Build a company
driven by systems.
Led by people.
Make AI part of how your company operates. We connect your strategy, people, processes and data in an AI Operating Model, then build the workflows and agents that put it to work.
Designed by consultants with business transformation experience at Nike, Heineken, Kraft Heinz, Randstad and Philips.
Experience of the consultants. These companies are not presented as ARQ clients.Start with the business.
Connect the whole system.
An AI Operating Model defines what the business needs to achieve, how work flows and who owns each decision. The technology follows those choices. Our six-part framework brings these principles together for the way your company works.
Choose the problems worth solving and the measures of success.
Roles, ownership and skills.
How work moves end to end.
Reliable business context.
Agents, tools and workflows.
Clear permissions, review points and accountability.
01Strategy & outcomes
Map the bottlenecks, costs and opportunities. Define the outcome, the baseline and the business owner before selecting a tool.
02People & adoption
Define where people lead, where AI assists and how the team learns to use the system. Build review habits and escalation routes into daily work.
03Processes & decisions
Map the journey from a trigger to a verified result. Remove unnecessary handoffs and define the decisions that require human review.
04Data & context
Identify source systems, agree definitions and establish access, freshness and quality checks. Keep evidence linked to its source.
05AI & technology
Combine integrations, deterministic rules, AI agents and workflow orchestration. Choose the approach that fits the task and its failure modes.
06Governance & improvement
Set permissions, approval boundaries and monitoring. Track exceptions and outcomes, review performance and improve the operating model over time.
Framework references: our synthesis of public guidance on AI operating models — McKinsey and roles and decision rights — Microsoft, adapted to each business.
From a signal
to a verified result.
A connected company needs a clear path from information to action. Here is an illustrative workflow for an order that has not shipped.
- 01 · DetectConnect the context.
Read the order, payment, fulfilment and support history.
- 02 · PrepareBuild a proposal.
Check the evidence and prepare the next action for the responsible person.
- 03 · DecideApply human judgment.
Review customer impact and approve, adjust or reject the proposal.
- 04 · VerifyClose the loop.
Execute within agreed permissions and check the result in the source system.
Each workflow has its own permissions and review requirements. A prepared proposal, an approval and a completed action are separate states.
The operating model
in practice.
Explore the systems behind our ecommerce operations, agency workflows and agent software.
AI Cockpit with 3 agents for a supplement brand
Orders, tickets and tracking in one store. The first run found 13 real problems, including one paid for and never shipped for eight weeks.
Read the case study →From lead to off-boarding: agency automation
Twelve automations covering the whole arc of a client, all reading from one warehouse. Four decisions stay human on purpose.
Read the case study →AI Operating System with agents for dropshipping
Every capability its own agent, an orchestrator routing the work, and a guardrail no approval can override. Rebuilt from a dashboard in one week.
Read the case study →Map the company.
Build one valuable workflow.
Map the people, systems and recurring decisions. Agree which problem is worth solving first.
Build with real business context, a named owner and clear review boundaries. Validate the result before expanding.
Train the team, monitor outcomes and extend the model to the next valuable workflow.