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Enterprise AI Operationalization
Move AI out of pilots, into the parts of the business that change the P&L.
Pilots succeed easily. Production rollouts stall. We rebuild the operating model around named senior experts orchestrating AI agents on our proprietary harnesses, in twelve-week outcome-staked cycles. From scattered experiments to operating capability.
No obligation. We pick up.
The pattern
Pilot succeeds. Production never lands.
You have models that work. A vendor demo went well. A pilot shipped. Then the rollout calendar starts slipping. The team that built the pilot got reassigned. The integrators want a new discovery phase. The model accuracy stops mattering because no workflow consumes its output. The operating model around the AI was never built to scale.
Operationalization is the missing piece. It is not more pilots, and it is not a larger SI engagement. It is rebuilding the small number of workflows where AI directly moves the P&L, with senior operators owning judgment and AI agents owning the volume. Each cycle ships a verified outcome and seeds the next one.
How we do it
Twelve weeks. Production-grade.
Verified value.
One cycle is enough to ship a verified outcome. Multi-cycle programs compound: each cycle expands the production surface of AI inside your business while the baseline tracks the P&L impact.
Week 0 to 2
Mobilize against your P&L
We name the pod in the SOW, ingest your context onto our harness, and lock an Approved Value Baseline with your ROI-approving stakeholders. The exec closest to the program's P&L signs off in writing.
Week 2 to 9
Build and deploy on production
Senior operators design and validate; AI agents do the volume work (data, mapping, drafting, instrumentation, QA). Everything ships against the Week 2 baseline, into the production workflows, not a staging fiction.
Week 10 to 12
Verify value, then compound
Your stakeholders sign off on Value Created. The agents, harness, and operating model stay with you. Cycle 2 activates against a Modular Rate Card with no second procurement cycle.
In operation
From scattered pilots to one operating fabric.
Where we engage
Five shapes inside this domain.
Most programs combine two or three of the shapes below into a single twelve-week cycle. We size the cycle to the value baseline, not to the number of shapes.
AI Center-of-Excellence redesign
Stand up or rewire the internal CoE so it ships agentic capability into the business instead of running a pilot factory. Governance, model catalog, evaluation pipelines, agent harness.
Agentic execution on existing workflows
Deploy AI agents into specific workflows (order-to-cash, demand sensing, exception management, contract intelligence) that close the loop on outcomes the operator already owns.
Decision-assist deployments
Production-grade decision-assist agents alongside named operators. The agents surface options, evidence, and trade-offs; the operator decides. Audit trail, accuracy budget, escalation rules.
Model governance and observability
Production observability for foundation-model traffic, with cost, latency, accuracy, and drift instrumented per workflow. CFO and security teams see the same dashboard.
Pilot-to-production rescue
Take a pilot that stalled in handoff and finish the production rollout in two cycles. Often the fastest path to a verified outcome for a buyer who is already invested.
Proof
Verified at Fortune 100 scale.
Trusted by teams at...
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How we unlocked a 3x+ return challenge in 12 weeks for Philips on an AI program that had stalled at the pilot stage.
Working capital and freight outcomes shipped inside Cycle 1, signed off by Philips Finance against an Approved Value Baseline locked in Week 2. The agents and operating model stayed with Philips. Cycle 2 expanded the production surface.
Commitments
Four contractual commitments,
live in every cycle.
The full set of seven sits on the Services page. These four show up the most often in AI Operationalization engagements.
- 01
ROI or We Pay
A portion of every cycle's fee is staked on validated outcomes against the Approved Value Baseline.
- 02
Transparent Resource Plan
Named senior experts on the SOW. Substitutions need client sign-off. No labor pyramid.
- 03
Free Until Value Pilot
Thirty-day proof-of-value pilot. Client pays only at production-grade outcome.
- 04
Vendor-Agnostic Architecture
Open standards, multi-cloud, model-agnostic harness. Tooling follows the design, not a sales quota.
Related domains
Programs usually span more than one.
Clients hire us on one problem domain and discover they have the other four. The mechanism is the same across all five: twelve-week cycles, named senior experts, AI agents on production workflows.
Supply Chain and Fulfillment Transformation
Allocation logic, freight discipline, demand sensing, SKU rationalization, fulfillment digital twins.
See the domain →
Agentic Execution of Enterprise Workflows
Order-to-cash, procure-to-pay, S&OP, contracts and quote-to-cash, decision-assist agents.
See the domain →
Operational Resilience and Working Capital
Margin and freight protection, inventory and SLOB reduction, working capital release, exception management.
See the domain →
Customer Experience and Service Operations
Agentic resolution, exception management, and service operations that lift CSAT while compressing cost-to-serve.
See the domain →
Direct line
Cycle 1 in your operation.
Twenty-five minute call. Cycle 1 sketch tied to a real workflow in your business. Baseline mechanics, named operators, agent harness. No slides, no obligation.
No obligation. We pick up.
Frequently asked