How Much Does Building a Custom App Cost?

Understanding Credits

Everything on the platform runs on credits. One dollar buys 1,000 credits, so each credit costs one tenth of a cent. Every operation your app performs consumes a small number of credits based on what it does. There are no monthly minimums, no per-user fees, and no hidden charges. You only pay for what your app actually uses.

Credits are consumed by three categories of operations: AI model queries, database and platform operations, and communication (email and SMS). Each category has different per-operation costs, which are detailed below.

Building Phase Costs

Building a custom AI app means having a conversation with an AI assistant that writes the application code for you. The cost of this conversation depends on how many messages you exchange and which AI model handles the conversation.

Typical Building Costs

• Simple app (single function, basic CRUD): 50 to 80 credits ($0.05 to $0.08)
• Medium app (multiple commands, scheduled jobs, business logic): 100 to 150 credits ($0.10 to $0.15)
• Complex app (multiple admin pages, integrations, detailed logic): 150 to 200 credits ($0.15 to $0.20)

These costs cover the entire AI conversation, including the initial build and any follow-up modifications. If you later return to add features or fix behavior, each additional conversation round costs the same small amount per message.

Running Phase Costs

After your app is built, it costs credits each time it processes a request, runs a scheduled job, or performs an operation. The exact cost per operation depends on what the operation does.

Database Operations

Reading from or writing to the database costs 1 to 2 credits per operation. This covers the base platform fee for executing the request. Most app commands involve one or two database operations, so a typical API call that reads data, processes it, and writes a result costs 3 to 6 credits in database fees alone.

AI Model Queries

If your app uses AI features (classification, generation, analysis, summarization), each AI query adds cost based on the model used and the amount of text processed:

• Fast, cheap models (GPT-5-nano): 2 to 5 credits per query for short prompts
• Standard models (GPT-4.1-mini, Claude Sonnet): 5 to 20 credits per query
• Advanced models (GPT-5.2, Claude Opus): 20 to 50 credits per query for longer prompts

The actual cost scales with the input and output length. A short classification prompt costs less than a long content generation request. Most practical use cases fall in the 5 to 15 credit range per AI query.

Email and SMS

If your app sends email or SMS messages, each message costs 1 to 5 credits depending on the type and length. Email is at the lower end, SMS at the higher end. These costs are competitive with dedicated email and SMS providers.

Background Jobs

Scheduled jobs (cron tasks) cost the same as regular API calls. A job that reads some data, processes it, and writes results costs the same credits as if that operation were triggered by an API request. The only difference is that jobs run automatically on a schedule instead of waiting for an external trigger.

Real-World Cost Examples

Here are realistic monthly cost estimates for common types of custom apps, based on typical usage patterns.

Simple Tracking App

An app that logs daily entries and lets you view history. About 100 operations per day (mix of reads and writes), no AI features, no email or SMS.

• 100 operations x 3 credits average x 30 days = 9,000 credits
• Monthly cost: about $9

Internal CRM

A customer relationship management tool that tracks contacts, logs interactions, and sends a daily summary report via email. About 500 operations per day plus one daily AI-generated report.

• 500 operations x 3 credits x 30 days = 45,000 credits
• 30 daily AI reports x 15 credits = 450 credits
• 30 daily emails x 2 credits = 60 credits
• Monthly cost: about $15

AI Content Processor

An app that receives incoming content via API, classifies it with AI, stores it in the database, and sends notifications. About 200 items per day, each requiring an AI classification and a notification email.

• 200 items x 3 credits (database) x 30 days = 18,000 credits
• 200 items x 10 credits (AI classification) x 30 days = 60,000 credits
• 200 emails x 2 credits x 30 days = 12,000 credits
• Monthly cost: about $90

Lightweight Automation

An app with a single scheduled job that runs once per hour, checks an external API, and updates a database record. No AI features. 24 operations per day.

• 24 operations x 4 credits x 30 days = 2,880 credits
• Monthly cost: about $3

Comparison to Alternatives

To put these costs in context, here is what the same types of applications would cost with other approaches.

SaaS Subscriptions

Off-the-shelf SaaS tools that handle CRM, project management, or automation typically charge $15 to $150 per user per month. A team of five people using a mid-tier CRM pays $250 to $500 per month. A custom AI app doing the same job for the same team costs $15 to $30 per month regardless of how many people use it, because pricing is based on operations, not seats.

Custom Development

Hiring a developer to build a custom application costs $5,000 to $50,000 upfront, plus $500 to $2,000 per month for hosting and maintenance. Even in the best case, the first year of a custom-built app costs $11,000 or more. A custom AI app with similar functionality costs under $200 for the first year total.

No-Code Platforms

No-code tools like Bubble ($29 to $529/month), Glide ($25 to $249/month), and Adalo ($36 to $200/month) charge flat monthly fees that apply regardless of how much you use them. A custom AI app with light usage might cost $3 to $10 per month, which is a fraction of even the cheapest no-code plan. For heavier usage, custom apps still tend to cost less because you are not paying for a visual editor and hosting infrastructure you may not need.

The Bottom Line

Custom AI apps are the lowest-cost option for backend-heavy applications, automation tools, and internal systems. The credit-based model means you pay proportionally to your actual usage, with no wasted spend on unused capacity. For applications where the front-end experience is the primary value (consumer mobile apps, marketing sites), other approaches may provide better value despite the higher price tag.