How much does a digital product cost?

It depends on the track. Automations start at $1.5k. Full digital products range from $8k to $18k. The price is locked before we start: no hourly billing, no budget surprises.

What is the minimum project timeline?

Simple automations take 2 weeks. Full digital products take 8 to 12 weeks. We define the timeline during the discovery week and don't change it after.

What is the 90-day warranty?

After delivery, we fix any bug or unexpected behavior at no additional cost for 90 days. That's three times the market average.

How does locked scope work?

Before writing a single line of code, we document exactly what will be delivered. The client approves. From that point on, timeline and price don't change. If scope changes, it's an addendum with new pricing.

What size companies do you work with?

We work with mid-size companies, startups with validated products, and internal teams at large companies. The ideal profile: has a clear process to automate or a validated idea to build.

Can I hire just a one-time automation?

Yes. One-time automations are Track 1: 2 to 4 weeks, locked scope, delivery with documentation. No long-term contract required.

Software house vs in-house dev, RPA, and no-code: when each makes sense

When a company realizes it needs technology to grow, the inevitable question comes up: who builds this? There's no universal answer. Choosing between a software house, in-house dev, RPA, no-code, or a freelancer depends on variables specific to the project and the company's current stage.

This post won't push one option as "the best." It'll give you the right criteria to decide.

Quick comparison table

Option	Upfront cost	Time to delivery	Maintenance	Scale	Best for
In-house dev	High (salary + benefits)	Slow at first	Excellent	High	Core product of the business
Freelancer	Low	Fast	Poor	Low	Simple, one-off tasks
RPA	Medium	Medium	Fragile	Medium	Screen automation on legacy systems
No-code	Low	Very fast	Platform-dependent	Limited	Simple SaaS integrations
Software house	Medium-high	Predictable	Good (with agreement)	High	Projects with defined scope

In-house dev: when it works, when it doesn't

Makes sense when technology is the core product of the business. If you're building a SaaS, a marketplace, or any product where continuous code evolution is the competitive advantage itself, having an internal team is the right path. In-house devs absorb business context over time, which is hard to replicate with external teams.

Doesn't make sense when the project is one-off. Hiring a full-time developer to automate an internal process that takes 6 weeks to build and then requires minimal maintenance is high fixed cost for a problem solvable another way.

Freelancer: when it works, when it doesn't

Makes sense for tasks with very well-defined scope and low complexity: a landing page, a simple API integration, fixes to existing code. The hourly rate can be attractive and delivery is fast when the freelancer is good.

Doesn't make sense when the project has interdependencies, needs architectural decisions, or will evolve after delivery. Freelancers rarely take ownership of maintenance and, without continuity, each new developer starts from scratch on the problem context.

RPA: when it works, when it doesn't

RPA (Robotic Process Automation) simulates human actions on graphical interfaces: clicks buttons, reads screens, fills fields. Tools like UiPath and Automation Anywhere are powerful in this domain.

Makes sense when the legacy system has no API, transaction volume is high, and the interface doesn't change frequently. It's the pragmatic solution for automating what can't be integrated any other way.

Doesn't make sense when the process has complex logic with many exceptions, when the system interface changes frequently (the bot breaks with every screen update), or when the volume doesn't justify enterprise RPA licensing and maintenance costs.

No-code: when it works, when it doesn't

Platforms like Zapier, Make, Bubble, and N8N let you build automations and applications without writing code. Time to delivery is very low for common use cases.

Makes sense for integrations between SaaS tools (CRM, ERP, spreadsheets, email), internal approval workflows, and quick prototypes to validate business hypotheses. If the problem fits the connectors available on the platform, ROI is high.

Doesn't make sense when the data is sensitive (financial data, health data, customer data in regulated markets), when the logic is too complex for the visual builder, or when the company will be held hostage to a third-party platform's pricing and technical limits.

Software house: when it works, when it doesn't

Makes sense when the project has defined scope, the problem is real, and there's willingness to invest in the right solution. Also makes sense when the company can't hire and manage in-house devs right now, but the problem demands a robust technical solution.

Doesn't make sense when the problem isn't clear yet. Hiring a software house with vague scope will generate rework and frustration on both sides.

At Chiarelli Labs

We work with companies that have a concrete problem and are ready to solve it. Our typical client:

Has a process that consumes human time and could be automated or managed by a system
Needs a solution that works in production, not in a demo, and will keep working in 12 months
Doesn't want to be constrained by a no-code platform when volume grows or logic gets more complex
Has enough clarity about the problem to define scope together with the technical team

If you're still mapping the problem, that's fine. Our discovery week exists exactly for this: structuring the problem before writing production code.

And if after reading this post you conclude that Chiarelli Labs isn't the right fit for your moment, there's another post that might help: When it doesn't make sense to hire us.