Mastascusa Holdings · Build
AI automation, shipped in days. Fixed price. Fixed scope.
Senior ML engineer, picking up where lightweight wrappers fall short. You get production-grade AI work — eval harness, monitoring, deployment doc all included — with the price and the deliverable on the page before the first call.
Beta cohort · half off
The first three customers get 50% off in exchange for written permission to publish the engagement (anonymized fine) as a case study. Full price from customer #4 forward.
Three ways to work together
1 week
Automation Sprint
One specific thing shipped
$1,500
Beta: $750 · first 3 customers
You have one AI integration in mind — a Claude-powered support triage, a smart classifier, an LLM-backed search. We scope it on the call, build it the same week, and ship it with a written handoff.
What you walk away with
- · Working integration deployed to your environment
- · Prompt + tool schemas checked into your repo
- · Smoke-test eval harness covering the golden-path cases
- · Written deployment doc + monitoring notes
You know what you want built, you just need a senior pair of hands to ship it without disrupting your roadmap.
Talk to me about this
2 weeks
AI Foundation
Production-grade AI stack stood up
$4,900
Beta: $2,450 · first 3 customers
You're going to ship multiple AI features over the next quarter. The Foundation establishes the production discipline up front — the eval harness, the monitoring, the deployment story — so you don't have to retrofit it under pressure.
What you walk away with
- · LLM API integration with structured tool-use scaffolding
- · Eval harness with regression tests for every prompt change
- · Cost + latency + token monitoring with alerting
- · Deployment doc + rollback runbook
- · One reference feature shipped on top of the stack
You're past the prototype and want production discipline before you scale AI usage across the product.
Talk to me about this
4 weeks part-time
Embedded Month
One AI feature shipped end-to-end
$9,000
Beta: $4,500 · first 3 customers
I shadow your founders for a month, scope to ship, and build a meaningful AI feature in collaboration with your team — code review, eval design, monitoring, the full path. You walk away with the feature and the playbook.
What you walk away with
- · One end-to-end AI feature shipped to production
- · Eval suite + monitoring instrumented and handed off
- · Code reviewed alongside your team in your stack
- · Architectural notes for the next 2–3 features in the roadmap
- · On-call coverage for the first 2 weeks post-ship
You want a senior ML engineer working alongside the team for a month, not a contractor on the outside.
Talk to me about this
What "ML-engineer-grade" actually means
Eval before deployment
Every Foundation and Embedded engagement ships with a regression eval harness. Prompt changes never go to production without a green run. Most low-priced LLM-integration offers skip this entirely — and that's why their work doesn't hold up under real production load.
Monitoring as a default
Cost, latency, token usage, error rate, and content-flag rate are instrumented and alerting before the first user hits the feature. You learn about a degradation from your dashboard, not from a customer.
Built against the rubric we publish
The same maturity rubric we use to audit other companies' AI deployments is the standard the build is held to.
Read it →
Senior, not staffed-down
The person scoping the work is the person doing the work. Day-job: production ML engineer leading a 6-person AI imaging team. Zero handoff loss.
Background →
Common questions
- What if the scope grows mid-engagement?
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The scope is fixed. If the work changes, we have a 5-minute conversation, agree to a change order in writing (priced at the same SKU rate or a clearly bounded add-on), and I keep building. No surprise invoices.
- What stacks do you work in?
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TypeScript / Node, Python, Go. Anthropic, OpenAI, and open models. Vercel, Cloudflare, AWS, GCP. If your stack isn't here, ask — I'll be honest about whether I'm a fit.
- Do I need to sign anything before the call?
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No. The first call is free. We sign a mutual NDA + a one-page SOW only when we agree on the scope.
- Why is the price on the page?
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Because hiding it wastes everyone's time. The fixed price is the differentiation against hourly freelancers and "talk to sales" consultancies. If the SKU is a fit, we move fast; if it isn't, you saved a discovery call.
- What happens after the engagement ends?
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Optional retainer ($4–6k/month): office hours, eval review, on-call advisory. Most customers start with a Sprint, upgrade to a Foundation a month later, then settle into a retainer. No pressure — the engagement stands on its own.
Scope your project
Tell me what you want built.
A few sentences is enough. I read every brief myself and reply with a proposed SKU, a price, and the soonest start window. No discovery-deck dance, no qualifying call to qualify the qualifying call.
Or email directly: kevin@mastascusa.com