Outcome Before Implementation
Every engagement starts with defined business impact, not technical exploration.
AI Strategy & DeliveryMicrosoft Copilot
The AI Value Engine
A disciplined, three-stage path that aligns Microsoft AI to your data, processes, and governance, reducing risk and delivering measurable ROI.
Why It Matters
AI Doesn't Fail Because of Technology
Most AI projects don't fail outright, they lose momentum because goals, data, processes, and governance aren't clear. TrellisPoint turns AI into a disciplined, outcome-driven business capability, reducing risk before cost and credibility are at stake.
Data Readiness First
AI is only as reliable as the data behind it. We validate, structure, and align it before deployment.
Responsible Deployment
Governance, security, workflow integration, and stakeholder ownership embedded from day one.
AI Value Engine
Three Offers. One Proven Path.
The AI Value Engine is intentionally sequential. You can engage at any stage, but skipping steps increases risk, cost, and complexity. We'll be upfront about that. This is how organizations move from AI interest to real, sustained business value. Sound familiar? Talk to an AI Advisor.
Make AI Safe, Grounded, and Worth Deploying
A fixed-scope readiness engagement that determines whether Microsoft AI can actually deliver value in your environment.
- Validated data, security, and governance readiness
- Prioritized, high-value use cases
- A clear go / no-go recommendation
Deploy AI Into One Real Business Process, End to End
A fixed-fee implementation that embeds AI into a single, clearly defined business process to deliver measurable outcomes without sprawl.
- AI live in a real workflow
- Measurable business impact
- A repeatable pattern for future AI expansion
Operational Support for AI Over Time
Ongoing support to govern, optimize, and extend AI capabilities after deployment so they continue delivering business value without creating operational risk.
- Ongoing governance and performance oversight
- Continuous optimization of deployed AI solutions
- Support for scaling AI across additional use cases
By the Numbers
Proven ROI from Microsoft 365 Copilot
Measured across small and mid-sized organizations using Microsoft 365 Copilot, based on independent Forrester Total Economic Impact research.
353%
Up to Three-Year ROI
Forrester Total Economic Impact Study
$955K
Up to Net Present Value
Composite 200-Employee Organization
25%
Faster Onboarding
New Hire Ramp Acceleration
Download the AI Value Engine Guide
Complete the short form to receive the full guide outlining our structured approach to secure, scalable AI adoption.
Get Started
Ready to Get AI Right?
AI projects fail when they're misaligned with business goals, not because they're too ambitious. We help you pinpoint where AI can deliver measurable value, identify gaps and risks, and create a practical, outcome-focused roadmap that makes AI a lasting business capability.
- ✓ Clarify Where to Start
- ✓ Avoid Costly Missteps
- ✓ Build for Long-Term Value
Prefer to talk? Call (888) 719-0248.
Frequently Asked Questions
Common Questions About the AI Value Engine
If you do not see your question here, contact us and we will walk through your specific situation.
How is the AI Value Engine different from a typical AI implementation?
Most AI projects begin with tools and experimentation. The AI Value Engine starts with business outcomes, data readiness, governance, and process alignment. We treat AI as an operational capability, not a proof of concept, so it delivers measurable impact and can scale responsibly.
Do we need mature data to begin?
You don't need perfection, but you do need clarity. We assess data structure, ownership, and quality early in the process. If gaps exist, we address them before deployment to prevent unreliable outputs and stalled adoption.
What kinds of AI initiatives do you typically support?
We focus on practical, high-impact use cases within Microsoft's ecosystem, including AI agents, workflow automation, forecasting, operational intelligence, and decision support scenarios tied directly to measurable business outcomes.
How long does an engagement typically take?
Timelines vary based on scope and readiness. Initial strategy and readiness phases are typically measured in weeks, not months. Delivery timelines are defined clearly up front to ensure controlled execution and predictable outcomes.
How do you manage risk and governance?
Governance is built into the delivery model from day one. We define ownership, establish usage guardrails, align to security and compliance requirements, and ensure AI outputs are monitored and accountable, protecting both operational integrity and organizational credibility.