Not isolated tools, but an AI team that works together.
We build AI systems that carry a task from end to end: they analyse, plan, produce, and report the result. A person directs, the system produces. We use this approach in our own daily operation, our internal work runs on a multi-agent system we call Cordyceps.
Service scope
Multi-agent systems
Agents with distinct responsibilities working together, with the division of labour and approval steps written down. Every outward-facing output passes a human gate.
Process automation
Repetitive knowledge work automated end to end: reporting, correspondence, data collection, monitoring. The work that consumes hours and produces no judgement.
Internal assistants
Assistants connected to your own documents and systems, with access boundaries defined up front. Who may see what is a design decision, not an afterthought.
Visibility in AI engines
Making sure generative engines describe your brand correctly and consistently: structured data, llms.txt, entity identity, and measurement of how you are cited.
Our delivery approach
- 01 / 4
Understand the process
We separate what should be automated from what must stay with a person, before writing anything.
- 02 / 4
Design boundaries and authority
What the system may reach, what it may do on its own, and what requires approval are written down and agreed.
- 03 / 4
Build and measure
The system goes live with checks that catch fabrication and error early. If it cannot verify something, it says so rather than inventing.
- 04 / 4
Hand over or operate
Transferred to your team with documentation, or operated by us under a managed-service agreement.
Business outcomes
- Measurable time returned on repetitive knowledge work
- An auditable flow where every outward output passes a human gate
- Written, reviewable access boundaries instead of implicit trust
- A brand that generative AI engines describe correctly
Frequently asked
How is this different from simply using ChatGPT?
A chat window answers a question and forgets. What we build carries a task through: it holds the context of your business, follows a defined division of labour, and produces an output that a person approves before it leaves the company. The value is not the model, it is the process built around it.
Will the system invent information?
That is the central risk, and it is designed against rather than hoped away. The systems we build answer from named sources, and when a source does not contain the answer they say so instead of filling the gap. Checks that catch fabrication are part of the build, not an afterthought.
Does our company data leave our environment?
What the system may reach, and where it runs, are decided before anything is built and written into the scope. Deployment inside your own infrastructure is a supported option. Access boundaries are documented and reviewable rather than implicit.
Can it send email or take action on its own?
Only where you decide it should. Our default is that anything leaving the company, an email, a message, a published page, passes a human approval gate. Internal, reversible work can run unattended; outward-facing action does not.
Do you use this yourselves?
Yes. Our own operation runs on a multi-agent system we call Cordyceps: it prepares reports, monitors our infrastructure, drafts correspondence, and keeps our records. We are the first users of what we build.
All engagements are delivered under ISO/IEC 27001-aligned controls and KVKK / GDPR-aware data handling, with audit trails maintained throughout the engagement lifecycle.
Discuss your project with our team
Submit a brief and the relevant member of our team will get back to you as soon as possible.