audit-trailed workflows.

And yours

Not built here yet. Here is the method we would bring to it.

04 / 05 PROOF

Three builds, three domains

ILLUSTRATIVE — REPRESENTATIVE PROJECTS

Each one states the business problem, what AI actually accelerated, and who signed off before it shipped.

HEALTHCARE SPRINT

Patient intake and triage assistant

Front-desk intake was slow and inconsistent across a multi-location clinic network. We built a structured intake flow that drafts a summary and flags triage priority.

WHERE THE WORK CAME FROM
AI-accelerated buildEngineer-owned decisions
3 weeks
Discover to working prototype. Every triage flag confirmed by clinical staff before action.
RETAIL FULL BUILD

Inventory and personalization engine

Inventory lived in three disconnected systems and personalization was manual. We unified the inventory layer and added an assisted recommendation engine.

WHERE THE WORK CAME FROM
AI-accelerated buildEngineer-owned decisions
Stockouts ↓
Engineers tuned and validated every model output before it reached a customer.
LOGISTICS EMBEDDED POD

Route and load optimization dashboard

Route planning at a regional freight operator was manual and reactive. The dashboard suggests routes and loads in real time; dispatchers approve every change.

WHERE THE WORK CAME FROM
AI-accelerated buildEngineer-owned decisions
Override rate
Dispatcher override rate is tracked and reported as a trust metric, not hidden.
05 / 05 ONE COMPANY, TWO DISCIPLINES
STUDIO

Broad and fast

Custom software in any domain, on compressed timelines, with AI named at every stage of delivery.

3 weeks
DISCOVER → WORKING PROTOTYPE
SYSTEMS

Narrow and deep

The same standard applied to the hardest performance work: real-time systems, deterministic transport, operator-grade network infrastructure.

<1 µs
WIRE-TO-WIRE AT PEAK LOAD
Switch to Systems

Tell us what you're building.

Start a project
WHAT WE BUILD

Real software, owned by you, in production.

Five kinds of work cover almost every project that comes to us. Each one ships as a production-grade codebase with tests, documentation, and a named engineer behind it.

01

Product MVPs

A first version that is genuinely production-grade, so validating the market doesn't mean throwing the code away afterwards.

Typical shape: Sprint, then Full Build
02

Internal tools and back-office systems

The workflow nobody sells software for: reconciliation, tracking, scheduling, approvals. Usually the highest-return work we do.

Typical shape: Full Build
03

Customer-facing applications

Web and mobile products where design, performance, and reliability are all part of the brief, not a later phase.

Typical shape: Full Build, then Pod
04

AI-assisted workflow tools

Software where a model does part of the work — drafting, matching, classifying — with a human approval step designed in from the start.

Typical shape: Sprint, then Full Build
05

Legacy modernization

Moving a system that works but can't change any more, without a rewrite-everything gamble. Behaviour is captured in tests before anything moves.

Typical shape: Pod

Not sure which one this is?

Most projects arrive as a problem, not a category. The first call sorts that out.

Describe your project

Three ways to engage

Sprint / proof of concept

A working prototype in weeks, to validate direction before committing to a full build.

2–4 WEEKS

Full build

A production-grade custom application, delivered on a compressed timeline relative to conventional development.

2–4 MONTHS

Embedded pod

An ongoing AI-native engineering team embedded with yours for continuous delivery.

ONGOING
HOW WE BUILD

We'll tell you exactly where the AI is — and where it isn't.

AI compresses the manual-labour phases. People own every judgment call. Below is the full pipeline, stage by stage, with the division of responsibility written down.

The pipeline

STAGES LIGHT UP AS YOU SCROLL
STAGE 01

Discover

Typically days, not weeks.

WHAT AI DOES

Synthesizes stakeholder conversations, existing documentation, and domain research into a structured brief, with the open questions listed rather than guessed.

WHAT A PERSON OWNS

A senior product lead validates the brief with you and signs it before any build begins. Nothing gets built from an unreviewed summary.

STAGE 02

Design

Runs concurrently with early build.

WHAT AI DOES

Generates multiple UX flows and architecture options quickly, so the choice is made against real alternatives instead of the first idea.

WHAT A PERSON OWNS

A designer and an architect select the direction and shape the one that ships. Product and engineering stay one discipline, not a handoff.

STAGE 03

Build

Where the timeline compression comes from.

WHAT AI DOES

Agentic code generation across the stack — scaffolding, integrations, migrations, and the repetitive breadth of a codebase — under continuous supervision.

WHAT A PERSON OWNS

Senior engineers direct the work and review every merged change. If a named engineer hasn't reviewed it, it isn't in your codebase.

STAGE 04

Verify

Gate, not a formality.

WHAT AI DOES

Generates test coverage and regression suites, including the edge cases a human writer would skip on a deadline.

WHAT A PERSON OWNS

A QA and engineering sign-off before release. A green pipeline on its own does not ship software here.

STAGE 05

Ship & operate

Accountability doesn't end at launch.

WHAT AI DOES

Monitors behaviour in production, surfaces regressions, and drafts the first pass at fixes and iterations.

WHAT A PERSON OWNS

A named engineering contact stays accountable after go-live, with the same review discipline applied to every change.

Why we're this explicit about it

The market has recently watched what happens when a vendor's claimed AI involvement turns out not to match the reality of who was doing the work. The lesson we took from it is not that AI claims are dangerous — it's that vague ones are.

So we don't say "AI-powered." We say which stage, what the model produced, and which named engineer approved it. If you ever want that record for a specific feature, you can have it.

OUR RULES, IN PLAIN TERMS
01

Every speed claim names the phase AI accelerated.

02

Every AI output that reaches a user was approved by a person we can name.

03

We staff senior only. AI compresses time, not standards.

04

You own the codebase, the tests, and the decision record.

ABOUT

One company. Two disciplines. One standard of engineering.

Astrinix Systems does some of the least forgiving engineering in the industry — software where a microsecond or a dropped packet is a failure. Astrinix Studio applies that same standard broadly, and quickly, to custom software in any domain.

Why both faces exist

The disciplines feed each other. Systems work forces a habit of measuring instead of asserting; Studio work forces the same team to move at product speed across unfamiliar domains. Engineers rotate between them.

It also means the answer to "can you actually build this well?" is a portfolio of the hardest work in the field, not a claim.

Who we hire

Senior, comfortable directing AI

Engineers who treat models as a fast, unreliable colleague whose output they are accountable for.

Domain-curious

People who enjoy learning a new industry's vocabulary well enough to argue about its edge cases.

Willing to sign their name

Every merge, every release, every post-launch escalation has an owner. That's the job.

Careers

Broad domains and compressed timelines on this side; deterministic systems and operator-grade network infrastructure on the other. Most people want a turn at both.

Get in touch
CONTACT

Tell us what you're building.

An engineer, not a salesperson, will respond — usually within one business day.

All enquiries, including careers
contact@astrinix.com
Typical first response
One business day
Registered office
Astrinix LLC
Floor No. 8, The Gate Tower 2, QFC, Doha, Qatar

What happens next

01 — FIRST CALL

Forty-five minutes with the engineer who would lead the work. We want the problem, the constraints, and the date that matters.

02 — SHAPE AND PRICE

Within a few days: the engagement shape we'd recommend, what the first two weeks produce, and what it costs.

03 — BUILD STARTS

Discovery and design run concurrently from week one. You see working software early, not a status report.