VADIXAI Consulting ← All services
AI Consulting

AI consulting that ends in shipped software

From strategy and use-case discovery to custom models, automation, integration and deployment — we take AI from idea to production on Azure, built for organizations whose data can't go to someone else's cloud.

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The Problem

The pilot works. Then it dies.

Industry research consistently finds that the large majority of enterprise AI initiatives never reach production. The model is rarely the problem — the operating model around it is.

Compliance veto

Compliance treated as a final checkpoint instead of a design constraint. GxP, HIPAA, and SOC 2 reviews kill the project at the finish line.

Security objection

Public network paths to AI services, API keys in code, no privileged identity management. InfoSec says no — correctly.

Cost surprise

The first production month arrives at several times the pilot estimate. No token budgeting, no caching, no model-tier strategy.

Quality drift

Output quality degrades and nobody notices, because no evaluation harness was ever built.

Ownership vacuum

The pilot team moves on. No runbook, no on-call, no budget owner — so the workload quietly rots.


What We Do

Eleven ways we put AI to work

Start with strategy and let it scope the rest, or come in at the one you need. Every engagement is fixed-scope and ends with something you own.

01

AI strategy

Where AI fits in your business and what to build first.

02

Use-case discovery

Finding the high-value tasks worth automating or improving — and the ones that are not.

03

Process automation

Chatbots, workflows, document handling and data entry that run without a person in the loop.

04

Custom model development

Building or fine-tuning models for the needs an off-the-shelf model cannot meet.

05

Data prep and governance

Organizing your data, quality checks and access rules so AI has something trustworthy to work with.

06

Integration

Connecting AI with CRM, ERP, websites, APIs and internal systems so it changes what actually happens.

07

Analytics and forecasting

Predictions, dashboards and trend analysis your team can act on.

08

Prompt engineering

Designing prompts and systems that give reliable outputs, not lucky ones.

09

AI training

Teaching your teams how to use AI effectively — and where not to.

10

Risk and compliance

Security, bias checks, policy guidance and testing built in from the start.

11

Deployment and support

Rollout, monitoring, maintenance and iteration once it is live.


How We Engage

Three scoped engagements, not open-ended hours

Each one is fixed-scope with defined deliverables, and each naturally scopes the next. Start at the top — it's designed to be a low-risk way to find out whether we're the right partner.

ENGAGEMENT 02

Pilot-to-Production Sprint

4–6 WEEKS

Take one AI use case — new, or stalled — and put it into production properly: identity, private networking, evaluation, cost guardrails, and a runbook.

  • Azure OpenAI deployment with Private Link, no public paths
  • Managed Identity throughout — no API keys in code
  • RAG pipeline: ingestion, chunking, hybrid retrieval, citations
  • Automated evaluation harness with a labeled test set
  • Token telemetry, cost guardrails, and content safety
  • Runbook, on-call handoff, and team walkthrough
You walk away with: one workload live against real traffic, with the observability to prove it works.
ENGAGEMENT 03

AI Platform Foundation

8–12 WEEKS

Build the platform layer so the next ten AI workloads take weeks instead of quarters — the move from one working thing to an operating capability.

  • AI landing zone aligned to the Cloud Adoption Framework
  • Shared platform components product teams can build on
  • Policy-as-code guardrails and a governed model catalog
  • FinOps baseline: tagging, per-team showback, budget alerts
  • Everything as Bicep or Terraform — reproducible, no drift
  • Enablement sessions and full knowledge transfer
You walk away with: a platform your team runs without us — that's the point.

Why VADIX

What makes this different

🏛

Regulated by default

Two decades in pharma, healthcare, financial services, and insurance. GxP, HIPAA, SOC 2, and PCI DSS are design inputs here, not surprises at the end.

🔒

Your data stays yours

Private Link, Managed Identity, customer-managed keys, and — where it matters — fully local models. Nothing leaves your tenant that you didn't choose to send.

🚢

We ship, not just advise

We build and run production software ourselves. Every recommendation is one we've had to live with operationally.

📐

Everything as code

Bicep, Terraform, policy-as-code. Reproducible environments, peer-reviewed infrastructure, and a clean handoff — you're never locked to us.

Read the thinking before you buy the work

The Enterprise AI Playbook is our 26-page field guide covering the maturity model, the Azure reference architecture, the compliance playbook, FinOps for AI workloads, and the 90-day roadmap. It's the same framework we run engagements on.

Get the Playbook

Start with a conversation, not a contract

Thirty minutes. Tell us about your environment, your compliance context, and what you're trying to achieve. We'll tell you honestly whether we're the right fit.

Book a Discovery Call