ABOUT SYMMATHIC
Designing organisations where humans thrive through agent collaboration
Organisations face a choice in how they integrate AI. We exist to ensure that choice is made well: designing human-agent collaboration where both evolve together in context, grounded in 50+ years of systems science and 20+ years of consulting methodology.
Mission
To provide the decision infrastructure that lets complex organisations safely unlock agentic operations — from strategy through to implementation specifications.
Vision
A world where "Designed on Symmathic" is the signal that an organisation's agentic transformation was done right — with agent-augmented decisions that are safe, governed, and reversible.
Why "Symmathic"?
The name and the philosophy behind it
The name comes from symmathesy — Nora Bateson's term for how living systems learn together. A symmathesy isn't just a collection of parts; it's defined by mutual learning between those parts.
We think organisations work the same way. Not machines to be re-engineered, but living systems of people, decisions, and relationships that evolve through interaction.
This shapes our methodology: we design for continuous learning, not fixed states. Decision architecture that adapts, not optimisation that brittles.
If you're curious about the deeper roots, Nora Bateson's book Small Arcs of Larger Circles is a wonderful place to start.
We build on a tradition of systems thinking that has spent decades understanding how living systems actually work. Each thinker has shaped specific, concrete elements of how the platform works:
Gregory Bateson — relational epistemology, learning levels. How the platform models relationships and compounds learning.
Nora Bateson — symmathesy, Warm Data. The foundational design principle: mutual learning between humans and agents.
Donella Meadows — leverage points, system dynamics. How we prioritise interventions in decision network redesign.
Stafford Beer — Viable System Model, requisite variety. How we design organisational viability and flexibility.
Elinor Ostrom — polycentric governance, commons design. How we handle shared resources and competing interests.
Dave Snowden — Cynefin, contextual sense-making. How we match decision processes to the domain's nature.
OUR METHODOLOGY
Decision Topology
The methodology for the agentic era
Decision Topology reframes organisations not as static hierarchies or process flows, but as networks of decision nodes that can be dynamically adapted, automated, and reconfigured.
Every organisation is fundamentally a network of decisions. Every capability, process, and system exists to enable better decisions — faster, more accurate, more consistent.
The 7 design activities
- • Objective Design — Organisational objectives as decision outcomes
- • Value Model — Value creation as decision flows
- • Business Model — Business model as decision domains
- • Service Portfolio — Services as decision points
- • Operating Topology — Capability and resource decisions
- • Resource Portfolio — Dynamic resource allocation
- • Topology Reconfiguration — Continuous learning
Safe Agentic Operations
The winners in agentic operations won't have the flashiest demos — they'll make agent actions boring, predictable, bounded, and repairable.
Draft-First
All agent outputs go through review before commitment
Business Diff
Preview what will change before any action takes effect
Extended Reversibility
Expand time horizons for rollback capability
Systematic Repair
Build robust correction mechanisms enabling faster autonomous operation
Permanent Record
Every action leaves queryable history: intent, inputs, changes, tools, approvals
Door Classification
Distinguish two-way doors (reversible) from one-way doors (irreversible)
Let's discuss your transformation
We work with complex organisations that need decision infrastructure to make agentic operations safe.
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