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What we keep, and what never reaches us

Your Decision Model is built from your own decisions; other people’s material stays out. Last updated October 15, 2026.

ContentsSearch to publicationNever approveHow we limit exposureWhat we can and cannot promiseWhat we holdCookiesWho holds thisCommon questions
You approve first

No source is submitted until you approve it.

Nobody else’s material

Your decisions publish as cases. Source quotes do not; your AI takes out client and employer names, and you check every case.

Limits

No automated check can tell what an NDA covers. You still review every case.

From search to publication

Each step ends with what avva keeps at that point. Nothing moves on until you approve it.

01

Your AI searches

Inside Claude, ChatGPT, Cursor, or the other AI app you chose, using history and tools it already has.

avva retention: Nothing
02

You approve what gets sent

Every candidate record in full, redacted, saved on your side first and grouped by where it came from. You strike personal, client, NDA, security-sensitive, and unreleased work before any source text reaches avva.

avva retention: Nothing
03

Approved decisions pass through

The approved text passes through Studio MCP and is discarded when that response is written. It is not stored. A short-lived record keeps one anonymous marker per decision, the kind of source each came from (chats, documents, tickets), and counts: how many records you were shown, how many you crossed out, how many carry a reason. Never titles, quotes, or case text.

avva retention: Anonymous markers, up to 7 days
04

A clean draft is handed off

Your decisions stay as cases (the situation, what you decided, and why), plus the criteria and stop rules drawn from them. Your AI took client and employer names out and you checked; source quotes and any private examples used only to check the model are removed on our side.

avva retention: Draft and its go-ahead, up to 7 days
05

You approve and publish

Your AI reads the draft back to you and applies your corrections; the site shows what publishes and asks you to confirm privacy. avva strips private residue again before saving or serving. The markers and the go-ahead to publish are discarded once they have done their job.

avva retention: Published Decision Model
You see every record first, and only what you approve publishesYou see every record firstWhat publishesstrike anything privateyour model · your name
Your own AI does the reading, in your own account, and you cross out anything private before a word is sent. avva stores the finished model, including the cases you approved, and never receives your sources.

Never approve

  • Passwords, tokens, credentials, private keys, or internal URLs
  • Personal data about customers, colleagues, patients, or candidates
  • Client, employer or privileged material: anything your duty of confidentiality or an NDA covers. A case carries your practice, never a recognizable client or matter, de-identified or not.
  • Security incidents, vulnerabilities, or unreleased product details
  • Exact financial, legal, or contractual facts covered by confidentiality

Good source material

  • Professional decisions you own and are allowed to generalize
  • Explanations of why you accepted, rejected, or changed an approach
  • Repeated trade-offs across different, safely approved contexts
  • Generic review patterns with identifying details removed
  • Lessons you would comfortably explain in a public talk

How we limit exposure

Your approval before anything is sent

Your AI must save every candidate record in full on your side and ask before submitting decision text.

Strict draft format

A draft carrying quotes or source locations is refused when your AI hands it over. Your own cases pass.

One-time codes

Eight-character codes are rate-limited, and each one delivers a draft once. It can be pasted again for fifteen minutes in case the page never loaded; after that it stops working. Studio posts it, so no logged URL carries it.

Automated scan

Publishing blocks obvious emails, URLs, credentials, phone numbers, and confidentiality markers.

Your confirmation

You cannot publish, or open a private or workspace model to everyone, without confirming every field is authorized.

Serve-time strip

Every MCP response strips private residue again before it reaches anyone’s AI.

What your AI sends

A proposal your AI sends through MCP, or through a preview compile, is used for that response only and is not stored. The Claude Code plugin’s push hook sends up to 8,000 characters of the diff plus the list of changed files, and whether it ran in CI, under the same rule.

What we can and cannot promise

We can enforce that avva application code does not persist the source material your AI read, and that a published model carries no source quotes and none of the private examples used to check it during extraction.

