VYROX consults, designs and deploys agentic AI, fine-tuned on your own decision framework, with your team holding every approval.
From the team behind VYROX's operational software.
Most software sits at one end or the other. It either gives your people a new screen to type into, or it scripts a system to repeat fixed steps. AutoServa goes in the gap between the two: it reads the case, reasons through it in multiple steps, acts across your systems, and escalates the moment a call needs a person.
Your team keeps the parts that need a person.
Fine-tuned by VYROX AI on your experience, your standards and your decision framework. It reads the case, applies your rules the same way every time, does the work, and shows the evidence behind each call.
The work still happens where it already lives.
They live with the person who has done the job for eleven years. They are why two clerks handle the same invoice differently, why the answer changes when someone is on leave, and why the procedure manual and the real process stopped matching years ago. Automate the steps and you automate the paperwork. Consolidate the decisions and you automate the work.
Rule engines and generic assistants both stop at the same wall.
AutoServa is tuned on the reasoning first, then set loose on the work.
Before AutoServa automates a single case, VYROX AI consolidates the material that makes your answers yours. This is the part that generic AI cannot buy and your competitors cannot copy.
How the work is really done, including the exceptions nobody wrote down. The shortcut your senior clerk takes on a Tuesday close. The supplier you always chase twice. The clause your legal lead never lets through. This is the material that normally walks out of the door with the person who holds it.
The inputs each decision depends on, the thresholds that change the answer, the constraints that cannot be crossed, who has to approve what, and when a case stops being routine and has to go to a human. Written down as an explicit structure, not left as instinct.
Your templates, your standard terms, your accounting treatments, your tolerances, your service levels. AutoServa applies the standard you already publish, so the output is recognisably yours rather than a plausible generic answer.
What you decided last time, and the reasoning that supported it. Every case AutoServa handles becomes searchable precedent, so the hundredth decision is consistent with the first and a new hire inherits a decade of judgement on day one.
Entity names, cost centres, product codes, project references, the internal shorthand your teams actually type. A general model guesses at these. A tuned one reads your documents the way your staff read them.
This is an engineering engagement, not a licence handover. VYROX AI does the consulting, the design work and the fine-tuning, alongside the people who currently do the job. Nothing is automated until the AI can already reach your team's answer on its own.
Read the stage-by-stage breakdownWe sit with the people doing the work and watch a real queue, not a demo. What arrives, what they check, where they hesitate.
The tacit rules come out of heads and into writing, including the ones that contradict the official procedure.
That becomes an explicit decision framework: inputs, thresholds, constraints, approvals, escalation, evidence required.
VYROX AI is trained on your material, your vocabulary and your framework, so the operator reasons in your terms.
AutoServa works the live queue beside your team. Humans keep the release, and disagreements are logged, not overridden.
Every decision carries its evidence: what was read, which rule applied, what threshold was hit, who approved it.
Every correction your team makes feeds back into the framework, so the operator converges on how your business decides.
An AI that only advises is another meeting. AutoServa signs in to the systems your staff use, works the queue, and carries the case to the point where a person signs. Every action is tested against your policy before it lands.
The agent calls the same tools your team already uses: ERP, CRM, accounting, mail, document stores and the browser based portals nobody ever built an integration for. No migration, no rebuild, no new screen to learn.
Approval chains, spending ceilings, access scope, segregation of duties, retention rules and regulatory obligations are checked before an action executes, not discovered in an audit afterwards.
What was read, which rule applied, which threshold was crossed, what precedent it followed and who approved it. Your auditor gets a trail, and your team gets a reason they can argue with.
AutoServa is not built on a single model. We run the operator on the frontier cloud model that fits your workflow, or on open-weight models on a local AI server inside your own infrastructure. Same governance, same evidence trail, wherever it runs.
How we pick a model, and what tuning needs from you
AutoServa is not locked to one vendor. We connect the operator to whichever frontier model reasons best for your workflow, and move it to a new one the moment a better model ships.
For clients who cannot send data off-premise, we deploy open-weight models on a server inside your own building or private cloud, fully air-gapped if your policy requires it.
We start where decisions are repetitive, high volume and reviewable, so the operator's answer can be checked against a standard you already hold. These are the queues clients hand over first.
See the full breakdown by departmentCoding invoices to the right account and cost centre, testing journal entries against your own treatments, and preparing the reconciliation pack overnight with every unmatched line explained.
Read moreReading incoming contracts against your playbook, marking every deviation from your standard terms, and drafting the redline for counsel to accept or reject.
Read moreChecking requisitions against budget, policy and preferred suppliers, and routing the exceptions to the person who actually has the authority to approve them.
Read moreDrafting the first response from your own procedures and precedent, and escalating with the diagnosis already attached when it falls outside the framework.
Read moreRebuilding the recurring pack from source every cycle, reconciling the definitions between systems, and explaining what moved rather than only that it moved.
Read moreWorking the exception queue down, applying the standing rules the team knows by heart, and opening the ticket with the evidence attached.
Read moreNot every workflow is. These are the signals we look for in a first working session, and the ones that tell us to wait. We would rather say wait than deploy onto a queue that is not ready.
Any three of these usually means a queue is worth a decision audit.
Any one of these and we will tell you to fix it first.
Not a platform programme. We take a single queue your team owns, consolidate the decisions behind it, design and deploy the AI onto them, and measure the result against how that queue runs today.
We map how one workflow really decides, and tell you honestly which parts should be automated and which should not.
The agentic AI designed and fine-tuned on that workflow, implemented and running it live, governed by Workflow Guard, with your people holding approval.
Further workflows added as the deployed ones earn trust, each one inheriting the knowledge already consolidated.
If yours is not here, ask it on WhatsApp.
Full FAQ and plain-English AI glossaryAutoServa 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.
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.
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.
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.
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.
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.
Tell us the queue, not the technology. We will come back with what the operator would need to learn before it could run that queue, and which parts of it we would refuse to automate.
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