A consulting-led planning phase delivered through focused workshops that converts AI ambitions into a concrete, measurable implementation plan. We align stakeholders on the business outcomes to pursue, prioritize the best-fit use cases (value vs feasibility vs risk), and map current workflows (As-Is) against the target operating model (To-Be) for AI Agents—defining what the agent should do, what information it needs, and when it must escalate to humans. In parallel, we assess knowledge and data readiness by identifying sources of truth, ownership, and the minimum “AI-ready” structure required for reliable, compliant answers. The phase concludes with a clear Point A → Point B gap analysis and an actionable roadmap, including a vendor-neutral PoC Scope of Work that Hawaiiana can use with Vstorm or any qualified AI agent implementation partner.

A rapid, agile delivery phase that turns the selected use case into a working PoC and then iterates toward a production-ready MVP—proving ROI before a full-scale rollout.
With clear success metrics defined in Phase 1, we build in small, decisive increments: each sprint delivers a tangible capability (e.g., one intent group, one workflow step, one integration), tested with real users and real data. This approach reduces risk—especially in AI—because it quickly surfaces data and process gaps, validates assumptions, and keeps every engineering decision anchored in measurable business value. As the PoC stabilizes, we harden it with the essentials needed for scale: governance and guardrails, evaluation and analytics, human handoff, and the integrations required to complete the workflow end-to-end. If the client has an internal AI/IT team, we run the PoV collaboratively—combining Vstorm’s agentic AI patterns and engineering expertise with the client’s domain knowledge to accelerate adoption and ensure the solution fits operational reality.

The phase where AI becomes a real operating capability—not a standalone tool. We embed Vstorm experts into your delivery rhythm to drive adoption, knowledge transfer, and measurable outcomes. We focus on the organization as much as the technology: standardizing how teams use the agent, designing handoffs and accountability, training users, and setting up governance so the solution remains accurate, compliant, and continuously improved. Our AI Transformation Manager ensures the agent is integrated into day-to-day workflows and that the change sticks—turning the built technology into sustained business impact and scaling it to additional processes. The phase concludes with structured ownership transfer: documentation, runbooks, and technical enablement so your team controls the code and infrastructure with no vendor lock-in.