Services · Success & ROI

Pick the lever. We'll pull it.

Six service tracks. Every engagement starts with an estimate, ends with a runbook, and includes ROI math you can show your CFO.

🛡️

Strict quality procedure on every build.

Every shipped product passes our 11-gate Quality Control check (build · types · secrets · WCAG 2.1 AA accessibility · backup-readiness · routes · safety · compliance) and meets our backup standard (RPO ≤ 24h, encrypted, off-site, monthly drill). No exceptions.

Full Business AI Integration

8–14 weeks typical

End-to-end AI for any business — small practice to mid-market. We map every workflow that touches a keyboard, replace the slow ones with AI, and wire the results into the systems you already use.

·Workflow audit + ROI scoring across the whole org
·AI feature roadmap with payback math per feature
·4–10 week build with weekly Friday demos
·30-day stabilization + handoff playbook
·Optional: hosted under your tenant or ours

Mock exampleIllustrative · not a real client

Scenario: 15-chair dental clinic, 22 staff, two locations
Pain: 14 hrs/wk on insurance claims posting · 8 hrs/wk on recall calls · denials caught only after 30 days
What we'd build: Claims-posting agent (auto-files to 5 clearinghouses) + recall agent (texts + books) + denial-pattern dashboard
Outcome: Claims time → 90 min/wk · denials caught in 24h · payback in 11 weeks · $58K/yr labor reclaimed

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Custom AI Agents for Busy Founders

4–8 weeks typical

A fully functioning, customizable AI agent built around YOUR daily workflow. Hand off the recurring work — inbox triage, follow-ups, scheduling, research, reporting — and reclaim your calendar.

·Discovery: map your daily + weekly task list
·Custom agent built to your voice, your tools, your rules
·Connects to Slack / Email / Calendar / CRM / DB
·Source available · tenant-isolated · revocable
·14-day post-launch tuning window

Mock exampleIllustrative · not a real client

Scenario: Solo SaaS founder · 50 signups/day · early-stage fundraise active
Pain: 90+ inbox emails/day · missed VC follow-ups · investor updates 2 weeks late
What we'd build: Triage agent that drafts replies in founder voice + calendar agent that books from email + 7am daily summary with priority queue
Outcome: 8 hrs/wk reclaimed · 0 missed VC follow-ups in 6 weeks · investor updates back to weekly

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E-commerce + Website Stores

4–8 weeks typical

Full-functioning e-commerce stores AND marketing websites — built fast, designed sharp, AI-feature-ready. Stripe, inventory, multi-currency, SEO, analytics — all wired on day one.

·Stripe / Shopify / custom checkout — your call
·Product catalog · inventory · multi-currency · tax
·SEO metadata + sitemap + structured data + JSON-LD
·Email capture + abandoned-cart + transactional emails
·Mobile-first · WCAG 2.1 AA · production deploy + SSL

Mock exampleIllustrative · not a real client

Scenario: Boutique jewelry brand · Etsy-only · 600 followers · ~$3K/mo revenue
Pain: Etsy fees eating 18% margin · no email list · zero remarketing · no brand control
What we'd build: Custom Stripe-backed store + abandoned-cart automation + 8 SEO landing pages + AdSense-safe blog seed
Outcome: Launched in 4 weeks · 38% mobile conversion · $14K first month revenue · 1,200-person email list built in 90 days

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App Design + Build

6–12 weeks typical

Web app or product MVP. Auth, payments, dashboards, the boring stuff and the hard stuff. We build for ship date, not perfection.

