What advisory services does Foundeon offer?

Four core services: the AI Readiness, Ownership, and Control Gap Assessment; DSIL™ Foundation Advisory; an AI-Ready Foundations and Runtime Governance Pilot; and an Enterprise AI Capability Advisory Retainer.

Who does Foundeon advise?

Boards and executive committees, CEOs and COOs, CAIOs and Heads of AI, CDOs, CIOs, and CTOs, and CROs and General Counsel on enterprise AI transformation, sovereignty, governance, and ownership decisions.

How do Foundeon engagements typically begin?

Foundeon engagements usually begin with the Enterprise Identity Readiness Assessment (EIRA), then evolve into DSIL™ Foundation Advisory, domain foundation design, an operating model engagement, runtime governance work, or an executive advisory retainer.

Advisory

Sovereignty-Preserving AI Transformation

Foundeon helps enterprise leaders scale AI capability while preserving ownership of the operating logic AI depends on: business meaning, decision context, governance expectations, accountability, and institutional memory.

Engagements are led personally by Anna Jibgashvili, bringing 15+ years of enterprise data, AI foundation, governance, and transformation experience across regulated institutions.

Start with EIRA Discuss Your AI Transformation Path

EIRA is the Enterprise Identity Readiness Assessment: Foundeon's diagnostic for understanding whether the enterprise has made its institutional logic, ownership, governance, and decision boundaries explicit enough for AI scale.

Transformation Path

The three paths to AI scale

As AI scales inside the enterprise, organizations tend to move toward one of three structural paths: vendor-mediated, fragmented, or sovereign. The path is shaped by who owns business meaning, decision logic, governance expectations, evidence, and accountability as AI becomes embedded in work.

Vendor-mediated

Capability shaped through external platforms.

AI capability arrives quickly through platforms, vendors, and models. The enterprise consumes intelligence that external systems help structure, interpret, and operationalize.

What it looks like

Critical workflows depend on vendor-defined logic
Business meaning is encoded inside external platforms
Governance applies after outputs are produced
Switching costs increase as capability expands

Where it leads

The enterprise becomes increasingly dependent on external systems to describe, execute, and evolve its own operating logic.

Condition

Reclaim enterprise meaning before vendor-shaped logic becomes the operating default.

Fragmented

Local progress without enterprise coherence.

AI activity expands across teams and functions, each using its own meanings, tools, models, and governance practices. Speed increases while shared context remains unresolved.

What it looks like

The same customer, product, or process is defined differently across systems
Pilots succeed locally without integrating enterprise-wide
Governance is reinvented by each team or function
Decisions become defensible locally and difficult to reproduce across the enterprise

Where it leads

AI activity grows faster than the enterprise can reconcile what AI is doing, deciding, or learning on its behalf.

Condition

Anchor shared meaning before fragmented progress becomes the operating model.

Sovereign

Enterprise-owned operating logic.

The enterprise defines what it means, decides, governs, and owns. AI operates inside that defined context. Tools accelerate. Enterprise meaning remains governed internally.

What it looks like

Enterprise-owned identity substrate
Trusted foundations governed by contracts and passports
Runtime governance at the moment of decision
Agents governed by defined scope, boundaries, escalation, and accountability

Where it leads

AI accelerates the enterprise without replacing its institutional logic. Vendors change. Models evolve. The enterprise’s meaning, decisions, and accountability remain its own.

Condition

Define enterprise identity before scaling intelligence.

Engagement Path

How Foundeon engagements typically evolve

Foundeon engagements usually begin with the Enterprise Identity Readiness Assessment (EIRA). From there, the advisory path evolves iteratively as ownership gaps, domain priorities, decision contexts, governance needs, and Foundational Data Products™ candidates become clearer. The sequence below shows a typical progression, while engagement models may be used independently or in combination depending on scope.

Five stages from baseline diagnostic to ongoing coherence. Each stage produces named outputs, while the full path evolves as domains, facets, governance needs, and implementation dependencies are discovered.

Baseline — Enterprise Identity Readiness Assessment (EIRA)

Duration2–4 weeks

Apply EIRA to understand readiness, articulation gaps, ownership clarity, governance maturity, and decision-boundary strength.

Example Outputs

EIRA score and readout · Articulation gap view · Priority risks · Recommended path forward

Path Clarity

Duration2–4 weeks

Determine whether the enterprise is moving toward vendor-mediated, fragmented, or sovereign AI capability.

Example Outputs

AI Sovereignty Path readout · Path indicators · Ownership risk view · Leadership implications

Foundation Definition

Duration4–10 weeks

Define what the enterprise must own across priority domains: identity, terminology, decision context, governance expectations, accountability, dependencies, and candidate Foundational Data Products™. As new facets are identified, the foundation becomes more complete and more AI-readable.

Example Outputs

DSIL™ baseline · Domain identity brief · Ownership map · Decision-context map · Foundational Data Products™ hierarchy · Candidate FDP areas · Prioritization view

Timing Note

Initial work typically focuses on one priority domain. The work expands iteratively by domain, subdomain, facet, and decision context.

Capability Build Enablement

Duration8–12+ weeks

Define the repeatable delivery model, certification logic, semantic contracts, governance scaffolds, runtime controls, and AI activation model.

Example Outputs

Foundational Data Products™ operating model · Semantic contract structure · Certification criteria · DPOE intake · Runtime governance design · ARD · Contracts/passports · Implementation roadmap · Governance activation plan

Timing Note

This reflects advisory design, structure, and enablement. Full buildout varies based on the enterprise's technology stack, data environment, internal teams, vendors, tooling, and execution capacity.

