FREQUENTLY
ASKED
QUESTIONS

Because no engagement is priced before it is understood. The AI Operations Consultation starts with a free 30-minute fit call, and the paid consultation is scoped and quoted after it. The builds work the same way: final scope, timeline and investment are defined after discovery.

A number invented before discovery is either padded or wrong. After the fit call, discovery and solution research, the proposal states the recommended scope, milestones, assumptions and exclusions alongside the price, so the figure you see is one we can hold to, and you always see it before committing.

Price follows the outcome, scope, system connections, delivery risk and support required. Complex work begins with a paid AI Operations Consultation when more investigation is needed.

After a fit and discovery call, we research the likely approach, dependencies and risks, then send a commercial proposal stating the recommended scope, exclusions, assumptions, milestones, timeline, payment schedule and final price. Nothing is quoted before the delivery risk is understood, because a number given too early is either padded or wrong. Where a consultation comes first, its findings become the scope of the build that follows, so the same investigation is not paid for twice.

Timelines depend on scope, integrations and delivery risk. Most focused AI Operations Consultations take one to three weeks. Website, automation and custom software schedules are defined after discovery so the proposal can include clear milestones, responsibilities and launch criteria.

What moves a date is rarely the build itself: access to third-party systems, content and data, decisions that need several stakeholders, and review time on your side all sit on the critical path, which is why the proposal names who owns each of them. We would rather commit to a date we can hold than a shorter one we cannot, and report progress against milestones instead of vague phases.

Because no engagement is priced before it is understood. The 30-minute fit call is free; paid work is scoped after the call and, for the builds, after discovery. The final figure is written into the proposal with its scope and exclusions, so you always see the price before committing.

Most focused consultations take one to three weeks. For the builds, the timeline is defined with the scope after discovery and stated in the proposal, with milestones, not vague phases.

Ownership, access and handover are defined in the proposal. Clients receive the agreed production assets, documentation and credentials. Third-party services remain subject to their own terms.

After full payment you own the deliverables and source code created uniquely for your business, to the extent the proposal or Client Agreement specifies, including the data, administrator access, agreed repository access and documentation needed to operate the delivered system. We retain our pre-existing and reusable tools, templates, frameworks, assessment methods and general components, and never reuse your confidential data, branding or private business information. For the AI Operations Consultation you own the delivered findings; the underlying methodology and software stay ours.

Yes. Maintenance, support and future improvements are scoped according to the system and the client’s internal capacity.

A team with its own technical people usually wants documentation, access and an agreed response path. A team without one usually wants us to hold the system. Both are legitimate, and the arrangement is written into the proposal rather than left to goodwill. Support covers the system we delivered: monitoring, fixes, dependency and platform updates, and a defined route for changes. Third-party services keep their own terms and fees, and larger changes are scoped as new work, so the cost of running the system stays predictable.

You do: the deliverables and source code created uniquely for your business, after full payment, as specified in the agreement. We keep our reusable tools and methods. Full terms are in the ownership section above.

Ongoing operation, support and improvement arrangements are defined in each proposal, so the level of cover matches the system's importance. We do not disappear at handover, and we also do not lock you in: the documentation and access you receive are enough for another team to operate the system.

We design and build websites, web and mobile applications, operational platforms, integrations and business automation. The format follows the problem, not the other way around.

Projects usually begin with an operational question, enquiries arriving through too many channels, follow-up depending on memory, the same information re-entered by hand between tools, and the build is whatever answers it: a conversion-focused website, an internal application, a connected workflow, or a combination of the three. AI is used where it genuinely improves response, retrieval, document handling or decision support, and conventional software where conventional software is more reliable. What you receive is one working system, not a collection of parts.

No. We use AI when it improves response, retrieval, document handling or decision support. When conventional software is more reliable, we use conventional software.

The restraint is deliberate. An assistant that answers enquiries accurately, a document workflow that removes hours of manual reading, or a decision-support layer over data the business already holds all earn their place. A model added to a problem that a form, a rule or a straightforward integration solves more predictably does not. Discovery establishes which case you are in, and the proposal states plainly where AI is used, what it depends on, and how the system behaves when it is uncertain.

Yes, when those tools support the right system. Discovery determines what should stay, what should connect and what should be replaced.

Most businesses already own more capability than they use, a CRM, a booking tool, a messaging channel, a spreadsheet quietly doing real operational work, and the faster gain is often connecting those properly rather than replacing them. Where a tool is actively holding the workflow back, we say so and price the change instead of building around it. Third-party hosting, APIs and platforms remain governed by their own terms, licences and fees, and material dependencies are disclosed in the proposal.

Yes. When the work can be scoped responsibly from discovery, we go straight to a proposal. The consultation exists for when the right move is not yet clear, especially whether and where AI belongs in the operation. We tell you which case you are in on the first call.

You keep the findings and the recommended order of action, whoever you build with. When the recommendation is a build, the consultation's findings become the build's scope, so nothing is paid for twice. And if AI is not the right answer, we say so and the engagement ends there.

Where it earns its place: assistants, document workflows, retrieval, decision support. Where simpler software is the better answer, we build the simpler software. AI is a capability inside a system, never the reason to build one.

Almost never. Discovery maps what you already run; the packages are built to integrate with existing tools where they work and replace them only where they are the bottleneck.

Yes. Monolit labs is based in Canggu, Bali, and works with businesses across Indonesia, Southeast Asia and beyond. Discovery, design reviews and delivery can be handled remotely, with in-person collaboration arranged when the project requires it.

Our sharpest work is with operationally complex businesses running multiple venues, properties or service lines, where enquiries, qualification, booking and follow-up cross several teams and nothing owns the whole path. That problem looks much the same in Jakarta, Singapore or further out as it does here. Being in Bali matters for on-site work and for knowing this market; it does not decide who we can build for.

We are based in Bali and work across Indonesia, Southeast Asia and beyond. Much of our current work is with premium, operationally complex hospitality operations, because multi-venue businesses are where fragmented enquiries and workflows hurt most, but the packages apply to any business whose operation has outgrown its tools.