01
Autonomous systems
Multi-step agents that plan, call tools and hand off to people at the right moment — designed around real operating constraints rather than demo flows.
Swiss AI consultancy
Agents that act.
And transact.
We engineer trustworthy autonomous AI systems — and, where agents need economic agency, cryptographic authority and programmable financial infrastructure around them.
Strategy to production
Systems, not demos
Autonomy with accountability
01 / Expertise
From idea to reliable system.
Agentic AI is easy to demonstrate and hard to depend on. We close that gap with engineering discipline: clear scope, measurable behaviour, and limits that hold when the agent meets real users and real money.
02
Trustworthy AI infrastructure
Architecture, evaluation, observability, security and governance around probabilistic models — so autonomous software stays measurable, bounded and operable in production.
03
Agentic finance
Cryptographic authority, programmable accounts, smart contracts and settlement infrastructure for cases where autonomous software needs to commit resources or move value.
02 / The agent economy
When agents can spend, they become economic actors.
Our specialism: autonomous systems that can participate in economic workflows without being given uncontrolled financial authority.
Economic agency begins when software can commit resources — buy data, pay for compute, reserve capacity or settle with another service — inside limits you set and can prove.
Most financial infrastructure was designed around human-operated accounts and organisations. Delegating narrow, programmable authority to autonomous software is therefore awkward. Onchain systems can make that authority explicit in code and provide fast, machine-readable settlement and auditability. We use blockchain where it materially improves the trust model — not as a separate product line or a default answer to every problem.
An accountable actor
An agent can have a distinct account and cryptographic identity while signing keys remain isolated behind policy-controlled infrastructure. Actions stay attributable without exposing custody to the model.
Budgets, not good intentions
Limits, allowlists and approval thresholds belong in deterministic software or contracts rather than prompts. An agent cannot exercise authority it was never granted.
Machine-readable value movement
When onchain rails fit the trust model, approved intent can become fast, programmable settlement with evidence that software can observe and reconcile directly.
03 / Approach
Clarity before complexity.
Frame
Define the decision, workflow or constraint that matters — and exactly what the agent is allowed to do — before choosing a model.
Prove
Build a narrow prototype and test it against evidence: evaluations, failure modes and real cost. Not a polished demo.
Engineer
Turn what works into a secure, observable system with enforced limits that your team can operate, audit and extend.
04 / About
A small team for consequential work.
BelaZayka is an independent AI consultancy based in the Zürich region.
We combine deep software engineering, AI architecture, applied cryptography and business judgement. That range lets us move between board-level questions and implementation detail without losing sight of either.
We have built and operated systems in environments where correctness, security and audit trails are not negotiable. It shows in how we work: narrow scope, explicit assumptions, evidence before scale.
We work with teams that value clear thinking, technical depth and systems built to last.
SwitzerlandWorking internationallyAdvisory to build
05 / Open source
We publish how we build.
CognoKratos is BelaZayka’s open-source, community-built engineering curriculum for trustworthy autonomous systems. Its laboratories make our assumptions, boundaries and trade-offs inspectable instead of asking you to take expertise on faith.
Published online
The CognoKratos Book — Engineering Agentic Systems
The structured synthesis of the current CognoKratos curriculum: production agents, durable runtimes, governed decisions, cryptographic capability and financial workflows in which AI capability is deliberately separated from human authority.
Its lessons are grounded in code you can run at pinned revisions, and every project states plainly what it does not do.
The same principles shape our client work. The model is treated as a probabilistic component; identity, permissions, policies and approvals are enforced in software around it. Trust boundaries are explicit, and limits are tested rather than assumed.
The projects are reference architectures for learning, not audited or certified products. When your team needs these patterns applied to its own systems, data, controls and risks, that is the work we do.
Claims you can inspect.
Real diagrams, runnable repositories and explicit authority boundaries make the engineering visible. These are not decorative case-study graphics; they come directly from the systems.
PRODUCTION AGENT / TRUST BOUNDARIES
Deterministic controls around a probabilistic model
Identity, gateway, agent runtime, tool boundary, durable state and evaluation are separated so the model never silently becomes the source of authority.
Inspect the repository
CRYPTOGRAPHIC CAPABILITY / CUSTODY
Capability without exposing the secret
Arktos isolates wallet material behind a narrow service boundary. The agent can request useful operations without receiving seed phrases or private keys.
Inspect the repository
FINANCIAL WORKFLOW / AUTHORITY
AI capability is not financial authority
Tauros separates proposal from approval and execution so an agent may do operational work without acquiring the authority reserved for a human actor.
Inspect the repository06 / Contact
Have a difficult AI problem?
Whether it is an agent that has to act in the real world, or a system that has to be trusted with money, we are glad to look at it with you.
Email info@zayka.dev
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