Ongoing Coherence

Duration3–12 months

Support executive decisions as AI capability expands across domains, vendors, governance forums, and operating cycles. This stage helps the enterprise continue refining meaning, ownership, governance, and operating capability as new domains, data products, use cases, and agents emerge.

Example Outputs

Advisory memos · Artifact review · Roadmap refinement · Governance support · ATM measurement · Steering preparation · Domain sequencing · Path correction

Timelines reflect advisory design, definition, and enablement work. Enterprise implementation timelines vary based on scope, tooling, resourcing, technical dependencies, internal delivery capacity, and the number of domains and facets brought into scope.

Engagement Models

Ways to work with Foundeon

Foundeon engagements can begin with a diagnostic, a foundation advisory track, a domain design effort, an operating model engagement, runtime governance work, or an executive advisory retainer. The timeline above shows how the work can evolve. The models below describe the main ways Foundeon can be engaged depending on the enterprise's starting point, priorities, and internal capacity.

Model Type · Diagnostic advisory

EIRA Advisory Engagement

Best for

Leadership teams seeking an evidence-based view of whether institutional logic, decision boundaries, ownership clarity, and governance maturity are explicit enough for AI scale.

Typical outputs

EIRA readout, six-dimension gap analysis, priority risks, recommended advisory path, executive readout.

Model Type · Foundation architecture

DSIL™ Foundation Advisory

Best for

Enterprises defining the Digital Substrate Identity Layer that organizes business meaning, decision logic, governance expectations, accountability, and institutional memory.

Typical outputs

DSIL™ baseline, ownership primitives, governance expectations, decision-context map, foundation roadmap.

Model Type · Domain design

Domain Foundation Design

Best for

Functions or domains preparing AI-ready foundations within a priority area of the enterprise.

Typical outputs

Domain identity brief, domain context map, ownership model, dependency map, candidate Foundational Data Products™ areas, prioritized build sequence.

Model Type · Operating model

Foundational Data Products™ Operating Model

Best for

Enterprises operationalizing Foundational Data Products™ as the trusted foundation AI capability runs on.

Typical outputs

Product definition standards, certification model, lifecycle governance, DPOE intake model, ownership and accountability structure, contract/passport model.

Model Type · Runtime governance

AI Activation and Runtime Governance

Best for

Enterprises moving AI from pilots into governed runtime use across workflows, decisions, agents, and operating processes.

Typical outputs

Runtime governance scaffold, evidence and auditability requirements, decision-node map, ARD, agent contract/passport model, rollout plan.

Model Type · Ongoing executive advisory

Executive Advisory Retainer

Best for

Boards, CEOs, and senior executives requiring sustained advisory on AI strategy, ownership, governance, and operating model decisions.

Typical outputs

Executive counsel, decision support, artifact review, board and leadership briefings, roadmap refinement, periodic strategic reviews.

Engagements may be used independently or combined into a broader advisory path as the enterprise moves from readiness, to foundation definition, to governed AI capability.

Scope of Engagement

What Foundeon helps define

Foundeon helps leadership define the enterprise-owned structures required for AI capability to scale with governance, auditability, and institutional control.

Engagements focus on

Enterprise identity architecture
Trusted foundation design
Ownership and accountability decisions
Governance scaffolds and runtime controls
Certification standards and lifecycle models
Capability rollout strategy

Out of Scope

Vendor selection as the primary engagement, platform resale, day-to-day data engineering execution, cloud infrastructure implementation, standalone model benchmarking, standalone prompt engineering training, and replacement of internal technology, data, risk, legal, security, or engineering leadership.

Working with Anna

Senior advisory, personally led

Engagements are led personally by Anna Jibgashvili. The work is designed for leadership teams that need clear judgment, structured decision support, and practical artifacts they can use to align ownership, governance, foundations, and AI operating capability.

Anna brings 15+ years of enterprise data, AI foundation, governance, and transformation experience across regulated institutions. Her role is to help leaders clarify what must be owned, where foundations need to be strengthened, how governance should operate, and what should be sequenced next.

This is advisory work for enterprise decision-making, foundation design, and governed capability development.

Frequently asked questions

What advisory services does Foundeon offer?: Four core services: the AI Readiness, Ownership, and Control Gap Assessment; DSIL™ Foundation Advisory; an AI-Ready Foundations and Runtime Governance Pilot; and an Enterprise AI Capability Advisory Retainer.
Who does Foundeon advise?: Boards and executive committees, CEOs and COOs, CAIOs and Heads of AI, CDOs, CIOs, and CTOs, and CROs and General Counsel on enterprise AI transformation, sovereignty, governance, and ownership decisions.
How do Foundeon engagements typically begin?: Foundeon engagements usually begin with the Enterprise Identity Readiness Assessment (EIRA), then evolve into DSIL™ Foundation Advisory, domain foundation design, an operating model engagement, runtime governance work, or an executive advisory retainer.

Leadership Audience

Who Foundeon advises

Foundeon works with enterprise leadership teams facing AI transformation decisions where scale, governance, auditability, and enterprise-owned capability converge.

Boards and executive committees

Confronting enterprise AI strategy, sovereignty, risk, and accountability decisions.

CEOs and COOs

Scaling AI capability across functions while preserving operating coherence and enterprise ownership.

CAIOs and Heads of AI

Translating AI mandate into governed operating capability, adoption paths, and measurable transformation.

CDOs, CIOs, and CTOs

Designing AI-ready foundations, trusted data structures, interoperability, and enterprise-owned architecture.

CROs and General Counsel

Embedding governance, evidence, escalation, and auditability where AI participates in decisions.

Discuss Your AI Transformation Path Explore the Method

Also on Foundeon: Diagnostics