VERITY AI · Launch

Verity AI Launch: From Business Case to Governed Production

A structured, single-workflow path from a defined AI business case to a governed production system — discovery through operations, in one accountable engagement.

The Problem

Most AI Pilots Never Reach Production

According to Deloitte’s 2025 Emerging Technology Trends in the Enterprise Survey (as reflected in Deloitte’s Tech Trends 2026 research), 38% of organizations are piloting agentic AI, but only 11% have agents running in production. The gap between the two isn’t a technology problem — it’s an ownership problem. No one owns the whole path from a working demo to a system with real integration, security review, governance sign-off, and an operator who keeps it running.

Verity AI Launch is that path, owned end to end. One scoped workflow, one accountable team, from business case to a production system you can actually run — not another pilot that quietly stalls.

Who This Is For

Organizations with one clear, scoped AI use case and an executive sponsor ready to take it to production — not enterprise-wide AI sprawl across multiple business units without a shared standard. (If that describes your situation instead, ask us about our broader AI transformation program when we scope your project.)

Engagement Phases

Nine Phases, One Accountable Team

Every phase is delivered by the same team — no handoff between a strategy firm, a dev shop, and a security vendor.

1
Discover
Confirm the business case, current AI footprint, and data sources for the target workflow.
2
Govern
Establish governance requirements for this workflow — data sensitivity, approval authority, regulatory exposure — before design begins.
3
Design
Architect the system: model/provider selection, retrieval design, integration points, identity and access model.
4
Prototype
Build a working prototype against real (or representative) data to validate the approach before full build investment.
5
Build
Full engineering build: the application, integrations, and workflow automation defined during design.
6
Secure
Prompt-injection defense, data boundaries, tool authorization, and output controls engineered in, not reviewed after the fact.
7
Validate
Evaluation against defined success criteria, security testing, and governance sign-off before go-live.
8
Deploy
Production deployment into your environment, with rollback and incident procedures defined before go-live, not after.
9
Operate
Transition to ongoing operations — see “What Happens After Launch” below.
Deliverables

What You Receive

Architecture & design documentation

System architecture, data flow, and integration design for the target workflow.

A production system

The deployed, working application — not a demo or a proof of concept left for your team to finish.

Security & governance evidence

Records of the security controls implemented and the governance sign-offs obtained during Validate.

Evaluation & audit records

Structured execution traces, evaluation results, and audit metadata — not raw hidden model reasoning, which isn’t something any vendor can honestly promise to expose.

Operations handoff plan

A defined transition into ongoing operations, whether through Managed AI Operations or your own team.

Timeline & What Success Looks Like

Timelines are scoped to workflow complexity, integration requirements, and data sensitivity during the Discover phase — we don’t publish a fixed week count that doesn’t hold up across genuinely different engagements.

Success is a running production system with an accountable operator — not a demo that impressed a steering committee and then quietly stopped moving forward. If Launch doesn’t end with a system your business is actually using, it hasn’t succeeded.

What Happens After Launch

A deployed system still needs someone watching uptime, cost, model changes, and evaluation drift. Launch transitions directly into Verity Managed AI Operations — the same standard of accountability, continued.See Managed AI Operations →

Frequently Asked Questions

What does AI Launch cost?
Engagements are scoped based on workflow complexity, integration requirements, data sensitivity, and production requirements. We provide a written proposal after the Discover phase’s initial scoping call, before any commitment.
Do we need an existing AI governance program first?
No — the Govern phase establishes what’s needed for this specific workflow. If you already have a Verity AI Governance Program or a vCAIO in place, Launch works within it rather than duplicating it.
What if we already tried a pilot that stalled?
That’s a common starting point. Discover includes reviewing what already exists — a stalled pilot is often reusable input, not wasted work, once it’s given the integration, security, and governance path it was missing.
Can we use our own AI model or cloud provider?
Yes. Model and infrastructure choices are made during Design based on your constraints, not dictated by a fixed platform.

Ready to Plan a Governed AI Launch?

Engagements are scoped based on workflow complexity, integration requirements, data sensitivity, and production requirements. Every engagement starts with a scoping call and a written proposal.Request a Launch Proposal →

Part of Armorstack’s VERITY AI program.