Why is the midpoint multiplied by timeline and team, not added?

Mobile app cost scales multiplicatively with timeline and team because both compound. A rush timeline (1 week) does not add a flat fee — it changes how every hour of work is structured: parallel engineers, daily reviews, no-buffer scoping. That structurally increases cost by roughly 50% across the entire build, not just on top of one line item. The same logic applies to team size: an outsourced agency layers project management and account management costs over every hour, not just billed engineering hours.

What counts as a feature for the Denver AI app cost estimator?

A feature is one user-facing capability that ships as a screen plus its supporting backend. Examples: chatbot conversation UI, AI-generated image gallery, voice transcription input, recommendation list, search with semantic ranking. Login, push notifications, settings, and onboarding are not features in this estimator — they are baked into the $5,000 base. A 5-feature app is small-to-medium; 10+ features is enterprise-scale. The estimator caps at 20 features because beyond that, custom architecture cost begins to dominate per-feature cost.

Does the estimate include ongoing AI API costs (OpenAI, Anthropic Claude)?

No. The estimator covers development cost only. Ongoing AI API costs (OpenAI, Anthropic Claude, Google Gemini) are a separate monthly line item. Rough rule: a typical business app with moderate AI usage runs $50-$500 per month at early traction, scaling with conversation volume. Production RAG (Retrieval-Augmented Generation) systems with embedding costs typically run $200-$2,000 per month. If your app is consumer-scale (100k+ monthly active users), expect $5,000-$50,000 per month in API costs. I usually architect for cost monitoring and per-user usage caps so API costs do not surprise you 90 days into launch.

Should I hire solo, build an in-house team, or outsource to an agency in Denver?

Solo (-20% cost) is the right choice when scope is bounded, timeline is 1-6 months, and you have a single decision-maker. The estimator discounts solo because there is no project-management overhead, no hand-off cost, and the same engineer scopes, builds, and ships. In-house team (baseline) is right for ongoing product work where you need 2+ engineers full-time. Outsourced agency (+10%) is right when you want a fixed-bid contract with a known counterparty for a defined project — the +10% is the cost of the agency's project management and sales process. For most Denver business apps, solo is the highest ROI; for VC-funded startups with a 12-month roadmap, in-house team is right; for enterprise IT with procurement requirements, agency is the only option.

Denver AI App Cost Estimator

A defensible budget range for your Denver AI mobile app — built around the same formula I use to scope my own client work. Move the sliders, see the range update live. No email required.

Configure your project

Primary AI use case

Use case is informational here — it scopes the conversation, not the formula.

Feature count: 5

One feature = one user-facing capability (a screen + backend). Login, push, settings, and onboarding are baked into the $5,000 base.

Timeline

Rush (+50%) Standard Relaxed (−5%)

Team

Solo (−20%) In-house team Agency (+10%)

Estimated cost range

$10,500 – $19,500

Midpoint $15,000 · ±30% range

Show breakdown

Base cost $5,000
Features (5 × $2,000) $10,000

Want a real Denver-specific quote?

The estimator gives you a range; a real quote needs a 30-minute scoping conversation. No sales pitch — I either give you a number I will honor, or I tell you why the project does not fit my work.

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Or call 303.324.4953

How the estimator works

The formula is intentionally simple so you can sanity-check it against quotes from other Denver developers. Midpoint cost equals a $5,000 base plus $2,000 per feature, then multiplied by a timeline factor and a team factor:

midpoint = (5,000 + features × 2,000) × timeline × team
range    = midpoint ± 30 %

Multipliers are calibrated against actual Denver AI app projects I have shipped or shadowed: AIBuddy Desktop (custom AI integration), CompassCare (HIPAA-regulated voice + on-device AI), and a dozen client projects from $8,000 chatbot pilots to $80,000 multi-feature production launches. The formula deliberately does not try to be precise — it tries to be defensible: 80%+ of real Denver quotes land inside the ±30% range.

Frequently asked questions

How accurate is the Denver AI App Cost Estimator?

The estimator returns a ±30% range around a midpoint based on four inputs. Real Denver quotes I have shadowed land inside this range 80%+ of the time; the remaining 20% diverge because of regulated-industry overhead (HIPAA, SOC 2), unusual integrations (legacy ERP, hardware), or scope discovered after kickoff. Treat the range as a starting conversation, not a binding quote.

What counts as a feature?

A feature is one user-facing capability that ships as a screen plus its supporting backend. Login, push notifications, settings, and onboarding are baked into the base — they are not features here. The estimator caps at 20 features because beyond that, custom architecture cost begins to dominate per-feature cost.

Does the estimate include ongoing AI API costs?

No. The estimator covers development cost only. Ongoing AI API costs (OpenAI, Anthropic Claude, Google Gemini) are a separate monthly line — typically $50–$500/month at early traction, scaling with usage.

Why multiply, not add, the timeline and team factors?

Both compound. A rush timeline changes how every hour of work is structured (parallel engineers, daily reviews, no-buffer scoping); an outsourced agency layers project management on every billed hour, not just engineering. Multiplication captures that compounding; addition would understate the impact at higher feature counts.

Configure your project

Want a real Denver-specific quote?

How the estimator works

Frequently asked questions

Thomas Woodfin