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(NSP® / 01)How we operate

Built around AI that has to hold up inside the workflows, handoffs, and deadlines a company already runs on.

How We Work

Studio team at work
(NSP® / 02)Made for live operations

Our
Method

Mapped, drawn, wired, handed over. Four passes, and at the end we are the ones who leave.

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1/4

001.Discovery

Constraint
Discovery

Before anyone writes code we sit with the work: who decides what, on which evidence, and what happens when the evidence is late.

What we analyse
  • 001.Who signs off, and on what evidence
  • 002.Which numbers people actually trust
  • 003.The judgement calls made from memory
  • 004.What already works and must survive
Stack we use
Output: a system audit report

002.Automation

Automation Design
And Agents

We turn audit findings into an automation architecture: what runs on its own, what escalates, and where a person stays in the loop.

What we analyse
  • 001.Work repeated often enough to encode
  • 002.What the system refuses to decide alone
  • 003.Where it reaches into your services
  • 004.The stop button, and who holds it
Stack we use
Output: an automation architecture

003.Architecture

Strategy And
System Blueprint

We define the long horizon: what to build, what to buy, what to retire, and how the whole thing scales without a rewrite.

What we analyse
  • 001.The one number this is meant to move
  • 002.How far your current data can carry
  • 003.What to write, what to rent, what to skip
  • 004.Who answers when a regulator asks
Stack we use
Output: a phased roadmap

004.Infrastructure

Data Infrastructure
And Foundations

Scattered records become one layer the system can lean on, with ownership, freshness and access written down beside it.

What we analyse
  • 001.Every feed the system will read
  • 002.The records that disagree with each other
  • 003.How fast a lookup has to come back
  • 004.Who may see which row, and why
Stack we use
Output: an AI ready data layer
(NSP® / 03)How we got here

Turning complex operations into systems that run themselves

From small automation scripts to production AI used by companies that cannot afford downtime.

2016 / 2018

Two Desks
And A Script

We started as two engineers writing automation for other people’s back offices.

2018 / 2021

First Client
Builds

Early client work: rules engines, queue routing, and the first models in production.

2021 / 2024

Systems
Expansion

The work grew into whole operating systems and the data layer beneath them.

2024 / Now

Operational
Systems Practice

Today we run production systems for companies across several industries.

2.4k +Decisions automated each month
0.4xPlanning time per cycle
6%Exceptions still left to a human
14Systems running in production
(NSP® / 05)Picked up along the way
  • Northline Systems ReviewOperational AI, shortlistedNorthline Systems Review2026
  • Freight Technology IndexAutomation build of the yearFreight Technology Index2025
  • Applied Systems QuarterlyStudio to watchApplied Systems Quarterly2025
  • Cadence Design RegisterData infrastructure, honourable mentionCadence Design Register2024
(NSP® / 04)Shaped by live operations

The habits that decide how a build actually goes, long before any code exists.

© / 001.

We Read The Flow First

We agree on the live constraints before anyone proposes a model.

© / 002.

We Show The Thinking

We demonstrate behaviour in a live environment, not on a slide.

© / 003.

We Sit With The Decisions

We map the logic beside the people who make the calls today.

© / 004.

We Draw The Logic

We break the work down step by step, then rebuild it as something a machine can hold.

© / 005.

We Agree On The Handoffs

We place the system across teams so nothing quietly lands on one desk.

We take the jobs where the queue cannot stop

Novelty projects are somebody else’s business. We take the work where a wrong call costs money and the queue cannot simply stop.

Start with Nullspace
Portrait of a studio engineer
(NSP® / 09)Our team

The
Workshop

A compact group of engineers and researchers shipping systems that run every day.

Work with us
1/5

The Engineering Bench

A compact group of engineers and researchers keeping production systems honest.

Imani Zuberi

Builds AI architectures that stay reliable inside live systems.

  • 001.Deploys systems into live workflows
  • 002.Designs architecture for decision automation
  • 003.Connects models to real operating data
Building AI systems for real operations
(NSP® / 11)Notes from the bench

Field notes

Working notes: arguments we lost, calls we would make again, and whatever broke in week three.

Read every note
(NSP® / 12)The mailing list

One note a month. Demo form, nothing is sent.

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Portrait of a studio principal
(NSP® / 15)What we hold to

House Rules

Five rules we will not trade away, even when a client asks nicely.

See how we operate
1/3

Every system we hand over has to earn its place. If a team cannot point at what got simpler, faster or cheaper, we built the wrong thing.

Automating everything is not the goal. The goal is a system a human can read, question and switch off at three in the morning without phoning us.

Principle: the system must earn its place
(NSP® / 14)Reach the studio

Start here

Bring a system, a workflow, or a rough idea on a napkin. We will give you the honest shape of building it and keeping it alive.

+1 (555) 218-0140
hello@nullspace.example
PIER 9, STUDIO 400, PORTLANDREMOTE BY DEFAULT, CLIENTS WORLDWIDE

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