Your AI problem may not be an AI problem.

01 / When to call us

Call Foundation when the AI pilot works in the demo and breaks in the business.

• Everyone has a different definition of the KPI.
• Important operating knowledge lives in people's heads.
• Agents can access data but cannot understand company context.
• Governance exists as policy documents, not enforceable operating rules.
• Your AI roadmap is a collection of pilots without a shared control layer.

02 / The three engagements

Three engagements. Each ends with something you can operate.

1. 01

   Foundation Diagnostic

   Question: What is actually preventing trusted AI from scaling here?

   Deliver

   • Current-state assessment
   • Prioritized constraints
   • Target architecture and operating posture
   • Ranked 90-day roadmap
   • Owners
   • Investment sequence

   Best for: Uncertainty.

   Start with a Diagnostic →

2. 02

   Foundation Build

   Question: Can we stand up the missing governed layer?

   Deliver

   • Business knowledge structure
   • Certified KPI and metric registry
   • Ontology, entities, relationships
   • Source authority
   • Fiscal and operating logic
   • Decision registry
   • Agent policies
   • Governance workflow
   • COE and ownership model
   • Selected integrations

   Best for: A known gap and missing infrastructure.

   Scope a Build →

3. 03

   Foundation Operationalize

   Question: How does this become part of how the business operates?

   Deliver

   • Production rollout
   • Certification cadence
   • Control processes
   • Monitoring
   • Adoption
   • Operating governance
   • Connection to Gravity and Agentic BI where appropriate

   Best for: Moving from build to sustained operation.

   Talk about operationalization →

03 / What you own when we leave

The engagement should leave your company stronger without us.

Business context layer

Company-owned.

Metric registry

Named owners and certified definitions.

Decision and policy registry

Versioned and auditable.

Reference architecture

Vendor-neutral where possible.

Operating model

Named roles, cadence, controls.

90-day execution plan and implementation evidence

Prioritized and measurable.

We are not selling dependency. We are building the layer your company needs to operate.

04 / Where products fit

Foundation does not replace the products. It gets the enterprise ready to use them.

1. Foundation

   Governed context · definitions · data · policy · operating model

   ↓

2. Gravity

   Verified answer infrastructure

   ↓

3. Agentic BI

   Decision-consumption layer

Discovery and Friction connect where relevant.

05 / Operator experience

Built from the problems we had to own inside the enterprise.

5

Major enterprises

Carter's · NCR · Citrix · TracFone · Verizon

$250M

Profitability impact

attributed to AI-powered commercial analytics

$7B

Business scale

analytics and FP&A supporting growth from about $1.5B to $7B in revenue

2×

Delivery throughput

from an operating-model redesign

• 80% reporting-estate reduction
• 200 to 300 analysts enabled
• Enterprise applications, planning, and governance ownership

The people scoping the engagement have lived with the consequences of enterprise architecture and operating-model decisions.

06 / De-risk the engagement

You do not need to commit to the transformation to diagnose it.

Start with a Foundation Diagnostic. Every Diagnostic defines:

• ·Scope
• ·Interviews and inputs
• ·Deliverables
• ·Duration
• ·A fixed or bounded commercial structure where possible
• ·A decision gate at completion

Build only if the evidence says the gap is worth fixing.

07 / Trust and architecture

Ownership stays with you.

• What we build is yours: the context layer, the registry, the operating model.
• Reference architecture is vendor-neutral where possible.
• Everything we build stays reusable if Modern AI is no longer involved.