Questions organisations ask us most.

It depends on what you need, but most engagements involve some combination of a well structured database for your organisation's information, dashboards and reports drawn from that data, tools for collecting data in the field, and sometimes an AI assisted search tool over your own documents. See the Services and Use cases pages for concrete examples.

There is no fixed price list, because every organisation's starting point is different. Engagements are scoped individually after a short conversation about your current systems and what you are trying to achieve. See the Pricing page for how that process works.

It varies with scope, but most builds are broken into staged phases of a few weeks each, so you see something usable early rather than waiting for one long delivery at the end. A short discovery conversation upfront usually gives a realistic timeline for your specific situation.

Less than you might fear, but not nothing. Realistically: someone who can answer questions about how your organisation actually works, access to the data and systems involved, and a decision maker who can say yes or no without a three week wait. The single biggest predictor of a build going badly is not technical, it is nobody internally having time to be involved. If that is your situation right now, it is worth saying so before we start rather than halfway through.

Almost never, and any provider whose first instinct is to replace everything is worth a second look. Most builds connect to what you already run rather than replacing it, so information only has to be entered once and stops being re-keyed between tools. Where something genuinely does need replacing, usually an ageing database nobody can support any more, we would rather say that plainly and show you why than quietly build around it.

Live dashboards of whatever your source data holds: program outcomes, service delivery volumes, participant numbers, financial tracking, or whatever your board and funders ask for. Reports can be generated and emailed automatically on a schedule, so board packs and funder acquittals stop being a manual rebuild every cycle. Alerts can fire when a number crosses a threshold, so problems surface as they happen rather than at the next review. Dashboards can be shared with funders or partners under controlled access, without exposing your underlying systems. The honest constraint is not the dashboard. If an indicator is not being captured properly at the source, no reporting layer can invent it, and sorting that out is usually what discovery is really for.

Usually. If a funder requires a particular template, structure or portal upload, that shape can normally be produced automatically rather than assembled by hand each cycle. Bring an example of what you currently submit to the first conversation, because the format tells us more about what to build than a description of it will.

Yes, and often that is the more valuable half of the work. Plenty of organisations are collecting the wrong things carefully. Defining indicators that reflect what actually matters to your program and your community, rather than importing someone else's framework, is part of discovery. Where a program works directly with community, that process is designed around genuine community input rather than handed down.

Staff fill in forms on a phone or tablet instead of paper. Submissions land directly in your database, so nothing gets transcribed twice or lost between the field and the office. Forms can include photos, GPS coordinates, and logic that skips questions that do not apply. Coverage is handled rather than assumed: where connectivity is poor, forms can be set up to store submissions on the device and sync once a signal is available. How far to take that depends on where your team actually works, which is a discovery question rather than something to over build up front.

Whatever your team already has. Android phones and tablets can run the dedicated offline collection app. iPhones and iPads use offline capable web forms in Safari, which cache the form on first open and store submissions on the device until a connection returns. Either way, staff can work a full day with no signal and sync later. Devices do not need to be new or expensive, and they do not need SIM cards at all if the team syncs over wi-fi when they get back.

Yes, this is a genuine option with our architecture. Instead of calling an external AI provider, an open source language model can run directly on infrastructure your organisation controls, so document content and queries never leave your system. The trade off is a higher hosting cost and somewhat lower raw capability than the largest cloud hosted models. See the AI Knowledge & Search page for the detail.

You do, fully. Every system is built on infrastructure your organisation owns, typically your own AWS account, using open and source-available tools rather than a proprietary product. There is no ongoing subscription required just to keep access to your own data, and no vendor lock in. See the Data Sovereignty page for the detail.

Access is role based, so each person sees only what their role needs, down to individual records where that matters. During a build we need administrative access to your system to do the work. At handover you receive all credentials and can revoke ours entirely, and plenty of clients should. After that, nobody at DataBytes AI can see anything unless you deliberately grant access again for support. Because the system sits in your own cloud account rather than ours, this is something you control rather than something you have to trust us about.

You have options, deliberately. Optional support can be arranged if you want continuity. Or your own team handles it, using the runbooks and training that ship with every build. Or you hand it to another provider entirely, because everything is standard, documented and open. Nothing about the system is designed to make us hard to leave, which is the point.

Sometimes, and it needs care rather than enthusiasm. The technical part is straightforward. The hard part is governance: who can see whose data, who decides that, what happens when a partner leaves. Those questions have to be answered by the organisations involved before anything is built, because a shared system that encodes an unclear agreement is worse than no shared system at all.

Infrastructure is designed against the Australian Cyber Security Centre's Essential Eight, at Maturity Level 1, which is the proportionate baseline for an organisation of this size. That covers things like multi factor authentication, role based access, version controlled infrastructure, regular backups, and production data held in Australia on infrastructure you control. See the Security page for the full picture, including what is not claimed.

Being straight about this: a small practice does not run a 24/7 security operations centre, and we will not pretend otherwise. What you do get is infrastructure defined as version controlled configuration, so a compromised system can be rebuilt from a known good state rather than patched in a panic; regular automated backups; audit logs showing who created, changed or deleted a record; and an agreed response process written down before anything goes wrong. If your funder or regulator requires certified round the clock monitoring, that is a genuine gap in what we offer, and the right answer is a managed security provider alongside us rather than pretending the gap is not there.

DataBytes AI is deliberately lean. That means you deal directly with the person doing the work, with no account managers and no junior staff learning on your project. It also means engagements are built to remove single point of failure risk: every project uses documented, version controlled infrastructure as code, so your systems are never dependent on undocumented knowledge sitting in one person's head. Where a project needs additional capacity, vetted delivery partners are brought in under clear agreements, so you always know who is working on your systems. And because every engagement includes a structured handover and genuine capacity building, you are never more than one document away from being able to run things yourself, with or without us.

Every engagement includes hands on training for your staff, not just a handover document. The aim is for your own team to be able to confidently operate the system, make routine changes, and troubleshoot common issues themselves, with written documentation and runbooks to back that up. Where useful, we help establish an internal data champion as the day to day point of knowledge within your organisation, so capability sits with your team rather than staying locked up with us.

No. Systems are built so that non technical staff can do the day to day work: viewing records, editing them, building and adjusting reports. Training and documentation are part of every engagement for exactly this reason. What helps enormously is one person willing to be the internal point of knowledge, not a developer, just someone curious who becomes the person others ask.

No, DataBytes AI is not an Indigenous owned business. Worth knowing plainly: if a government agency is the direct buyer and Indigenous Procurement Policy thresholds apply to your contract, procurement rules may require an Indigenous owned supplier to be given first right of refusal, and that is worth checking with your agency contact. Outside that specific circumstance, which covers most grant funded community organisations, philanthropic funding and direct engagements, working together is generally straightforward. We are also glad to work alongside, or refer you to, Indigenous owned technology providers where that is the right fit for your organisation's procurement requirements.

Yes. DataBytes AI is based in Canberra but works with organisations across Australia, including remote and regional areas, and engagements are set up to be remote friendly by default.