Not every organization is ready for AI at scale. These frameworks show who is—and who’s not.
Alignment gaps. Undefined milestones. No ownership. No audit trail. Likeable was built to remove those variables. Our frameworks are designed for enterprise leaders who don’t have time to repeat failed pilots.
These are not lightweight templates. They are delivery systems used to scope, govern, deploy, and manage complex AI initiatives with real financial and operational risk attached. If you’re investing six to seven figures in AI strategy, infrastructure, or LLM deployment, these frameworks are how we ensure that investment doesn’t turn into shelfware.
What it is:
A diagnostic that measures how prepared your organization is for responsible, high-scale AI deployment.
How it works:
Assesses five areas:
Outputs a score and a strategic roadmap.
Why it matters:
This is how you defend your AI roadmap to your board. It also tells you if you’re about to waste half your budget.
What it is:
A structured delivery model with defined gates, roles, and metrics for each phase of the engagement.
How it works:
Four phases:
Each stage includes formal deliverables and mapped responsibilities.
Why it matters:
When you're managing a seven-figure budget, you can't afford misalignment or ambiguity. This framework gives both sides a common language and trackable progress.
What it is:
An operational map that clarifies every role in the project—from technical execution to executive signoff.
How it works:
Why it matters:
If your CISO, Head of Data, and PMO don’t agree on ownership, the system will fail before it launches. This solves that before it becomes a problem.
What it is:
A comprehensive delivery methodology that moves strategy to execution across 8 enterprise-grade phases.
How it works:
Steps include:
Why it matters:
When your AI strategy is tied to real outcomes and real constraints, this is the path that makes it executable.
What it is:
A dual-path model that allows us to run a quick-win pilot while your broader strategy and governance roadmap is being finalized.
How it works:
Why it matters:
Boards don't wait. This shows early progress while protecting long-term architecture integrity.
What it is:
A real-time view into post-launch performance, compliance signals, and business ROI—presented in a format leadership can act on.
How it works:
We track:
Delivered via Power BI, Looker, or your internal analytics layer.
Why it matters:
If you can’t measure it, you can’t scale it. This dashboard keeps AI work tied to outcomes your CFO cares about.
These frameworks are not menu options. They work together.
If you’re looking to run experiments, we’re not the right partner. But if you're investing seven figures to bring AI to life in a way that survives audit, scales across business units, and ties to measurable value, this is how we do it.
We’ll walk you through how these frameworks apply to your environment. No generic slide decks. No product demo. Just clarity, structure, and executive-level readiness.