The Cost Breakdown

Those hours aren't free.
They're costing you a salary.

Move the sliders to your real week. See what those hours actually cost you — at rates anywhere from a VA ($10/hr) to your own time as an owner ($400/hr).

01 — Your Week

29hrs/wk

01
Email & inbox
writing, replying, sorting
8hrs
040 hrs
02
Content & posts
writing, editing, scheduling
10hrs
040 hrs
03
DMs & customer chat
Instagram, Messenger, replies
6hrs
040 hrs
04
Admin & busywork
invoices, scheduling, spreadsheets
5hrs
040 hrs

02 — Your Time Value

$25/hr

Hourly rate

Freelancer

$10VA$25Freelancer$150Pro$400Owner

What it's costing you

Live

29 hrs/week × $25/hr

$37,700

per year in your own time

Per week: $725
Per month: $3,142
Hours / yr: 1,508

One agent costs

$30 – $200/month to run. Pays for itself in week one.

The 12-Week Roadmap

From idea to a live AI product
in 12 weeks. Not 12 months.

A predictable, phase-by-phase sprint that takes your AI MVP from whiteboard to production. Each phase has a clear deliverable, a demo, and a go/no-go gate — so you always know where the project stands.

12
weeks to launch: 6
phased sprints: Fri
weekly demos: 30d
post-launch care

01
Kickoff
Week 0 – 1
Discovery & Strategy
Find the one problem worth solving with AI.
We sit with your team, audit the workflow, and pinpoint where AI actually moves the needle. By the end of week one you have a sharp problem statement, success metrics, and a build-vs-buy decision.
What you get
- 01Stakeholder & workflow interviews
- 02AI opportunity scoring matrix
- 03Success metrics & KPI baseline
- 04Tech feasibility & risk note
02
Sprint
Week 1 – 3
Design & Blueprint
Wireframes, data flow, and an AI architecture you can defend.
Our designers and ML engineers map the user journey, the data pipeline, and the model architecture in parallel. You see clickable flows and a system diagram before a single line of production code is written.
What you get
- 01Clickable Figma prototype
- 02Data pipeline & model architecture
- 03Prompt / model strategy doc
- 04Sprint backlog ready to build
03
Sprint
Week 3 – 6
Core MVP Build
Ship the product shell — auth, UI, APIs, the spine.
We build the application skeleton in production-grade code. Auth, dashboards, integrations, and the API surface go in first so the AI layer has somewhere real to plug into.
What you get
- 01Production-ready frontend & backend
- 02Database, auth, role-based access
- 03CI/CD + staging environment
- 04Weekly demo every Friday
04
Sprint
Week 6 – 8
AI Integration & Training
Plug in the model. Tune it on your data.
We integrate the right model — fine-tuned LLM, custom ML, or a RAG stack — and wire it into the product. Prompts get tested, guardrails go in, evaluations run on real data, not toy examples.
What you get
- 01Model + RAG / agent pipeline
- 02Prompt evals & guardrails
- 03Fine-tuning on your dataset
- 04Latency & cost benchmarks
05
Sprint
Week 8 – 10
Testing & QA
Real users. Real edge cases. Real load.
Functional QA, AI red-teaming, performance and security testing all run in parallel. We don't ship until accuracy hits the bar agreed in week one and the system holds under expected load.
What you get
- 01Manual + automated test coverage
- 02AI red-team & hallucination report
- 03Load + security testing
- 04Acceptance review with stakeholders
06
Sprint
Week 10 – 12
Launch & Handoff
Go live. Monitor. Hand the keys back.
Production deployment, observability dashboards, and a 30-day hyper-care window. Your team gets the runbooks, the model registry, and a roadmap for V2 — not a black box.
What you get
- 01Production deployment & rollback plan
- 02Monitoring + AI observability dashboards
- 03Documentation & team training
- 0430-day post-launch hyper-care