Agent architecture
Design planners, specialised agents, tools, memory and orchestration around the work to be performed.
Core capability / 02
Agentic systems
Controlled AI agents that coordinate knowledge, tools and operational actions without surrendering institutional authority.
The proposition
Agentic systems become valuable when goals, permissions, tools, validation and human intervention are engineered as explicitly as the model itself.
01
Automated multi-step work with defined boundaries
02
Clear human approval and escalation points
03
Observable actions, evidence and decisions
What we engineer
A complete operational capability—not an isolated model.
Every engagement is shaped around the institution, its constraints and the outcomes the system must produce.
Tool and workflow integration
Connect agents safely to APIs, documents, enterprise applications and operational queues.
Control and validation
Introduce permissions, policy checks, confidence thresholds and human approval before consequential actions.
Agent observability
Trace plans, tool calls, evidence, cost, latency, failures and final outcomes.
System flow
How intelligence moves through the system.
This visual grammar is consistent across Praxnetics: context becomes intelligence, intelligence is governed, and action remains observable.
- STEP 01Goal
- STEP 02Plan
- STEP 03Retrieve context
- STEP 04Use authorised tools
- STEP 05Validate
- STEP 06Human approval
- STEP 07Action
Applications
Where this becomes operational.
01
Case-processing agents
02
Procurement and policy assistants
03
Research and analysis agents
04
Service orchestration
05
Operations coordination
06
Document-intensive workflows
Governance by design
Control is part of the architecture.
The system is designed so that trust can be demonstrated through evidence, permissions, evaluation and accountable intervention.
Role-based tool access
Action-level approval
Policy enforcement
Execution sandboxes
Complete activity logs
Fallback and recovery paths
Begin with the operational challenge