The team you cannot afford
A controller, an analyst, an admin and someone who understands compliance. Large companies hire all four. Smaller ones run on spreadsheets and hope, and the gap shows up at the worst possible moment.
AIO · Enterprise · Production · internal
Enterprise systems are not hard because accounting is hard. They are hard because the work is buried in hundreds of screens nobody has time to learn. AIO puts an agent in front of that: you say what needs to happen, by text or by voice, and it happens — under a control layer that writes down what it is about to do before it does it.
The four problems every company of this size has, stated without drama.
A controller, an analyst, an admin and someone who understands compliance. Large companies hire all four. Smaller ones run on spreadsheets and hope, and the gap shows up at the worst possible moment.
A supplier turned out to be fraudulent. Someone went around an approval. An audit arrives and asks who authorized a payment. In most systems these are discovered later, from records written after the fact.
The people who can run these systems well cost more every year and are hard to find. Meanwhile competitors automate the same work and quietly lower their cost per order.
Enterprise software is usually capable enough. The problem is that using it requires months of training, so teams use a fraction of it and keep the rest in side spreadsheets.
Real operations on real records — not answers about your data. Left: what a person says. Right: what actually happens in the system.
An agent that can act inside a business is only worth having if what it did can be proven afterwards. That part is deterministic code, not a model.
Facts are gathered, risk is classified, and the reasoning is written to immutable storage before the action runs. A refusal is documented as carefully as a success.
A risky operation stops and shows the amount in words, the document and the reason. The approval applies to those exact facts — if they change, it no longer counts.
A separate process compares the record against what actually changed and flags any disagreement. The component that did the work is not the one that certifies it.
The same gate applies to a person working in the system directly, not only to the agent. In practice the larger risk in an enterprise is not the model — it is an authorized human doing something irreversible without a record of why.
The same agent, different tools behind it. Nobody has to learn a new interface to get an answer.
List pricing for a fifty-person company, as published by each vendor. Voice and long-term memory are counted only where they come with the product, not as an add-on project.
| Approach | Cost, 50 users | Voice | Memory | Records stay yours |
|---|---|---|---|---|
| Large ERP with an AI assistant | High five figures to set up, then per user | Limited | Session only | Vendor cloud |
| Office suite with a copilot | Thousands per month | Text first | Session only | Vendor cloud |
| CRM with a built-in assistant | Thousands per month | CRM scope only | Limited | Vendor cloud |
| Mid-market ERP, self-hosted | Low thousands per month | Add-on | None | Yours |
| Custom development | Six figures, months of work | If specified | If specified | Yours |
| AIO | $999 per month at this size, not per seat | Included | Long-term, per person | Yours, readable directly |
One difference is worth stating plainly: none of the alternatives records why an action was taken before taking it. That is the part we built, and it is the reason this exists as a product rather than as a chat window.
Every tier carries the whole product — voice, memory, knowledge base and the control layer. Tiers differ in volume, never in features, and seats are never billed per person.
One company, five people. 10,000 AI messages, 900 voice minutes, 50 document pages and 30 knowledge-base documents a month, on shared infrastructure.
Three companies, twenty-five people. 30,000 AI messages, 1,800 voice minutes, 500 document pages and 200 knowledge-base documents a month.
Fifteen to twenty-five companies, one to two hundred and fifty people. 150,000 AI messages, 6,000 voice minutes, 5,000 document pages and 2,000 knowledge-base documents a month.
No volume ceilings, a dedicated voice channel and dedicated servers. Moving off an existing ERP, isolated deployment, and integration with the systems you already run.
The parts that exist and run in production. Named plainly, so an engineer on your side can evaluate them.
Routing, extraction, conversation and tool execution are separate nodes, each running on the model that fits that step — so cost and speed are decided per step, not once for everything.
Preferences, facts, summaries and past episodes persist across sessions, isolated per user and per organization.
Each tool runs in its own isolated function behind a single gateway, with permissions granted per tool rather than per system.
A streaming voice channel that reasons and calls the same tools directly, without dropping to text and back in between.
Your documentation indexed for semantic search, so an answer arrives with the passage it came from attached.
Managed guardrails for content moderation, denied topics, personal data detection and prompt injection — applied before a request reaches a tool.
What AIO is not, so nobody discovers it later. This section exists on purpose.
The system of record underneath is ERPNext, an established open-source platform. We built the agent layer and the control layer above it, and your data stays in a database you can read directly.
Nobody is forced through the agent either. Anyone who prefers the ERP screens keeps using them, and the same control layer applies to what they do there.
The control layer runs in production and records every operation. Enforcement is being calibrated against a full reference company before it starts blocking work — so today it observes and documents rather than refuses.
That order is deliberate: a gate that misfires teaches people to route around it, and a gate people route around is worse than no gate at all.
AIO prepares, checks and records. It does not file returns, does not give legal or tax advice, and does not replace the person who is accountable for the decision.
That line matters more as the system gets better, not less. An agent that drafts the filing, reconciles the figures and flags what looks wrong is doing the work — but the approval still carries a name, and the record shows whose it was. Where something needs a licensed professional, the agent says so rather than producing an answer that is confident and wrong.
Automation is welcome to remove the labor here. It is not permitted to blur who answers for the outcome.
Our infrastructure runs in data centers that hold SOC 2 and ISO 27001 certifications. ARE5 itself does not yet hold an audited certification, and we will not imply otherwise — anyone claiming it at this stage is describing their hosting provider.
In practice the platform controls we build on — physical data-center security, encryption in transit and at rest, network isolation — are inherited from that certified infrastructure. The parts that are ours to audit we will certify when it is worth its cost at our size, and we will put a date on it when it happens rather than a promise now.
Memory, documents and retrieved knowledge are isolated per organization, and no shared or general-purpose model is trained on your records.
What your data does build is a dataset that stays yours, in your own storage. That training is not running yet, and when it does it will be under an agreement stating plainly that the dataset and the resulting model belong to you.
Because the system of record is standard ERPNext in a database you control, leaving is not a rebuild. The data exports in open formats, the same ERP keeps running elsewhere, and the agent layer is simply the part you stop paying for — not a hostage you negotiate to get your own records back.
We would rather earn the next month than fence the exit. A product that keeps customers by making departure expensive is admitting it cannot keep them any other way.