Services Overview
How Truzen supports clients end-to-end: assessment → scale → governance
Your services should not feel like standalone offerings. Truzen’s portfolio is designed to help organizations progress from baseline assessment and portfolio clarity to scaled delivery with governance, evidence, and risk assurance.
What clients engage Truzen for
Clear starting points — and clear outcomes
Most engagements start with one of the following “entry” options, then expand into a phased program as needed. This makes it easy to begin, while keeping an end-to-end path to enterprise-scale AI.
Starter engagement
AI Governance & Maturity Review
Establish baseline maturity, decision rights, key control gaps, and a prioritized action plan aligned to scale.
Starter engagement
AI Portfolio & Roadmap Program
Prioritize use cases, define value measures, and sequence initiatives into a practical roadmap with dependencies.
Starter engagement
Responsible AI Operating Model
Define how strategy, delivery, governance, and risk functions collaborate in practice (RACI, forums, checkpoints).
How Truzen works
Services organized by transformation phases
Each phase is outcome-led and designed to support enterprise-scale AI: clarity first, then prioritization, then operationalization, then assurance and continuous improvement.
Phase 1
Assess & Diagnose
Outcome: a clear baseline across portfolio visibility, governance maturity, data readiness, and risk posture.
AI Governance & Responsible AI
Baseline decision rights, lifecycle controls, and accountability.
Explore →Phase 2
Design & Prioritize
Outcome: a sequenced portfolio and roadmap tied to value, feasibility, dependencies, and governance requirements.
Phase 3
Embed & Enable
Outcome: governance and delivery practices embedded into daily execution (controls, roles, documentation, training).
Phase 4
Assure & Evolve
Outcome: ongoing monitoring, evidence of control, and improvement cycles aligned to internal and external expectations.
Engagement paths
Common ways clients work with Truzen
Path A: Start with Assessment
Governance & maturity review → roadmap → operating model → assurance.
Path B: Start with Roadmap
Portfolio prioritization → program roadmap → embed governance and risk checkpoints.
Path C: Start with Governance
Responsible AI operating model → lifecycle controls → assurance & monitoring.
Not sure where to begin?
Start with a discovery conversation. We’ll recommend the shortest path to a governed AI roadmap—based on your maturity, risk exposure, and near-term value priorities.