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Questions, answered straight.
These are the questions that actually come up, in the order they usually come up.
What is AutoServa?
AutoServa is VYROX's workflow automation service. We consult, design, deploy and implement agentic AI, fine-tuned on how your organisation actually decides, that works between your business and its workflow while your team keeps approval.
Does AutoServa replace our existing software?
No. AutoServa works your existing stack, including ERP, CRM, accounting, mail, document stores and the browser based portals nobody ever built an integration for. There is no migration, no rebuild and no new screen for your staff to learn.
How is this different from a chatbot or a generic AI assistant?
A generic assistant answers from what it read on the internet, in a plausible generic voice. AutoServa is fine-tuned on your own documents, decisions and vocabulary first, so its answer matches the one your team would recognise as the house answer, and it acts inside your systems rather than only replying in a chat window.
How is this different from RPA (robotic process automation) or a rules engine?
RPA repeats a fixed sequence of clicks and breaks the moment a case does not match the script. AutoServa reasons through a case the way a trained staff member would, applies your decision framework rather than a hard-coded path, and can handle a case it has not seen in exactly that shape before.
Which cloud AI providers does AutoServa support?
AutoServa is not locked to one vendor. We connect the operator to frontier models from OpenAI (GPT-5), Anthropic (Claude Sonnet 5 and Claude Opus 5), Google (Gemini 3), Moonshot AI (Kimi K2) and Zhipu AI (GLM-5.2), and move it to a new model the moment a better one ships.
Can AutoServa run entirely on our own local AI server?
Yes. For clients who cannot send data off-premise, we deploy open-weight models, including Qwen3, Meta Llama 4 and Google Gemma 3 for reasoning, on a server inside your own building or private cloud, fully air-gapped if your policy requires it.
Who stays in control of what AutoServa does?
Your team does. Workflow Guard checks approval chains, spending ceilings, access scope, segregation of duties, retention rules and regulatory obligations before any action executes, and nothing irreversible happens without an approval you defined.
What happens when the operator is not sure what to do?
It escalates. The decision framework defines explicitly when a case stops being routine, and the operator hands that case to a person with its reasoning and the relevant precedent attached, rather than guessing or stalling silently.
How long before we see the operator working live?
A decision audit runs two to three weeks. Design and deployment, tuning the operator and running it live beside your team, typically reaches a supervised live run within five to eight weeks of starting, depending on how much of the decision framework already exists in writing.
What does an engagement cost?
Pricing is quoted per engagement, based on the workflow's complexity and volume, not a seat licence. The decision audit is the cheapest way to get a firm number: you will know the shape of the cost before committing to design and deployment.
What do we keep if we stop after the decision audit?
The written decision framework for that workflow, in full: the inputs, thresholds, constraints, approvals and escalation rules we documented together. It is yours whether or not you continue to design and deployment.
Does our data get used to train models for other clients?
No. The operator is tuned specifically on your material and stays inside your infrastructure boundary, cloud connection or local server. It is never pooled with another client's data or used to improve a shared model.
What industries or company sizes does AutoServa fit?
AutoServa fits any organisation with a repetitive, reviewable, decision-heavy workflow, most commonly mid-size to large organisations in finance, legal, procurement, service operations and reporting. The determining factor is the workflow, not the industry label or headcount.
We already use RPA. Does AutoServa replace it?
Usually not. If a scripted bot is reliably handling stable, judgement-free work, leave it running. AutoServa typically takes the exception queue that the bot keeps failing on, which is where your team's time was going anyway. The two run alongside each other.
Who from our side needs to be involved, and for how long?
Four roles: the process owner, the person whose judgement the team actually defers to, an IT or systems lead, and a compliance lead. The first two are the ones that matter most, at roughly two to four hours a week each during the first three weeks. The other two are a few hours in total.
What data do you need from us to tune the operator?
The documents the work already produces, past cases with the decisions your team made on them, your written standards, scoped access to the systems in play, and time with the person who holds the knowledge. Not a clean labelled dataset; the real material, including the awkward cases.
How do you decide which AI model to use?
Per workflow, against six criteria: the reasoning depth the queue needs, how much long-document reading is involved, how fast the answer must arrive, where your policy allows data to go, cost per case at your volume, and how easily the model can later be replaced. We test candidates on your own documents before choosing.
Do we need to buy hardware?
Only if you choose a local deployment because data cannot leave your premises. On a cloud deployment there is no hardware to buy. We size and specify the server with you if local is the right answer for your policy.
What if our process is not documented anywhere?
That is the normal starting point, and writing it down is the first thing the engagement produces. The decision audit exists precisely because most real workflows live in people rather than documents. If nobody can say how a decision is made and nobody will arbitrate, that is an organisational problem we will name rather than paper over.
What happens when the operator gets something wrong?
Anything irreversible sits behind a human approval, so the costliest errors are stopped at the gate. Where something reversible went wrong, it is reversed under the same audit trail, the framework rule that allowed it is corrected rather than the single case, and if one case type keeps producing corrections that type moves back behind human approval until it is handled properly.
Can we switch it off?
Yes, immediately, and your team controls the switch. Pausing the operator returns the queue to exactly how it ran before, because we never remove that path. Nothing about the deployment makes your previous process unavailable.
How do you measure whether it worked?
Against how that queue ran before we arrived. We agree the baseline during the decision audit, usually a mix of throughput, how often a case needed rework, and how often two people would have decided it differently. The comparison is to your own prior numbers, not to an industry benchmark.
What happens after the first workflow is live?
Nothing automatically. Further workflows are added only as the deployed ones earn trust, and each new one is faster to tune because the vocabulary, standards and precedent are already consolidated. Some clients stop at one queue, which is a legitimate outcome.
How does an engagement start?
With a decision audit: two to three weeks mapping how one workflow really decides, with the decision framework written down and yours to keep whether or not you continue.
How do we contact VYROX?
Message us on WhatsApp at +60 19 688 3338. There is no email enquiry channel or contact form; we reply on WhatsApp, usually the same working day.
Still have a question?
Ask it on WhatsApp before you book anything. We answer honestly, including when the answer is that a workflow is not a good fit yet.