Stalled AI maturity
Most companies accumulate proofs of concept that never reach production or the P&L.
Proofs of concept that never reach the P&L
Gartner Research 2026
Most companies never get past the experiment. VLNX delivers what is measurable.
Measurable AI outcomes, delivered by senior people and accelerated by proprietary assets — not by an army of consultants.
How it works45%1
of high-AI-maturity organizations keep AI in production for 3+ years (vs 20%)
Gartner, 2025
57%1
of high-AI-maturity organizations have the business ready and confident to use AI (vs 14%)
Gartner, 2025
39%2
of technology leaders are confident their AI investment will have positive financial impact
Gartner, 2026
4×2
more in data and analytics foundations is what successful AI organizations invest
Gartner, 2026
The problem
AI stalls between the pilot and the outcome
Market data shows a consistent pattern: AI initiatives don't scale, data isn't ready, and impact isn't measured.
Data not AI-ready
Without a trustworthy data foundation, models perform in demos and fail in production.
The data foundation separates demo from production
AI ROI not tracked
Without measuring financial impact, AI becomes a cost center with no mandate to scale.
Without ROI, AI becomes a cost center
Legacy architecture as bottleneck
Legacy systems and siloed data prevent delivering AI solutions at scale.
Legacy and silos block scale
AI Maturity Check
Want to see where your company stands?
A sample of the VLNX AI Assessment methodology: the check returns an automatic read-out of your AI maturity stage, in 2 minutes — the starting point, not the assessment.
The read is generated by our own AI — living proof that we run VLNX with AI.
Solutions
From strategy to production, with ROI as a commitment
Two complementary services — designed to start from the outcome and work backwards.
AI strategy consulting
Maturity assessment, a roadmap prioritized by economic impact, and governance with AI FinOps.
- Data readiness map
- ROI-prioritized roadmap
- AI governance model
- AI cost view (FinOps)
AI and data project delivery
Production delivery with data-centric architecture, observability, and embedded technical governance.
- AI-ready data foundation
- Solution in production
- End-to-end observability
- Documented handover
Method
We start from the outcome and work backwards
Four steps. Each with a concrete deliverable. The last one closes with measurement — ROI as a commitment, not a promise.
-
01Outcome
What business outcome needs to happen?
Before any technology, we define the measurable outcome that justifies the investment.
Outcome definition (1 page) -
02Problem
What is blocking that outcome today?
We map the real gaps — data, architecture, process, and skills — and their root causes.
Gap and root-cause map -
03Solution
What needs to be built — and what doesn't?
We design the shortest path to the outcome, with fixed scope and projected ROI.
Proposal with projected ROI -
04Delivery
Iterative delivery validated by the outcome
We ship to production in short cycles, validating each increment against the outcome and measuring impact.
Solution in production + impact dashboard
Contact
Is your company ready to scale AI?
The work is the VLNX AI Assessment. Before it, a free 30-minute diagnostic session, conducted by VLNX's founding partner: 30 minutes to review your case critically and decide whether there's a business outcome that justifies the Assessment now.