The model and its interface
Voice conversation, images analyzed and generated, web browsing, long research, data analysis, apps inside the chat. That is a catalog we are not going to match and are not going to try to.
Comparison
Ofivia vs ChatGPT
As a general artificial intelligence interface, ChatGPT is better and your team probably already pays for it. The difference is elsewhere: it does not hold your company’s files, it does not know your org chart, and it will not tell you what each area spent.
- The agent works inside your folder
- Its memory is a file you own
- Usage metered per company
Start here
What ChatGPT does better
We are not competing for the same job. Four things ChatGPT does better, and for three of them our recommendation is that you keep using it.
Starting in a minute
Anyone opens an account and is working. In Ofivia the account is provisioned by a person on our side after you sign up, because there is no automatic onboarding, and that is hours rather than seconds.
Everything that is not your company
Drafting a difficult email, translating, summarizing a one-off PDF, writing code, understanding somebody else’s contract, thinking out loud. ChatGPT is the right tool for that and Ofivia adds nothing.
Connectors to what you already use
Its business plans read from repositories and tools your team already has. Ofivia has no connectors at all: documents get in because somebody uploads them. That is a real limitation, not a posture.
Side by side
The table, without the tricks
The honest comparison is not feature against feature, it is what happens when the question depends on a document inside your company.
Of 12 rows, ChatGPT wins 3.
| Aspect | Ofivia | ChatGPT | Edge |
|---|---|---|---|
| Where your documents are | In your company’s folder on the server, in standard Markdown | On your computer, or in whichever repository you connect | Ofivia |
| What the AI reads without you pasting anything | The department folder: main note, memory, open tasks and files | Whatever you attach, or whatever the configured connector reaches | Ofivia |
| What it leaves behind | New files inside your vault, linked to the sources it used | Text in the conversation, which you copy wherever it goes | Ofivia |
| Permissions | A company role plus a per-department role, inherited downward | A workspace with shared projects on the business plans | Ofivia |
| Searching your documentation | Semantic and literal at once, fused, at no cost per query | Depends on the connector and the plan | Ofivia |
| Remembering what you already discussed | A full-text query over your own history, zero credits | The vendor’s memory, inside the product | Even |
| Audit trail | A per-company hash chain over every tool the agent ran | Administration logs on the business plans | Even |
| How it is billed | A monthly plan plus real usage measured in dollars, shared across the company | Per user per month | Even |
| Images, video and voice | No image or video generation. Voice notes are transcribed and indexed | Image generation, image analysis and voice conversation | ChatGPT |
| Connectors to other tools | None. Files are uploaded | Connectors to repositories and work tools | ChatGPT |
| Self-hosting | Yes, on the Enterprise plan, with a one-command install | No. It is a cloud service | Ofivia |
| Security certifications | None. No SOC 2, no ISO 27001, no third-party audit | Holds published certifications | ChatGPT |
The agent lives inside the work, not beside it
The limit In exchange, one department’s agent does not see another’s files. If you need to cross purchase cost with sale price, those documents have to sit in the same department or somebody has to share them.
The practical difference shows in what you have to do before you ask. With a general chat, the preparation is gathering the context: finding the three documents, opening them, copying what matters and pasting it. In Ofivia the agent’s working directory is the department subtree, so it is already inside: it reads the area’s main note, its memory, its open tasks and its files, and it writes back in the same place.
- You watch the work live: every search, every file it opens and every tool it runs
- What it produces stays as a file in the department folder, not as text to be rescued from a chat
- It can run Python in a container with no network, no privileges and a 20 second ceiling, so a calculation is a calculation and not an estimate
- The text box does not lock while it works: you can keep typing
The memory is a file you own, dated and sourced
The limit It is not a magic memory that understands your whole company. It is one file per department, holding what the reviewer judged relevant, and sometimes it has to be corrected by hand.
Every so many turns, a background reviewer writes into the memory section of the department’s main note whatever is worth remembering, with the date and the document it came from, and re-indexes it. It is Markdown, appended, inside your vault. You read it, you correct it, you take it with you.
