Bitcube
AI-accelerated software delivery at Bitcube

How We Build Software Now

Software at AI speed.
Built to hold up in production.

AI-accelerated software development from senior-led delivery pods, priced on outcomes, not hours.

Book a free AI readiness review How we engage
3–5 daysTypical delivery for a well-scoped featurevs ~2 weeks traditionally
Fixed feeEvery engagement priced on outcomesno timesheets, no drift
ISO 42001 & 27001Governed & independently auditedAI management + information security

The Problem

AI made writing code cheap.
It didn't fix delivery.

When AI generates code faster than your team can review, test, and ship it, the bottlenecks don't disappear — they shift. The tooling isn't the problem; the delivery model is.

PR reviews slow down
QA becomes the constraint
Docs lag behind
Incident risk rises with speed

The Model

We no longer sell hours.
We sell outcomes.

Hours are a poor measure of value when differences in tooling matter more than differences in individual skill. Rather than layer AI onto existing team structures and quietly bank the margin, we rebuilt how we compose teams, govern AI, and structure engagements — and we're transparent about all three. This isn't a side offering; it's how we build software now.

Traditional agency

  • ×Project manager + multiple dev tiers
  • ×QA as a separate phase
  • ×Hours billed, outcomes assumed
  • ×AI layered on quietly for margin

Bitcube pod

  • ✓Senior-weighted pod, no bloat
  • ✓Dual peer review built in
  • ✓Fixed-fee outcomes, no timesheets
  • ✓ISO 42001-governed AI, transparently

How We Deliver

A senior-weighted pod, built to review its own work.

Every engagement runs on the same four-role pod — senior throughout — backed by shared tooling, prompt templates, and review checklists that improve over time.

Client Lead

Part-time

Owns the engagement end-to-end and is your decision-making point of contact.

Lead Orchestrator

Full-time

Senior engineer who sets technical direction, reviews output, and owns what ships.

Orchestrators

Full-time ×2

Two senior engineers who direct the AI tooling and peer-review each other's work.

QA Engineer

Part-time

Owns test strategy, automated testing, and release readiness.

Scoping is more thorough

We spend more time upfront getting the specification sharp. In return, build is faster and scope creep is rarer.

Review is explicit

Every substantive output is reviewed by a second senior engineer. AI code can look right while being subtly wrong — we treat that as a first-order concern.

Velocity is different

A well-scoped feature that would have taken a traditional team two weeks is often delivered in three to five days.

Proof & Governance

Safe at production scale.
Your IP stays in your boundary.

Security and AI governance are contractual commitments, not settings. AI tooling operates within your data boundary; no client code, credentials, or business logic trains external models; oversight and accountability are documented before build begins.

ISO 42001 badge
ISO 27001 badge
Cyber Essentials badge
IASME Cyber Baseline badge
  • ISO 42001 · AI Management — Responsible-AI management — risk assessment, human oversight, data-boundary controls, and accountability for what ships.
  • ISO 27001 · Information Security — How client data, credentials, and source code are handled and protected across every engagement.
  • Cyber Essentials · UK Gov Certified — Baseline endpoint, network, and access security across our operating environment.
  • IASME Cyber Baseline · Supply Chain — Organisational and supply-chain controls, relevant for regulated-sector procurement.
See what you'll have visibility of

Every engagement includes

  • Senior-weighted pod — three senior / senior-mid engineers and a part-time QA Engineer
  • Dual peer review on every substantive piece of output
  • ISO 42001 & ISO 27001-governed delivery — documented data handling and human oversight
  • A named Client Lead as your decision-making point of contact
  • Fixed-fee, transparent commercials — no timesheets, no hidden budget drift

Failure modes we prevent

×Engineers don't trust the agents yet

✓AI involvement is explicit in every review — the team sees what was AI-assisted and how it was checked.

×Output isn't reviewed and errors compound

✓Dual peer review on every substantive output is structural to the pod, not optional.

