Agentic
Architectures
Translate the target AI journey into a concrete multi-agent system with defined roles, tools, and orchestration logic.
Each touchpoint in your target AI journey requires specific agents with defined capabilities. We translate the journey into an agentic architecture where every agent has an explicit mandate, a set of tools it can use, and clear orchestration logic that governs how agents work together.
We also design for what happens when things go wrong. Failure modes, escalation paths, and human-in-the-loop intervention points are built into the architecture from the start, so your system operates reliably under real-world conditions, not just in demos.
The journey tells you what to build. The architecture tells you how.
Six dimensions of a reliable agentic system.
An agentic architecture is more than a collection of agents. It is a system with orchestration logic, failure handling, and human oversight designed in from the start.
01
Journey-to-architecture translation
We take each touchpoint from the target AI journey and translate it into architectural components. The journey defines what the user experiences; the architecture defines how agents, tools, and orchestration logic deliver that experience. This ensures a direct line from design intent to technical implementation.
02
Agent specification
Each agent in the system gets a clearly defined role: intent recognition, information retrieval, action execution, or escalation handling. We specify what each agent does, what it must not do, what tools it has access to, and how it communicates with other agents in the system.
03
Orchestration flow design
We design the orchestration logic that governs how agents work together: sequential pipelines for deterministic workflows, parallel execution for independent subtasks, or hierarchical orchestration where a supervisor agent coordinates specialists. Every flow is documented and testable.
04
Tool & integration mapping
Agents only become useful when they can act in the world. We map every tool, API, and data source each agent requires, design the integration contracts, and build in the access controls that prevent agents from doing more than intended.
05
Failure mode analysis
We systematically identify where the multi-agent system can break: cascading errors, conflicting outputs, stuck loops, tool failures, and adversarial inputs. For each failure mode, we define detection mechanisms and recovery strategies before deployment.
06
Human-in-the-loop design
Agentic systems need explicit points where humans review, approve, or redirect. We design the intervention architecture: which decisions require human sign-off, how overrides are handled, and how the system resumes safely after human input. This is especially critical in early implementation phases.
The architecture
How the journey translates into an agentic system.
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What this work produces.
Journey-to-architecture mapping
A structured translation of every touchpoint in your target AI journey into specific agents, orchestration flows, and tool requirements.
Agent specification document
Roles, tools, boundaries, and escalation rules for every agent in the system. Clear enough for engineering to implement directly.
Orchestration flow diagrams
Documented flow logic for all core workflows: sequential, parallel, and hierarchical patterns with decision points and state management.
Tool & integration map
Complete specification of every API, data source, and external system each agent requires, with access control definitions.
Failure mode analysis
Systematic identification of where the system can break, with detection mechanisms and recovery strategies for each failure mode.
Implementation specification
Engineering-ready architecture document covering the full system. Ready for your team to build from without ambiguity.