Skip to content
Provi.ai
Services

Four engagement shapes. Fixed scope. Senior engineers.

We don't do hourly billing for discovery loops. Every engagement starts with a scoped outcome, named deliverables, and dates. Three deployment modes - public cloud, Azure AI Foundry in your tenant, or fully air-gapped on-prem - picked to fit your risk profile, not ours.

2–3 weeks

AI Readiness Audit

Best for: Leadership getting alignment before committing budget

Executive workshops, workflow scoring, and an honest 90-day roadmap. You leave with a ranked opportunity set, ROI estimates, and the projects we'd kill first.

Book the audit
Deliverables
  • Stakeholder interviews (CEO, ops, IT, security)
  • Workflow inventory & opportunity scoring matrix
  • AI risk register & governance recommendations
  • Build-or-buy analysis per opportunity
  • 90-day roadmap with named projects, owners, success metrics
4–10 weeks

Cloud Implementation

Best for: Teams ready to ship one or two workflows using frontier APIs

Frontier APIs (OpenAI, Anthropic, Gemini) integrated with your stack - governed, observable, and instrumented from day one. Knowledge transfer baked in so your team runs it after we leave.

Scope a cloud build
Deliverables
  • Architecture, model selection, prompt engineering
  • RAG over your CRM, knowledge base, SharePoint, or custom
  • Microsoft 365 Copilot rollout with role-based DLP and prompt logging
  • Workflow automation (Power Platform, n8n, Zapier, custom)
  • Evals, dashboards, and a runbook for your team
6–12 weeks

Azure AI Foundry

Best for: Microsoft-shop organizations needing sovereignty without on-prem lift

We deploy frontier-grade AI inside your Azure tenant through AI Foundry. Models, retrieval, agents, and evals - all running under your subscription, your keys, and your identity stack.

Scope a Foundry build
Deliverables
  • Foundry hub / project provisioning aligned to your landing zone
  • Model catalog setup (GPT-4o, Llama, Mistral, Phi) with model routing
  • Customer-managed keys (CMK) + private endpoints + Entra ID
  • RAG with Azure AI Search or pgvector on customer storage
  • Foundry-native evals, prompt flows, and Azure Monitor observability
8–16 weeks

Air-Gapped AI

Best for: Regulated enterprises and government - data cannot leave

Sovereign LLM and RAG stacks behind your firewall. Llama / Mistral / DeepSeek on GPUs you control, hardened to your compliance frame.

Talk to engineering
Deliverables
  • Hardware sizing and GPU provisioning plan
  • vLLM / TGI deployment with hardened policy controls
  • Sovereign RAG (pgvector / Qdrant / Weaviate) on your storage
  • Auth gateway, SIEM integration, full audit logging
  • Compliance documentation aligned to your framework
Back-of-envelope ROI

What's a high-leverage workflow worth, in real money?

Set three sliders. We'll show conservative recovery bands - what a well-scoped AI workflow typically returns. Estimates only; actual ROI varies by workflow and adoption.

50 people
5500
6 hours
120
$85 / hr
$40$250

Methodology. The low end of the band assumes recovery of 25% of automatable hours; the high end assumes 45%. These are typical ranges from well-scoped AI rollouts - bad rollouts recover 0%. Includes only direct time savings, not strategic upside (faster cycle time, better quality, etc.).

Projected recovery
Hours saved / week
-
Recovered / quarter
-
Recovered / year
-
Range, not a guarantee. Get the project-specific number - and the workflows where the math actually holds - from a 30-minute scoping call.
Pressure-test this number
Compliance fit

Pick your frameworks. See which mode actually meets them.

Verdicts reflect what's typically achievable with appropriate controls and contracts - not vendor marketing claims. We're not an audit firm; this is engineering experience translated into a quick filter.

Frameworks in scope

Select one or more frameworks above to see how the three deployment modes compare.

How we work

Outcomes measurable before invoice two.

Fixed scopes. Senior engineers. Honest dates. We've been shipping production systems since 2016 - applying the same discipline to AI is just the next chapter.

  1. 01 Week 1–2

    Discover

    Executive interviews, workflow mapping, and a candid look at where AI will and won't move the needle. We leave with a ranked opportunity set and an honest risk register.

  2. 02 Week 2–4

    Design

    Reference architecture, data flows, model selection, and a build plan with measurable outcomes. We pressure-test the plan against your compliance and security posture.

  3. 03 Week 4–10

    Build

    Engineers write the code. Real software in your environment - frontier APIs or air-gapped stacks, with evals and observability from day one.

  4. 04 Ongoing

    Operate

    We run the system with you until your team is ready to run it alone. Monitoring, evals, model updates, and a clear off-ramp when you outgrow us.

Ready to find your highest-leverage AI project?

Book a 30-minute strategy call. We'll ask sharp questions, give you our honest read, and tell you whether we're the right team for the work.

Book a strategy call [email protected]
Accepting new engagements Free 30-minute first call NDA-ready