5 people or 50,000.
Same craft.

The patterns that work for a Fortune 100 cloud architecture apply to a local bakery tired of paying the SaaS subscription tax. Scale changes. The thinking doesn't. Here's how engagements typically look across the four kinds of orgs we work with.

01 // Enterprise & Mid-Market

Existing systems. New AI capability. Senior voice in the room.

The most common engagement shape here: you already have cloud infrastructure, you have engineering talent, you have data, and you have a board or exec team that wants AI capability added. What you don't have is somebody who's done this five times before, can call out the dead ends quickly, and is comfortable writing code and writing a board memo about it in the same week.

That's the role. We slot into your existing rhythm (architecture review, leadership standup, sprint planning, whatever you run) and we work alongside your team. We don't replace your people. We give them air cover, and we help them avoid the mistakes that show up the same way every time.

Typical engagements:

What this looks like

  • AI feature added to an existing product, end-to-end
  • Cloud architecture modernization (often off VMware)
  • Pre-RFP technical architecture review
  • Embedded fractional CTO for a strategic initiative
  • Vendor evaluation: AWS Bedrock vs. Azure OpenAI vs. self-hosted
  • Multi-tenant SaaS retrofit (auth, RLS, OPA, all of it)

FIT: Fractional CTO, Fractional SE, Scoped Project

Build the right thing. Pick the right stack. Talk credibly to technical investors.

Founder/CEO without a senior technical co-founder is the most common version of this. You've got a product idea, you've got customers, you've got runway, and you need somebody who can answer "is this the right architecture?" with the authority of having actually built the wrong one before.

We're not a replacement for hiring your first VP Eng. We're the bridge between "two devs and a vision" and that hire. We help you ship the MVP without painting yourself into a corner. We talk to your technical investors so you don't have to fake the answers. And we tell you when it's time to hire the full-time person and what to look for.

What this looks like

  • Fractional CTO from pre-seed through Series A
  • Architecture decisions for the MVP that won't need a rewrite at scale
  • Technical due-diligence prep for investor conversations
  • Picking the AWS/Azure/GCP stack and standing it up
  • RAG and agentic features done right the first time
  • Recruiting help for the first three engineering hires

FIT: Fractional CTO, AI Readiness Assessment, Scoped Project

03 // Small & Local Business

Tired of the SaaS subscription tax. Want tech that fits.

Five employees or fifty. The dentist's office, the regional construction firm, the multi-location restaurant group, the boutique law firm. You're paying for fifteen SaaS subscriptions and using maybe four of them at any depth. Your processes live in someone's head. Your data is in a spreadsheet somebody emails around. And every AI vendor pitching you wants $50/seat/month for something that doesn't quite fit how you work.

We can fix that. A right-sized stack (sometimes cloud, sometimes a Mac Studio in the back office, sometimes both) that does what your business actually does, in the way you actually do it. On-site available across Central Florida. Remote everywhere else.

What this looks like

  • Custom AI assistants that know your business, not the generic model
  • SaaS subscription audit and consolidation
  • Local-first AI that doesn't leak your data to a vendor
  • Automating the things your team currently does by hand
  • A simple, documented stack you can hand to your next IT person
  • Mac Studio-based AI workstations for back-office work

FIT: AI Readiness Assessment, Scoped Project

Real infrastructure for the orgs the hyperscalers ignore.

Mission-driven organizations deserve the same technology access as the enterprise, and they almost never get it. The vendor sales motion isn't tuned for nonprofits. The pricing isn't right. The complexity is wrong. The result is that mission staff spend hours fighting their tooling instead of doing the work.

Privian was partly founded to fix that gap. We bring real AI infrastructure (the same patterns we use for the Fortune 100) to community organizations, school districts, regional libraries, and the kinds of nonprofits that need this work more than anyone but can't get it. Reduced rates available where they're needed.

What this looks like

  • Document search and summarization for mission staff
  • Donor and grant workflows that don't require a $40k/yr SaaS
  • Privacy-first, local-only AI for sensitive populations
  • Volunteer coordination and outreach automation
  • Training your team to maintain it once we're gone

FIT: Scoped Project, AI Readiness Assessment

Not sure which of these is you?

Tell us what you're working on. We'll figure out the right shape together.

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