·Stack: Next.js + Postgres + Stripe by default
·Component library + design system
·User auth + admin panel + billing flows
·Mobile-responsive, accessible (WCAG AA)
·Production deploy + monitoring

Mock exampleIllustrative · not a real client

Scenario: Pre-seed B2B SaaS · 2 founders · burned 6 months with offshore team
Pain: No working MVP after $40K spend · 4 lost design partners while waiting · runway burning
What we'd build: Next.js + Postgres + Stripe MVP w/ auth, role-based admin, billing flows, observability + on-call
Outcome: Live in 9 weeks · 4 paying pilots before launch · pre-seed round closed at month 3

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Hosting Setup (Local · VPS · Cloud)

1–3 weeks typical

You pick the tier, we wire it. From a hardened local box for HIPAA-sensitive ops to multi-region cloud for scale.

·Local: hardened on-prem box w/ backup + monitoring
·VPS: Hetzner / DO / Linode hardened + observability
·Cloud: Vercel / Fly / AWS with IaC
·CI/CD pipeline + rollback procedure
·Documented runbook for handoff

Mock exampleIllustrative · not a real client

Scenario: Solo therapist private practice · HIPAA-sensitive · 2,400 patient records
Pain: Cloud SaaS won’t sign BAA at small-practice price · existing setup unencrypted backups
What we'd build: Hardened local Linux box · encrypted at-rest + LUKS · daily off-site mirror to encrypted S3 · monthly restore drill
Outcome: HIPAA-compliant · $40/mo total run cost (vs $400/mo cloud quote) · 99.9% uptime over 14 months

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Ongoing Support

Monthly retainer

We don’t walk away after handoff. Pick an SLA tier, we stay on the line — patches, monitoring, monthly reviews.

·Tier 1: business-hours email support
·Tier 2: Slack + 24h response SLA
·Tier 3: on-call + 4h response SLA
·Monthly review with ROI + roadmap
·Quarterly stack security audit

Mock exampleIllustrative · not a real client

Scenario: B2B SaaS post-launch · 8 months in · Tier 2 retainer (Slack + 24h SLA)
Pain: Previous dev ghosted post-launch · 3 outages went unresolved · zero security review
What we'd build: 24h Slack SLA · monthly ROI + roadmap review · quarterly security audit + dependency upgrades
Outcome: 99.7% uptime over 8 months · 3 minor incidents each resolved < 4h · 14 features shipped in monthly cadence

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Team AI Training

Coming soon

Hands-on workshops in different AI models — Claude, GPT, Gemini, custom agents — for your whole team. Live exercises, real workflows, your stack.

·Beginner / intermediate / advanced tracks
·Model comparison: Claude · GPT · Gemini · open source
·Hands-on lab: build agents with your real data
·Internal-AI policy + governance templates
·Recorded sessions + reference workbook

Mock exampleIllustrative · not a real client

Scenario: Marketing org · 20 people · mixed senior + junior · no current AI policy
Pain: Shadow ChatGPT use · brand voice inconsistency · zero internal best practices
What we'd build: 2-day on-site workshop · Claude/GPT/Gemini comparison labs · internal AI policy template · custom agent build session
Outcome: Team launched 4 internal agents in week 3 post-training · brand-voice review time cut 60% · written AI policy adopted

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Content Creation Hub

Coming soon

A unified workspace for AI-assisted content production: blog posts, social, video scripts, ad copy, technical docs. Built for marketing teams that ship daily.

·Multi-model content drafting (Claude · GPT · Gemini)
·Brand-voice memory + style enforcement
·Auto-research from your knowledge base
·Approval workflows + scheduled publishing
·Performance analytics tied back to drafts

Mock exampleIllustrative · not a real client

Scenario: In-house marketing team · 6 people · 40 pieces/week target across blog, social, ads
Pain: Drafting bottleneck at senior writers · review cycles eating 3 days · brand voice drift across drafts
What we'd build: Brand-voice memory layer · multi-model drafting (Claude/GPT/Gemini) · 2-stage approval workflow · scheduled publishing tied to analytics
Outcome: 3x weekly output (40 → 120 pieces) · review time cut 60% · brand-voice drift flagged automatically

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Numbers, not pitches. Send a brief.

Tell us what hurts and we'll come back with three tiered options + payback math in 1–2 business days.

Request an estimate →Talk first