Bring an idea before it becomes a brief. Work through the possibilities, draw on what your business already knows, test a different perspective and turn a decision into something useful. AstraJax brings those capabilities together, with specialists and coaching to help you put them to work.

AI that understands what matters here.

See how context changes a decision.

Imagine a new customer wants work to start next month. The revenue looks attractive. But delivery is stretched, another customer has been promised priority and an exception needs the right person’s approval.

Those details change the decision.

With the relevant context, Clive can help you work through the options: adjust the start date, change the scope or reprioritise other work. You can check what the recommendation rests on, question it and decide what happens next.

The Household helps carry out the work you authorise. Keep the decision and its reasons in the record, ready for the next piece of work.

Your documents, decisions and conversations contain knowledge worth keeping. Clive’s Man helps turn it into a record the Household can use, with sources you can check and interpretations you can correct.

Start with the material you have. Where the knowledge is still in your head, guided conversation helps draw it out. The system suggests what is worth keeping and highlights what needs your judgement. You review what it has understood, correct it and decide what becomes trusted knowledge.

A possible price change is a proposal; an agreed change is a decision. Keeping that distinction means the Household can use what you meant, including your later corrections.

We help organise the underlying data too, with clear definitions, reliable sources and named owners. Each team contributes its own expertise, under shared rules about who can see and use it. Automation handles the routine sorting and checks, so people can focus on the decisions that need their judgement.

Clive helps you think. Pam tests assumptions. Doc helps design and build the work.

Hal helps you define what good work looks like, then assesses how your agents measure up. Clive’s Man looks after the context, while Luwani helps you become more capable of directing AI.

They bring the specialist skills. You bring the knowledge of how your business works.

You do not need to know the whole Household to begin. Start with the question, the work you want to make or the result you want to assess.

Already have agents? We’ll make the introductions.

We welcome them into the Household and help them settle in: adapting their setup, connecting the context they need and giving them a clear role. They become part of the family, with the same care and support as the rest of the Household.

Hal helps you assess the work they are already doing and identify what needs attention. You keep what is useful, with a clearer basis for deciding what to improve.

When you need a new capability, Doc helps develop the right skill, agent or workflow. You define its purpose and what a good result looks like; AstraJax provides the structure and support to build, test and maintain it.

An important decision deserves more than the first model’s verdict on its own answer.

Work through an idea with Clive, then ask Pam to test its assumptions. Drawing on a different model, Pam looks for missing evidence, hidden assumptions and alternatives worth considering.

You can weigh the proposal and the objection before deciding. Doc’s workshop carries out the work you authorise.

Routine work can run within agreed limits. Anything outside those limits comes back to the person responsible.

A confident answer is not a measure of good work.

You help set the standard. Hal helps make the comparison.

Work with Hal to turn real examples of what good looks like in your business into clear standards. The standard depends on the job: accurate information, a complete brief, a sound recommendation or an agreed process followed properly.

Examine where an agent meets that standard, where it misses and what needs to change—so a score comes with an explanation you can question.

Where the work falls short, Hal diagnoses the problem and recommends a change. Ristral looks outward for developments and methods worth considering. Doc turns justified findings—and your feedback—into proposed improvements to agents and skills.

Changes pass through review and the agreed approvals, with a clear record of what was updated and why.

We are extending this process to follow changes into everyday use and remeasure the results. An update should be judged by whether it helped, not simply whether it was published.

That care extends to the agents you bring into the Household. You keep shaping what they should achieve; we help look after how they perform.

Which result would you trust with this job?

Luwani’s coaching starts with your role, your experience and your real work: explaining what matters, asking sharper questions, recognising a weak result and directing what should happen next. As your confidence develops, you can take a greater role in shaping the tools and workflows around you.

When a result misses the mark, we look at the brief, the context and the agent’s work to understand what needs to change.

Your team helps shape the system too. Start with work people care about, let them question the results and make their feedback part of what improves. The aim is an environment they have a reason to use—and a hand in making useful.

The characters give people a familiar way into unfamiliar capabilities. You can recognise who helps you think, who challenges and who acts—and become comfortable questioning them as you learn.

Choose full story, light story or no story. The presentation changes; the roles and permissions stay the same.

Your context belongs to you. Models are guests.

A provider might raise its prices, change its privacy terms or discontinue the service you rely on. Your investment in AI should not depend on one company staying the same.

That investment is more than a subscription. It is the understanding you build over time: how your business works, what you have decided, which exceptions matter and what good looks like. When that knowledge lives only inside one platform, it becomes part of the cost of leaving.

AstraJax keeps your accumulated knowledge independent of the models that use it, in a record you can inspect, correct and export. Rather than rebuilding the relationship around each provider, different models can work from the relevant, permitted parts of the same record.

That gives you more than the freedom to switch. It lets you choose different intelligence for different work—and bring another model’s perspective to an important decision without starting the explanation again.

The principle applies to AstraJax too. We should earn your continued use, not depend on trapping your knowledge.

Change the intelligence. Keep the understanding.

Matthew Hopkinson spent seven years at Butternut Box as the company grew from 33 to 1,500 people. As Head of Sales, he led a team of 120 and understood first-hand what the operation needed.

He rebuilt the department’s fragmented operating system from the ground up, bringing its data, tools and workflows together. On that foundation, he introduced specialist AI agents that transformed how the business acquired customers through face-to-face sales. Clear responsibilities, human approval and an audit trail gave the operation a structure people could work with.

After roughly twelve months preparing the data and workflows, the first fourteen agents took two weeks to build—with AI, without hand-writing the code. Making them useful to a real team mattered as much as making them run.

Airtable invited Matthew to give a keynote at Airspace LA. He is an Airtable MVP and part of Hyperagent’s Founding 500.

His training at RADA and career in acting inform AstraJax’s approach to character, communication and teaching: helping people understand the system, find their confidence and put it to use.

That experience is the foundation of AstraJax.

Bring a recurring task, a difficult decision or a process your team knows could work better. We start with the people doing it and agree what a better result would look like.

AstraJax is in active development. Our early design partnerships combine the platform with hands-on setup, operational support and coaching.

Establish the foundation

We introduce you to the Household, organise the relevant data and context, and agree the first workflows and permissions. We help any agents you bring settle in too.

Put it to work

We establish what good looks like, test the agreed work with your team and help people get started. Their feedback and the results guide what we improve next.

Keep developing

Ongoing support brings together performance review, technical care, coaching and agreed improvements. You keep shaping the work while we help maintain the system.

Know what good work costs.

We help choose models for the work they need to do, weighing quality against running cost. Use more powerful reasoning where it makes a worthwhile difference, and assess changes against the results they deliver.

Before starting, we agree the scope, AI usage, support and price, with setup and ongoing costs shown separately. Additional work or spending is agreed in advance.

Five selected companies. $1,000 each in combined platform and AI usage credits.

Apply for early accessExplore a partnership

AI can give an unfinished idea a thinking partner, a difficult decision a serious challenge and more people the means to create what they could previously only imagine.

AstraJax exists to make that practice accessible without requiring people to become technologists or surrender control of what they know.

Business is our first proving ground. Human advancement is the larger purpose.

Read the thesis