  • Names. Client and employer names are different: your AI removes them under the extraction rules and you check every case. Our automated scan catches emails, URLs, credentials, phone numbers and confidentiality markings, not names.
  • What publishes. What a published model does carry, deliberately, because it is the product, is your own decisions: the situation, what you decided, and your reason, written in American English from your own records. Approved text still transits the hosting infrastructure while a Studio tool call is processed.
  • The boundary only you know. We cannot tell whether an otherwise ordinary sentence is contractually confidential. Only you know that boundary, which is why you review every case before it publishes.

What we hold

Building in Studio needs no account. Signing in, with Google or an emailed link, is only for publish and ownership.

Sign-in

Two ways in, one account either way: Google, or a one-time link to your work email. Either way we hold:

  • an account id, your email and an email-verified flag;
  • the display name and profile image URL Google returns, if you came in that way;
  • session cookies and encrypted OAuth tokens to keep you signed in;
  • for a link sign-in, a hashed, single-use token that expires in 15 minutes and is deleted when used;
  • against inbox flooding, a count of each link sent, under a keyed one-way hash of the address, for 2 days.

No password is ever set or stored, and there is no first-name / last-name form. Public expert credit is a Studio field you choose; it is not your sign-in profile.

Your expert profile

One profile per account, all of it optional and all of it public by design: a photo, a headline, a short bio, the roles and companies you list, your LinkedIn, and a consultation link if you want one. It is stored once and shown on every model you publish, which is the point. One edit, no republish.

Nothing here is taken from your sign-in: we do not copy your Google name or picture onto a page. Clear a field and it stops appearing; delete the account and the row goes with it. The same privacy scan that gates publication runs on every save, because this text goes on a public page too.

Trying without an account

The trial needs no account and collects no address. What it does count is the same per-caller, per-model, per-day row described under Request counters below, because that is what the daily allowance (40 requests a day, per model) is measured against. When it is spent, your AI is told so and the count resets at 00:00 UTC.

Full access and your connection key

Full access needs an avva account, so the address involved is the one already on it. There is nothing extra to type, and nothing collected here that the account did not already hold. It is stored as a contact on its own: never joined to the key, and never to any request your AI makes.

We send the key to that address so you have it after the tab is closed; that one message is not a mailing list. Announcements are different:

  • a separate, unticked box, kept on its own list;
  • every one of those emails carries a one-press unsubscribe;
  • addresses collected before that box existed are never added to it;
  • Request deletion any time via support@avva.chat; the key keeps working, because the two are not linked;
  • earlier beta addresses that sat on the key record were moved onto this same list and scrubbed off the keys.

The key record itself (avk_…) holds:

  • a hash of the key, and its issue time;
  • the dates it was first used and used again;
  • the days it first asked for a review and asked again, kept twice: for any review, and for only the reviews your AI chose to make (not the push hook’s, not a reference model’s), with the last day the push hook asked for one;
  • each day a key is taken, a one-way hash of the account and date, so a second tab is not counted twice.

Those dates say whether keys get used twice at all, and nothing about what was asked. They go with the key: deleted when you revoke it, and by a daily job once it expires, 90 days after issue.

Organization keys

A key issued on a workspace page records which member it was issued to. That lets an owner end someone’s access when they leave: access ends with membership, whatever the key’s expiry, so a workspace key lasts 365 days, not 90.

Each membership records whether it has used the shelf, a yes and never a date, and the day of its first review until a review on a later day turns it into a second yes. Nothing about what was asked; both go with the membership. Personal keys stay possession-only.

What a workspace holds

Its name, its owner, the addresses the owner invited (typed before those people agree to anything), each member’s role and the date they first joined, and which models the owner allowed to go public, and whether a model’s author asked for that. A removed member’s address is deleted with their membership. The rest goes when the workspace is closed.

Request counters

Every MCP request is counted twice, server side, with no browser involved:

  • once against a daily limit, under a one-way hash of the key, network address, or app sign-in it came from, keyed with a secret only our server holds. That hash is what the limit counts, and it is never stored alongside what it was made from;
  • once against the model, so its owner can see whether anyone used it;
  • and each is counted once a day per kind of app, under the same hash;
  • for an app sign-in with no key, the last day it asked for a review and whether it came back on a later day, under the same hash, deleted 90 days after that day.

