MAXIM BREGER / ADVISORY
Five service lines
for high-stakes AI decisions.
I work with enterprise leaders, investors and founders at the point where business assumptions become technical commitments. Each engagement produces a decision you can defend, with clear ownership and verifiable evidence.
1 · AI-Native Transformation
The problem: ad-hoc AI experiments that never become a governed, outcome-driven capability. For: leaders who own an AI mandate and need a credible operating model.
Typical deliverables
- Current-state assessment of AI activity, data and readiness.
- Target operating model with roles, decision rights and governance.
- A phased, outcome-driven roadmap.
- A prioritized risk register.
Discuss an AI-Native Transformation assessment →
2 · Delivery Governance
The problem: AI and software delivery that cannot be predicted, evidenced or accepted with confidence. For: organizations with active delivery and acceptance risk.
Typical deliverables
- A contract, evidence and acceptance framework.
- An independent verification model.
- Quality gates and definition of accepted work.
The AI Factory is the evolving implementation of this governed-execution approach.
Discuss a Delivery Governance assessment →
3 · Enterprise AI Architecture
The problem: AI systems that need architecture, integration and risk, security and governance review before commitment. For: CTO, CIO and CISO.
Typical deliverables
- An architecture blueprint with data flows, integrations and system boundaries.
- A risk and security review.
- A build-versus-buy decision with assumptions.
Discuss an Enterprise AI Architecture review →
4 · Venture Technology Advisory
The problem: funds and founders who need an independent read on technology, architecture and risk. For: VC and investors, and portfolio founders.
Typical deliverables
- A technical due-diligence report.
- An architecture and risk opinion.
- A bounded recommendation with next steps.
Discuss a Venture Technology due-diligence →
5 · AI Operations & Economics
The problem: AI systems whose cost, measurement and operating economics are unclear. For: operators scaling AI in production.
Typical deliverables
- An economics baseline, including cost per accepted result.
- A measurement and telemetry plan.
- Operating recommendations.
Discuss an AI Operations & Economics baseline →
How an engagement works
Start with an introductory conversation. From there, a paid Discovery or Assessment produces a technical recommendation. Any long-term advisory or implementation is a separate, agreed engagement. Scope, access and dependencies set the schedule; there is no universal delivery promise and no guaranteed outcome. Scope and pricing on request.