AI strategy
Use-case intake, operating model, and a CAIO-ready roadmap. Guild enters before the software decision is frozen.
Enterprise AI
AI as an operating capability. Built on IBM.
Strategy, ground, build, govern, authorize, operate, observe, intervene, optimize — with Guild AEGIS, ControlPlane, watsonx, and IBM Bob mapped under one lifecycle.
Guild AI lifecycle
Strategy → Ground → Build → Govern → Authorize → Operate → Observe → Intervene → Optimize.
The signature operating model. AEGIS, ControlPlane, observability, FinOps, integration, and IBM technology sit on this path — not as adjacent product pages.
01
Strategy
What should we build?
Use-case intake, operating model, and a CAIO-ready roadmap
watsonx portfolio fit, IBM Bob, Expert Labs scoping
02
Ground
What data and enterprise context can it use?
Estate inventory, lineage, and lakehouse design
watsonx.data, Knowledge Catalog, DataStage
03
Build
How is the model or agent constructed?
Model, prompt, and agent construction against real workloads
watsonx.ai, Orchestrate, IBM Bob
04
Govern
Who owns it and what policies apply?
ControlPlane — inventory, ownership, lineage, evidence, retirement
watsonx.governance, OpenPages
05
Authorize
What can it actually do?
Identity, entitlements, human approval, and a tested kill switch
AEGIS on watsonx Orchestrate, Verify
06
Operate
How does it behave in production?
Runtime on the IBM estate, not a lab exhibit
OpenShift, Cloud Paks, watsonx Orchestrate
07
Observe
What happened, and why?
Who acted, on what data, with which tool, under which policy
Instana, Concert
08
Intervene
How do we stop or constrain it?
Re-risk triggers, exception paths, and a kill switch that has been tested
OpenPages, watsonx.governance, AEGIS
09
Optimize
What value and cost is it producing?
Token economics, capacity, and measurable business value
Turbonomic, Apptio / Cloudability
How the capabilities fit together
9 stages. Ten capabilities. One firm accountable for the operating model — not a catalog of disconnected AI pages.
AI architecture
Data, models, agents, and controls as one design — not a chatbot project next to an unmanaged lakehouse.
AI governance
ControlPlane: inventory, ownership, lineage, policy, evidence, and retirement. watsonx.governance and OpenPages in the runtime.
Agentic AI
Guild AEGIS on watsonx Orchestrate. Identity, authorization, observability, human approval, and a kill switch.
AI observability
Who acted, on what data, with which tool, under which policy. Instana and Concert on the same estate.
AI FinOps / token economics
Usage, cost, ROI, and predictive budgeting across models and agents — mapped to Turbonomic and Apptio.
AI security
Identity, data classification, and runtime policy on the same path as the agent. Guardium and Verify where the rest of the estate already lives.
AI lifecycle management
Intake, promotion, recertification, and retirement. An agent that cannot be retired is not in production. It is abandoned.
watsonx & IBM Bob
watsonx.ai, watsonx.data, watsonx.governance, Orchestrate, and IBM Bob on the same estate when the work is code.
AI implementation
Production use cases in regulated industries. Guild delivers the platform and the first workloads that prove it.
Discuss an AI initiative
Strategy, governance architecture, or a first production workload — we will tell you which conversation it actually is.