V2 AI is an APAC-based data and AI consultancy that delivers enterprise data platform modernisation, MLOps and generative AI adoption programs, and cloud cost optimisation through advisory, engineering delivery, and upskilling services.
Published Oct 9, 2026
V2 AI is a consultancy, and mainstream software review platforms (G2/Capterra) generally focus on SaaS products rather than consulting firms. No clear, reputable G2/Capterra listing was found for V2 AI as a consultancy.
A search surfaced listings for other companies with similar names; these refer to different entities and were excluded from this evaluation.
V2 emphasises regulated or governance-heavy sectors:
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You require globally distributed delivery at very large scale
You require publicly available compliance attestations (SOC 2/ISO 27001)
You require entirely vendor-neutral stack selection
Your scope is very small or highly tactical
Vendor-published quotes on the company website include statements from client representatives expressing positive experiences. These are vendor-curated and should be validated through direct reference checks. Examples paraphrased from the site include:
These testimonials are not independent validations.
Because customer reviews on major platforms are scarce, the closest outside indicators are employee review sites:
Interpretation: The public review footprint is fragmented and name-collision-prone. Procurement processes should request direct client references relevant to the buyer's platform and industry.
What V2 reports it delivered:
Vendor-published metrics (reported by V2):
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What V2 reports it delivered:
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What V2 reports it delivered:
Vendor-published metrics (reported by V2):
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V2 AI is an APAC-based data, artificial intelligence, and modernisation consultancy. It describes itself as an outcome-oriented partner for enterprises (often in regulated industries) and offers advisory, delivery/engineering, and upskilling/enablement services. In practice, V2 AI appears to deliver:
V2 AI operates as a services firm rather than a packaged SaaS product. Prospective buyers should evaluate it like a system integrator or consultancy: methodology, delivery staff, referenceability, governance maturity, and contractual terms are generally more important than a feature checklist.