evanparra.ai

AI engineer · Jacksonville / St. Augustine

Own the software your team actually uses.

I replace per-seat ERP, BI, and workflow SaaS with apps that run in your cloud. $150K/yr off one client's bill so far. Imagine your operations without SaaS sprawl, data silos, or a brittle ERP.

How much more could your team accomplish with software built around them?

Let's talk

How I work

Four ways to work together.

Scope, timeline, and price get set in conversation per engagement. I'd rather understand what you actually need than sell you a tier.

Embed

Embedded fractional AI engineer.

I plug into your team for a multi-month engagement and ship production systems in your cloud. Mid-market companies replacing per-seat SaaS spend are the founding pattern; same shape works for any team that needs a senior AI engineer for a defined build window without the 4 to 6 month hiring drag.

Good fit when

You have a workflow that should be automated, the data lives somewhere accessible, and you'd rather embed an engineer for a quarter than hire one for a year.

Subcontract

Drop-in for PE sponsors and advisory firms.

Operating partners and tech-advisory firms bring me into one of their portfolio companies or client engagements. Common patterns: pre-sale tech cleanup, post-acquisition integration, or a discrete AI build that an existing advisor doesn't staff internally.

Good fit when

You're an advisor or sponsor with a client who needs production AI work delivered, and you want a named engineer behind the keyboard. Not a generalist subcontracted out by a consultancy.

Project

Bounded scope, single workflow.

A defined automation, integration, or AI feature with clear edges and a fixed outcome. Smaller and faster than an embed, with a longer relationship not part of the deal.

Good fit when

You can describe the one thing you'd ship if you had an engineer for a couple of weeks. Sometimes that's an internal tool, sometimes it's a customer-facing AI feature.

Advisory

Senior eyes on demand.

You have a team but want a senior AI engineer available for architecture review, code review, model selection, vendor calls, or sanity-checking the build before it ships. Monthly retainer, capped hours, no new feature builds.

Good fit when

You have someone shipping AI but want a second set of senior eyes, particularly for evaluation harnesses, retrieval quality, and "is this actually production-ready" calls.

Why this is different

You've been pitched AI before. Here's what's different.

Real savings, not promises.

$150K/yr already off one client's SaaS bill. Per-seat ERP licenses retired, replaced with custom apps they own. The math is auditable before you sign anything.

Production code, not pilots.

Embedded today at a regional commercial contractor, shipping apps that replace per-seat ERP. Two live products of my own: TextTimeline (family-law evidence search with 100% citation coverage) and GammaRips (14 Cloud Run services running an autonomous overnight options scanner). The work runs in production every day.

The workflows no vendor will build.

Once you own the system, the asks that never made the vendor roadmap become buildable: cross-system reporting, multi-stage approvals, customer-specific exports, agent workflows grounded in your real business semantics. The ceiling moves.

Founding case

What it looks like in production.

The pattern shipping today at a regional commercial contractor.

Regional Commercial Contractor · Construction

$150K/yr in retired per-seat ERP cost (and growing)

Embedded inside the contractor's own Azure tenant, replacing seat-licensed ERP workflows app by app. Cost-to-complete forecasting, change orders, approvals. Reads go through a drift-monitored knowledge base built from thousands of live ERP SQL views. Writes go through the vendor's official REST API. The ERP stays. The seats don't.

That $150K/yr is just the headline ERP line. Adjacent per-PM ERP seats are decommissioning in parallel and BI tool seats stack on top. Every role's daily flow that moves off the ERP surface drops the bill further.

Beyond the savings, the apps unlock cross-system flows no per-seat tool delivers: multi-trade rollups, change-order routing, and field data landing in one approval surface. The savings paid for the work; the workflows are why it keeps shipping.

Read the full case study →

Also in production

See all case studies →

The stack

The tools I trust to ship.

Built on

  • Google Cloud
  • Vertex AI
  • Azure
  • Firebase
  • Stripe
  • Anthropic
  • Claude Code

I ship on the stack I trust. No named client logos yet, I'd rather show you the work.