×Compliance flags the model months later

✓ISO 42001 governance is documented before build starts — contractual, not retrofitted.

How We Engage

Three ways to work with us.

Matched to where you are — testing the relationship, committing to a build, or running an ongoing partnership. Every engagement is fixed-fee and quoted after a short scoping call, so you have indicative figures before you commit — no timesheets, no drift.

Sprints

Step 1

2–6 weeks

A working proof of how we deliver before you commit to a build — real software you can act on, not an assessment. If it converts to a Programme, part of the fee is credited against the build.

Programmes

Step 2

A defined build

Discovery-then-build under one fixed fee: a written specification before build, senior-led pod delivery, and a post-release stabilisation window.

Continuity

Step 3

Ongoing

Guaranteed delivery throughput per cycle for live products — from steady-state maintenance through active roadmap delivery.

AI development and integration

AI built into your own product

Beyond building software faster, many clients want AI inside the product itself.

We build AI features the same way we build everything else: the software owns the record, the model works behind a boundary we can test, and a person stays in the loop where the stakes are high.

Global Mediation's scheduling engine negotiates mediation dates with AI-written email that a person approves before it is sent. MORI's data warehouse brings ten systems together, with an AI agent answering trading questions in plain English.

Read the Global Mediation case study Read the MORI Reorder Tool case study Explore AI Automation

Related Work

AI in production, with the guardrails that make it safe to ship.

See All Work
Global Mediation — Bitcube case study
AI · .NET · Azure

Global Mediation

An AI scheduling engine that negotiates SEND mediation dates across five participant types — with policy and local authority rules stored as data.

Read Case Study
Temporall — Bitcube case study
SaaS · Workplace Analytics

Temporall

Eight years building and running a multi-tenant analytics platform — Google Workspace, Microsoft 365 and Slack data, now measuring AI adoption.

Read Case Study

FAQs

Frequently asked questions

If AI does the work, why are you not cheaper?

You are paying for the outcome, not the labour. Writing the code has become cheap; getting the specification right, catching what AI gets subtly wrong, integrating with your existing systems, and standing behind it when it is live has not. A legal opinion does not get cheaper because the lawyer has better research tools — the same logic applies here.

Can we not just use AI ourselves?

Some of our clients do, for some of their work, and we support that. Using AI well at production quality is a discipline, not a tool — it requires review structures, architectural judgement, and accountability that are hard to assemble quickly. Where you already have that depth in-house, you may not need us. Where you don't, our model is built around exactly that gap.

How do we know the work is good?

Three mechanisms: every substantive output is peer-reviewed by a second senior engineer; test coverage is specification-driven, not ticket-driven; and you see working software early and often — typically within the first week of build — so quality is observable, not taken on trust.

How is AI use governed on our project?

Under our ISO 42001-certified AI management system. How AI will be used, and what data it may touch, is documented before build starts rather than retrofitted, and AI involvement is explicit in every review — the team sees what was AI-assisted and how it was checked.

What does ISO 42001 certification mean for us?

It means our use of AI is independently audited against the international standard for AI management: risk assessment, human oversight, data-boundary controls and accountability for what ships. Our certificate is on the Trust page, and our article on ISO 42001 explains what it means for a software agency.

Which engagement should we start with?

Most clients start with a Sprint: two to six weeks of real, working software rather than an assessment. If it converts to a Programme, part of the fee is credited against the build. Programmes suit a defined build, and Continuity suits live products that need ongoing delivery.

What happens if the engagement does not work out?

Every engagement has explicit exit points — monthly or milestone intervals for Continuity, phase boundaries for Programmes, completion for Sprints. We do not believe in lock-in. If the fit is not working, we would rather know early and part professionally.

See it before you commit.

Start with a short, fixed-fee Sprint and watch the model produce working software — before you commit to a full build. Or book a free AI readiness review and we'll map the fastest path for your team.

Book a free AI readiness review