Brainqub01
Work fragmented across tools
Client onboarding, document review, reporting, and CRM updates often cross several systems and inboxes. People spend time finding context, re-keying information, and coordinating the handoffs around the work itself.
AI agent implementation for service businesses
Put AI agents to work across your operations.
Brainqub3 helps founder-led and management-led service businesses find the expensive manual workflows worth fixing, then builds reliable AI systems around them. We integrate the work with your existing tools and enable your team to run it well.
- For consultancies and information-heavy service firms
- Led by a CTO · 10+ years applied AI
- 8 AI agent platforms used in production
10+
years of applied AI delivery behind every engagement. Senior, hands-on — no juniors.
8
AI agent platforms used in production — Claude, Claude Code, NemoClaw, Gemini, Codex, OpenClaw, OpenCode, Hermes.
Where agents create leverage
Expensive manual work is often hiding in plain sight.
In service businesses, a meaningful share of cost sits in people moving information between email, documents, CRM records, and internal systems. Research is repeated, reports are assembled by hand, and client delivery depends on senior people holding the method together.
The opportunity is not to deploy AI everywhere. It is to find the workflows where an agent can improve capacity, speed, or quality without weakening judgement. We map the work, identify where human review matters, and decide what is worth implementing properly.
02
Expertise becomes the bottleneck
Proposals, analysis, and specialist deliverables depend on a small number of experienced people. Their judgement is valuable, but too much of their time is absorbed by repeatable research, drafting, and checking.
03
Output still needs control
AI can produce plausible work quickly. Dependable operations also need source evidence, permissions, evaluation, review gates, and a clear point of human accountability. Those controls need to be designed into the workflow.
The fix is the same in every case: decide how you will maintain standards before scale forces the question. That is exactly what the Claude Skills Playbook lays out.
What we do
Find it. Build it. Scale it.
Start with the operational problem, then add the technology, controls, and team practices it needs. Every engagement is senior, hands-on, and anchored in work that matters to the business.
Findopportunity
AI Workflow Discovery
We examine how work actually moves through your business: the inputs, handoffs, systems, decisions, and review points. The aim is a grounded shortlist of workflows where AI can create meaningful operational leverage, with the value, feasibility, risk, and implementation path made explicit.
Good fit if manual work is consuming expensive time or constraining capacity, but you are not yet certain which opportunity justifies a proper implementation.
Buildsystems
Agent Implementation
We design, build, and integrate AI-powered workflows around real operational work: research, analysis, reporting, document handling, onboarding, proposals, compliance, and coordination between systems. Claude is often at the core; other models, tools, and services are used where the workflow requires them.
Good fit if you have a valuable workflow worth implementing beyond a demo, with the integrations, human review, and operational ownership designed in from the start.
Deployed in production- Claude
- Claude Code
- NemoClaw
- Gemini
- Codex
- OpenClaw
- OpenCode
- Hermes
Scalecapability
Claude Enablement
We help teams use Claude and Claude Code effectively through practical training, repeatable workflows, Skills, standards, and the supporting infrastructure that good work needs. The emphasis is not tool access; it is building shared capability around the work your people already do.
Good fit if Claude is already in the business, or about to be, and you want usage to become consistent, useful, and maintainable across the team.
Assurereliability
AI System Hardening & Assurance
We strengthen AI workflows that need to move from promising to dependable. That includes evaluations, failure handling, permissions, auditability, observability, security, and the operating practices needed to maintain the system after it enters day-to-day use.
Good fit if an AI workflow already exists, or is approaching production, and the questions now concern reliability, control, and safe operational ownership.
Selected client work
Relevant to your operation. Built to hold up.
Two kinds of proof matter: relevance to the way your business works, and confidence that the engineering will stand up in a demanding environment.
Paid client work
Service-business relevance
Inclusivity EQ · Method → product
A consulting platform built on Claude for a specialist risk consultancy
A founder-led consultancy specialising in AI risk and ethical governance had spent years refining proprietary assessment frameworks, delivered by hand to clients in high-stakes, governance-heavy environments. To scale beyond manual delivery, the founder commissioned us to turn the method into a product. We began with a discovery phase covering the architecture, data flows, and a security model matched to the privacy demands of their client base, then moved into the build once the architecture was approved.
The platform is built on top of Claude. Agents convert the consultancy's framework documents into structured assessments, with a practitioner review gate at every step: the tool acts as a 'check engine light', never a replacement for expert judgement. It ships with customer and admin portals, encrypted document handling, a full audit trail, multi-respondent surveys, and report generation on the firm's own templates. The architecture is framework-agnostic, so new methodologies are uploaded as bundles with no redevelopment.
For specialist service firms, this is the relevant archetype: a hard-won methodology translated into a technology-enabled service, with practitioner review retained at every step.
"I met John at an AI conference, and within minutes of connecting, I could tell his ethics and engineering principles were sound. That first impression only deepened as our conversation grew into a working relationship and I became his client. On the things that matter most to me, ethics and transparency, he never once disappointed.