- The memory is auditable: open the file and see what it learned, when, and from where
- If it learned something wrong, you edit the file and that is that
- Searching past conversations is a full-text query, not a model call, and consumes no credit
- The usage log records the size of the text covered and never its content
A meter per company instead of a subscription per person
The limit The meter informs, it does not brake. Today usage is recorded and displayed but it does not cut off on its own at the budget, and the monthly credit is applied by a person during onboarding. We would rather say it here than on the first invoice.
One chat account per person tells the company nothing about what it cost to sort out the operations documentation this month. Ofivia measures every agent turn in dollars and groups it by day, by process and by model. The Basic plan, at US$80 a month, includes 40,000 credits shared across the whole company, on the order of 210 working conversations at a measured average of US$0.19 per turn.
- Indexing, searching, walking the graph and people talking to each other consume no credit: only the agent’s work does
- Billing is idempotent, so a retry never charges twice
- Every tool the agent runs is hash-chained: deleting or editing one line breaks the chain
- One fixed model for every company, which we update: one less decision for the administrator and one less variable on the invoice
No spin
When NOT to pick Ofivia
If your company is in any of these positions, stay with ChatGPT and save yourself the conversation with us:
You have no documentation to sort out
If the knowledge fits in four people’s heads and there are not ten years of files behind you, Ofivia solves a problem you do not have yet.
What you need is general AI
Images, voice, web browsing, one-off data analysis, writing code. That is ChatGPT’s ground and we are not going to pretend we compete there.
You need connectors today
If the expectation is that the AI reads the mailbox, the shared drive and the corporate chat without anybody uploading anything, we do not do that today.
Your buyer requires certifications
We have no SOC 2, no ISO 27001 and no third-party external audit. We can show you how the isolation is built, but we cannot hand you a certificate.
You want to pay per seat and stop thinking
A usage meter is useful information and it is also one more thing to look at every month. If you would rather have a fixed figure per person, that is a legitimate preference.
Your team is not going to move the files
Ofivia is only useful if the documents go in. If nobody is going to upload the folder or drag the notes across, no product fixes that.
What people ask
Frequently asked questions
The same answers we give on the phone, including the awkward ones.
Do I have to stop using ChatGPT?
No, and you probably should not. They are two tools for two different jobs: one is each person’s general AI interface, the other is the company’s knowledge with permissions and an agent inside it. Most of the companies we talk to will have both.
Which model does Ofivia run underneath?
There is no model picker: the agent always runs on the same model, which we choose and update. That is deliberate, because it is one less decision for the administrator and one less variable in the cost. Exactly what runs underneath we tell you in the sales conversation and it goes in the contract, not on a comparison page that ages.
Are my documents used to train a model?
We train no model on your documents or your conversations, and one company’s content never reaches another: the isolation is in the application, in the database, in the file system and in the graph. What goes out to the model is the text the agent needs to answer the question it was asked at that moment. The log we keep records the size of the text covered and never its content.
What does it really cost per month?
The Basic plan is US$80 a month with 40,000 shared credits, roughly 210 working conversations. Uploading and indexing your entire back catalog spends no credit, searching does not either, and people talking to each other does not either. The full breakdown, with the per-turn price measured on this very system, is in how credits work.
What happens if I run out of credits?
You will see it in the meter and we will tell you. Today the system does not cut the agent’s work off at the budget: it records usage and shows it. An owner can request more credit from that same screen and somebody on our side approves or refuses it, with a note. The automatic cutoff is built and tested but it is not switched on yet, and we would rather put it that way.
Can I install it on my company’s server?
Yes, on the Enterprise plan. The whole platform comes up with one idempotent command that provisions the database, the embedding server, the cache, the graph and the backups. Every service listens on the loopback interface only and is reached through a reverse proxy whose configuration ships with it. The detail is on the security page.
Keep going
Three pages that help you decide
Ofivia vs Notion AI If your company lives in Notion, the real question is not which one has more features. It is where your files end up when you want to leave, and whose permissions the AI is working under when you ask it for something. Five use cases The same mess under five names: law firm, clinic, consultancy, importer and agency. How credits work The per-turn price measured on this very system, and what costs nothing.
Start free. Pay when it earns it.
Starter credit so you can try it against your own real documentation. No card and no sales call. If it works, you pick a plan.
- Starter credit on the house
- No credit card
- Every feature included