AI software development cost savings should reach the businesses buying the software. Lower development costs give suppliers room to offer better prices and deliver improvements sooner. After eight years of building for this market, we see a clear opportunity for operators choosing an on-demand platform: expect more useful software for your money.
How AI software development cost savings change the build
AI has changed our estimate of what a small, experienced team can build. For a complete product comparable to BetterTaxi, we now estimate roughly two people, three to five months and $40,000–$60,000. Our earlier estimate was four to six people, at least a year and $150,000–$400,000.
Both estimates cover market research, design and development, including the customer and driver apps, backend and operator console. They reflect our experience of building this kind of product, with geography, scope and team experience shaping the budget.
| Building a comparable complete product | Our earlier estimate | Our current estimate |
|---|---|---|
| Budget in US dollars | $150,000–$400,000 | $40,000–$60,000 |
| Team size | 4–6 people | Roughly 2 experienced people |
| Time, including research and design | At least a year | 3–5 months |
An established supplier can put more effort into improving its product with the team it already has.
For buyers, it is a reason to revisit old assumptions about what software should cost and how long improvements should take. An estimate made several years ago deserves a fresh assessment against the tools and working methods available today.
Lower software development costs should reach buyers
We believe customers should share in these gains. A supplier can pass them on through lower prices, more improvements within the existing subscription, or both. The commercial benefit should be visible in what you receive.
For a taxi operator, the charging model determines how software costs grow with the business. Compare fixed subscription charges with booking- or revenue-linked fees at your expected booking volume and revenue.
Build a monthly comparison covering fixed charges, booking- or revenue-linked fees, external services and support. Repeat it for a growth scenario, including any minimum monthly commitments in both calculations. Ask for a clear breakdown you can use to compare offers. This gives you a useful basis for judging value as your business expands.
Price belongs alongside the work the supplier delivers. Look at how the product has improved during the period you are paying for it. Ask which recurring problems have been addressed and how customer requests influence the next releases.
Faster development makes room for smaller improvements
Over eight years, we have heard many requests from operators that we wanted to address. Some stayed in our backlog because we expected months of development for a relatively small improvement. We prioritised work with a more immediate return.
AI-assisted software development has made some of those requests practical to revisit. That is one of the changes we value most. We can act on more of what customers have been telling us.
A small improvement matters when someone uses it throughout the working day. A dispatcher needs to see active bookings alongside driver availability. A driver needs to read the next trip action on a mounted phone. These everyday needs deserve engineering attention alongside larger features.
Knowing this market helps us decide where that attention belongs. Years of conversations with operators give us context for a request: who encounters the problem, how often it occurs and what would make the work easier. Faster implementation makes that knowledge more useful.
To judge AI-accelerated development as a buyer, look at the supplier's release history. Look for changes that solve problems you recognise in your own operation.
Code stability comes from a disciplined development process
We are happy with the stability of the software we are shipping. AI is part of the engineering process behind it, helping us implement changes, write tests and review code. Experienced engineers set the requirements and take responsibility for the result.
In our workflow, newer models need less redirection than the tools we started with. Given a clear specification, they can carry more of a well-scoped implementation through to completion. That gives engineers more room to focus on design decisions, interactions with existing behaviour and review.
Testing and review are particularly useful places to apply these tools. A payment change needs checks for the relevant outcomes. A trip-flow change needs checks that the driver and dispatcher can complete their work correctly. AI helps produce and examine those checks; engineering judgement determines what they need to cover.
We use AI throughout development, from the specification through to review. Clear requirements and careful verification give the implementation a stronger foundation.
See what BetterSuite has shipped, then try it
Our team has built and supported on-demand software since 2018, first through Ridy and now through BetterSuite. We built today's platform from scratch using what those years taught us. Our product changelog shows the work reaching the product.
Recent driver-app changes include landscape layouts and optional voice answers to ride requests on supported phones. Our driver dashboard redesign article explains the choices behind them. The operator console's Live Board brings active bookings and drivers into one dispatch view.
We make the product available through public demos and a free trial because we want buyers to explore it for themselves. Open the apps, follow the everyday workflows and see how they fit your business. You can do that before booking a sales call.
Frequently asked questions
How much does AI-assisted software development cost?
For a complete product comparable to BetterTaxi, our current estimate is $40,000–$60,000 with roughly two experienced people over three to five months. That includes research, design, customer and driver apps, backend and operator console. The scope and team's experience determine the project budget.
How much faster is AI-accelerated development?
Our estimate for a comparable complete build has moved from at least a year to three to five months. In our ongoing work, newer tools need less redirection and help us revisit improvements we previously deferred. The clearest evidence for a buyer is the useful work a supplier delivers.
Does AI reduce costs more for new projects or existing codebases?
We see value in both. For a new product, AI changes what a small team can plan to build. For an existing product, it helps us act on customer feedback and revisit useful work in the backlog. Buyers benefit from AI software development cost savings through better value and a product that keeps improving.
Explore BetterSuite's live demos and try the workflows your business needs to run.