How he builds tools is only part of the story. What sets John apart is the whole package: his professionalism, his flexibility, and a rare ability to grasp complex concepts quickly and translate them into genuinely flawless work. I work with engineers every day, and few operate at his caliber.
When the goal is to build agents or tools that are ethically engineered and responsibly built, John is my first choice without hesitation."
Dr. Veronica Lawrence-Ortega · CEO & Co-Founder, Inclusivity EQ LLC
Enterprise-grade engineering
IPI Switzerland · Workshop → build
From a workshop to a build: the Swiss Federal Institute of Intellectual Property
The IT and engineering teams inside the Swiss Federal Institute of Intellectual Property (IPI) were curious about AI agents but wary, with real questions about the technology's limitations, the risks, and the impact on their work. We started with a workshop that took them from the origins of the technology to its honest limitations, and answered the strategic questions directly.
That session built confidence across the organisation. Its service development and innovation team then engaged us to advise on the architecture of an internal software research agent: one that reads across their codebase, issue tracker, documentation, and process logs — without their code ever leaving a governed environment. We guided the end-to-end architectural design, including the tooling integrations, guardrails, and governance their strict privacy requirements demanded.
Evidence that we can design serious agent systems inside strict privacy and governance constraints.
- Workshop: from the technology's origins to its honest limitations, with strategic Q&A
- Architecture advisory: an internal software research agent across codebase, issues, and docs
- Governance first: code never leaves their governed environment
Learn the method
The strategy layer most rollouts are missing.
Everything we do with clients starts from a published method. Take it for free, go deeper with the course, or bring us in to build it with you.
Free guide
The Claude Skills Playbook
Your standards cannot live in people's heads. A practical guide to turning them into shared infrastructure: how to build and govern Claude Skills across a growing organisation so quality holds as more teams adopt them.
Free blueprint
The Always-On Agent Blueprint
The blueprint behind the autonomous, always-on agent setup that practitioners across the community have used to run long-horizon work and shared team sessions.
Self-paced course
Mastering Claude Skills
From First Principles to Organisational Scale — the same thinking we bring to client engagements, made available to individuals and teams. 40+ practitioners enrolled.
"It covered everything needed to get started with skills… being 'forced' to implement a first skill was exactly the right push."AI Researcher · Fraunhofer
Why us
About Brainqub3
Brainqub3 is an AI agent implementation and enablement partner for service businesses, led by John Adeojo, a CTO with more than ten years in applied AI delivery. We focus on information-heavy operations where expensive manual work, fragmented systems, or scarce expertise is constraining capacity and client delivery.
Claude is our primary ecosystem specialism, not a limit on the problems we can solve. We work with the technologies that fit the workflow and bring enterprise-grade engineering discipline to organisations that may not have a large internal AI team: clear architecture, controlled access, evaluation, and operating practices designed around the people who will own the system.
Common questions
Asked on almost every discovery call.
Do you only work with Claude?
No. Claude is our primary specialism, but the operational problem comes first. We have deployed eight agent platforms in production: Claude, Claude Code, NemoClaw, Gemini, Codex, OpenClaw, OpenCode, Hermes. We select and combine technologies around the workflow, existing systems, risk profile, and people who will operate the result.
What kinds of workflow are a good fit?
Information-heavy workflows with a clear operational constraint are usually the best place to look: research, reporting, proposals, client onboarding, document review, compliance, CRM updates, internal knowledge, and coordination across email and systems. We assess the value, feasibility, controls, and human review needed before recommending a build.
What does an engagement actually look like?
We first understand how the work is done today and identify the workflows worth pursuing. We then design and implement the system, integrate it with the tools and controls around it, and enable the people who will use and own it. Engagements are senior and hands-on, with a defined operational problem at the centre.
Can you work inside strict privacy and governance requirements?
Yes. For the Swiss Federal Institute of Intellectual Property we designed an internal research agent architecture where code never leaves a governed environment, with the tooling integrations, guardrails, and governance their privacy requirements demanded. Constraints like these are a design input, not an obstacle.
Is this only for engineering teams?
No. Our focus is information-heavy work across client delivery, operations, legal, finance, marketing, and leadership as well as engineering. The people who understand the workflow are part of the implementation, whether or not they write code.
What size of organisation do you work with?
Our centre of gravity is founder-led and management-led service businesses, often in the £1m–£20m+ revenue range, where manual knowledge work is a meaningful operating cost. We also work with enterprise and public-sector organisations; that experience informs the engineering, security, and governance discipline we bring to every engagement.
Where are you based?
The UK. We work remotely and on-site with organisations across the UK, Europe, and beyond — recent work includes Switzerland and Germany.
The next step
Start with one workflow worth fixing.
If work is repetitive, constrained by senior capacity, or passed between too many systems, that is enough to begin. We will help you decide whether an agent is justified and what it would take to implement it reliably.