Technology Fast 50 Pragmatics of AI workshop
AI Strategy Workshop for teams ready to move from ideas to execution.
Most teams don't need another AI inspiration session. They need to pick the right workflow, align on the business case, and define the first Proof of Value.
Trusted by operators
-
+11.76% orders from day 1 of the Australian launchThree-agent product advisor guiding customers through print-order configuration.
Read case study -
Supply chain intelligence agents reducing manual coordination overhead.
-
37 kernels ported from CUDA to Intel GaudiProduction AI workloads moved to new hardware for on-prem LLM deployment.
-
AI agent implementation for a global automotive enterprise.
-
2 hrs → 3 min to generate a workflowText-to-workflow agents building validated node graphs inside the platform.
Read case study -
44% → 98% raw LLM vs guideline-executing accuracy on the open 50-scenario benchmarkHIPAA-compliant guideline-executing triage — 44% to 98% on the open 50-scenario benchmark.
Read case study
Workshop approach
Practical AI strategy guidance for decisions that lead to execution
Most teams do not need another presentation on what AI might make possible. Our AI workshops align business, operations and engineering on the outcome that matters: leaving with prioritized use cases, decisions and a practical next step — not more ideas.
Workflows
Which processes are worth changing
Identify where AI agents can realistically improve operations — and where they cannot.
Readiness
Data, technology and risk
Assess whether your data and systems are ready, and which risks must be addressed before you commit.
Execution
From idea to production
Define what to test first and how to move from an early concept to a production system.
Engagement formats
Choose the right AI workshop or advisory engagement
01 / 03
Advisory and consulting
Best fit if your leadership needs decision-making support across a broader AI transformation — not just a prototype.
- Readiness assessment plus governance & risk mapping
- Prioritized use-case portfolio and roadmap direction
- Ongoing strategic and technical advisory
02 / 03
Execution workshops
Best fit if you want progress on one workflow/process and a concrete next step.
- Map the workflow, constraints and success criteria
- Prioritize AI opportunities by value and feasibility
- Recommend Proof of Value scope and next step
03 / 03
Workshops, training and team upskilling
Best fit if you want internal capability while reducing delivery risk.
- Practical training on agentic AI patterns and limits
- Identify workflows suitable for AI automation
- Turn prototypes into production-ready delivery plans
Outputs
What you will leave with
Exact outputs depend on the format and maturity of your initiative. A typical engagement gives your team:
01
A shared view of the opportunity
Business, operations and technical stakeholders align on the workflow, expected value and constraints — before anyone commits budget or engineering time.
02
Prioritized AI use cases
Options evaluated by business impact, feasibility, data readiness, risk and time to value — so you know what to start with.
03
Feasibility and readiness signals
Assessment of data, systems, integrations and operating-model constraints that determine whether delivery is practical.
04
Evidence for investment decisions
Key risks, assumptions and dependencies clarified — including what needs validation in a Proof of Value.
05
Recommended Proof of Value scope
A concrete next step: what to validate first, what inputs to use, and what production would require if the signal is strong.
Execution path
From workshop insight to production impact
A workshop can stand alone as a decision accelerator. When the case is strong, we move in three clear stages:
Workshop and prioritization
We align business, operations, and technology around one workflow that is worth changing now. The output is a prioritized scope, success criteria, and a clear owner.
- Prioritized use cases
- Decision criteria
- Scope and ownership
Proof of Value
We validate the highest-risk assumptions on real workflow inputs and business constraints, so investment decisions are based on evidence, not optimistic estimates.
- Assumptions tested on real data
- Risk and feasibility signal
- Go/no-go recommendation
Production delivery
When the signal is strong, we continue into architecture, integration, and rollout — with observability, operating safeguards, and team handoff built in from the start.
- Production architecture
- Integration and observability
- Team enablement and handoff
Workshop approach
Built around your workflow, not generic AI hype
We shape the session around your production constraints so your team leaves with a practical next step.
Business process first
We begin with your workflow, data, systems and expected outcome — not a preferred model or tool.
Cross-functional workshop room
Business, operations, technology, product, data and security — the owners of the affected workflow.
Not an AI inspiration talk
Designed to support decisions and execution, not only generate enthusiasm.
Not a generic tool demonstration
Tools change quickly. We focus on capabilities, architecture and the evidence required for dependable delivery.
Proof in practice
The proof is in the people
Workshop prioritization connected to measurable production signals.
Insights
Related reading
Practical perspectives on agentic AI adoption, delivery, and production systems.
Agentic AI
Why most agentic AI projects fail before a single line of code is written
42% of enterprises abandoned most AI initiatives before production in 2025, up from 17% (S&P Global). The failure happens during planning.
Strategy
From "where do we start?" to production: how mid-market companies actually ship agentic AI
PwC finds 79% adoption; KPMG finds 11% at full production. The gap is a starting position, not a technology problem — and how to build one.
Blog
View all articles
More perspectives on agentic AI, delivery, and production systems.
Browse the blogFAQ
Frequently asked questions
What is an AI workshop?
A focused working session where business, operational and technical stakeholders examine a real workflow, find where AI and agentic AI can create value, prioritize use cases and agree on a next step. Built around your processes and data — not generic AI education.
What is the difference between an AI workshop and AI advisory?
An execution workshop targets one process, product opportunity or stalled initiative and produces prioritized use cases and a delivery path. AI advisory is broader, ongoing guidance across a wider transformation — opportunities, architecture, technology and governance. Many engagements start with a workshop and continue into advisory, a Proof of Value or production engineering.
Is the workshop suitable for teams that are only beginning with AI?
Yes. The session can begin with opportunity discovery and a practical introduction to Agentic AI. It still remains focused on your organization, workflows and decisions rather than general AI education.
Can you work with a team that already has an AI prototype?
Yes. The workshop can focus on architecture, evaluation, data quality, integration, operational reliability or the reasons the prototype has not reached production.
Is this only for technical teams?
No. Executive and operational involvement is often essential because the most important questions concern business ownership, process change, risk and measurable outcomes. Technical depth can be adapted to the participants.
Can the workshop focus on one specific workflow?
Yes. This is the recommended format when a team already knows which process, customer journey or product capability it wants to improve.
Do you recommend particular AI platforms or models?
Recommendations depend on the use case, data, infrastructure, security requirements and the capabilities of the internal team. We do not begin with a predetermined vendor or technology.
What happens after the workshop?
You receive agreed outputs and recommendations. Depending on the findings, the next step may be internal execution, further advisory, a technical assessment, a Proof of Value or a production engineering engagement with Vstorm.
Start with the decision you need to make
You do not need to arrive with a complete AI strategy.
Bring us a business process, a product opportunity or a stalled initiative. Tell us what you want to improve and who should be in the room. We will recommend a practical format for the next step.