the token
Engagements Target Operating Model

The way your business actually runs — redesigned agent-native.

Most operating models were designed before agents existed. They allocate work to people, route decisions through meetings, and treat coordination as overhead. We redesign them with agents as the substrate — humans where judgement is non-delegable, agents everywhere repetition costs more than judgement adds. The result is a working operating model your executive team and your agents can both consume.

§ 02 · An example operating model 02 / 06
Example target operating model · Institutional financial services

An example operating model, redesigned around agents.

An illustrative operating model — an institutional bank, eighteen functions, three levels of AI involvement. The methodology applies to any industry.

Eighteen operating functions scattered across a wide canvas. Front-office functions (Sales, Trading, Client Services, Wealth Management, Investment Advisory) sit loosely upper-left. Middle-office functions (Risk Management, Compliance, Treasury, Operations, Settlement, Collateral) cluster centrally. Back-office functions (Finance, Regulatory Reporting, Audit, HR) sit lower-right and along the right edge. Cross-cutting platform functions (IT, Market Data, Data) anchor at strategic positions, with Data at the centre as the substrate every agent reads from. Undirected hairline edges connect functions that share day-to-day working relationships. AI participates at three levels: plain nodes are human-led; nodes with a hollow violet ring are AI-assisted; nodes with a solid violet pip are agentic. Sales Inv. Advisory Trading Client Services Wealth Mgmt Risk Mgmt Compliance Treasury Collateral Operations Settlement Finance Reg. Reporting Audit HR IT Market Data Data
Human-led
AI-assisted
Agentic
Signal
Zone · 01 Front office
Zone · 02 Middle office
Zone · 03 Back office
Zone · 04 Foundations & Platform
Hover a function to inspect

Eighteen functions; three states of AI participation. Hover any node to see how AI participates today — human-led, AI-assisted, or agentic.

§ 03 · How we work 03 / 06

Four phases. Bespoke from the first day.

Phase · 01
Audit

We sit with your business as it is. Functions, channels, brands, geographies, decision rights, handoffs, exceptions. No template. No copy-paste deck. Two weeks for most mid-cap shapes.

Phase · 02
Target Operating Model

We draw the agent-native version. Which functions get agented, which augmented, which left to humans. Where the decision rights move. Where the human-in-the-loop checkpoints sit. The map is the deliverable; everything downstream is sequenced from it.

Phase · 03
Agentic Redesign

For the agented functions, we specify the agents themselves. Roles, prompts, guardrails, tools, escalation paths. We build the orchestration layer that wires them together.

Phase · 04
Phased Rollout

Function by function, with the executive team in the room and the audit trail running from day one.

§ 04 · Functions, not guesswork 04 / 06

Functions, not guesswork.

We treat deterministically what should be treated deterministically. We use AI agents as functions — each one with a precise role, a precise input, and an expected output — placed in the architecture where they actually add value. Where the work calls for fit-for-purpose systems (microservices, integrations, data pipelines), we design and build them. Where AI agents are the right tool, we use them. We do not throw tasks at AI and hope.

§ 05 · Bespoke by default 05 / 06

No template. No playbook. No recycled deliverable.

Every business is its own shape. The agents and workflows we build for you are built for you. What travels with us is a standard of rigour — the same one carried over from designing and operating institutional-scale systems in heavily regulated environments. The methodology is domain-agnostic; the engagement is one-of-one.

§ 06 · Get in touch 06 / 06

Designed around agents. Delivered for your business.