From the first of those we show the owner how many distinct sources reached their model. It is a count and only a count, never a list, and a source is a key, a network, or a sign-in rather than a person. Neither counter holds your question, our answer, or your email, and neither is joined to one.

Daily tallies about requests name nobody:

  • answer sizes in four bands per tool and access level;
  • how many requests asked for named cases (never which);
  • refusals by reason;
  • app sign-ins started and finished by vendor, read from the app’s return address;
  • with nobody in them to delete, they are kept until we clear our analytics.

The per-caller rows are deleted by a daily job: the one behind the daily allowance is kept for 90 days, because the owner’s count of sources reads that far back, and the ones behind our flood limits and the once-a-day count of apps for 2 days. The per-model count names no caller and is kept, so an owner can see their model’s history; we delete it on request.

The first time someone with full access uses a published model, we email its owner once to say that it happened. That email carries no key, no network address, no question, and nothing about who you are, which we do not know. What we keep is one marker per model that the email was sent, so it is never sent twice.

Run durations

Studio counts how long the three legs of an extraction take — the sweep, the build, and the publish — as a tally in four coarse buckets, from under fifteen minutes to over ninety.

It keeps the tally only: a count per day, per leg, per bucket, with no start or finish time, no session code, no model, and nothing that joins a duration to a person. It exists so the Source step can state the cost of a run honestly.

Published models

The finished Decision Model, including your own cases, associated with your user id. Source quotes do not publish and are not retained; your AI keeps client and employer names out, and you check every case.

Private and organization models are withheld from every other user and refused to every key but their own. They are not withheld from us: avva’s operator can open any published model from the admin panel, and each read is logged. We email a workspace’s owner:

  • when a model leaves its shelf: which model, never where it went;
  • once each, when the first model a member published arrives and when a member first uses it: which model and how many the shelf holds, never which member.

Tick “Remind me monthly to add decisions” on a public or link-only model and we email you at most once every 30 days: its request count and where its update prompt is. We keep the tick and the last reminder’s date; untick to stop.

What a field request holds

Under the shelf on the experts page you can name a field nobody has published in yet. We keep the email you type, the field and the date, and nothing else: no account, no key and no request your AI makes is joined to it. It is used for one email, when a Decision Model in that field is published, and never for marketing or our announcements.

The row is deleted 365 days after you made the request. Request deletion any time via support@avva.chat; deleting your account deletes it too.

Retention and deletion

Account rows and owned models last until you delete the account or we remove them for abuse or shutdown. Session cookies expire; draft codes, the anonymous markers, and a draft's go-ahead to publish expire within days.

Unpublish stops serving a model, and you can publish it again. Delete erases the model and every earlier version from our storage and cannot be undone. Public addresses stay reserved, so a link never points at someone else. A copy already taken of a public page or an MCP response cannot be recalled.

Measurement and cookies

No advertising, no profiles, no data sold or shared for cross-site tracking.

What runs

One visit counter: Google Analytics 4. Page URL, referrer, coarse device and browser data, and an approximate location derived from your IP. Google truncates that IP on collection, and avva never receives it. It loads from a file on this site, which is what lets the content-security policy keep blocking inline script.

EEA, the UK and Switzerland

Analytics storage is denied by default in those countries: the counter still reports, cookielessly, until you answer the consent question at the bottom of the page. Ignore it and nothing changes — no identifier is stored on your device and Google receives aggregate signals only. Advertising storage is denied everywhere, for everyone.

What the visit counter sees

No session recording of any kind. Studio, the dashboard, company workspaces and the operator panel load no counter when a visit starts on them, and a link to a company’s shelf on the marketplace is reported as /experts, without the company’s name. Reached by a click from a page the counter is already running on, they are recorded by address, like any other page change.

Draft content, decision text, model fields and MCP responses are never sent to the counter. It sees which page loaded and nothing on it. The requests your AI makes over MCP never touch it either: those are server to server, with no browser involved.

The cookies themselves

Signing in sets an HttpOnly session cookie and a CSRF cookie. Outside the EEA, the UK and Switzerland the counter adds _ga. It is not used for advertising, and nothing on the site depends on it. There the legal basis is our legitimate interest in knowing whether the product is used at all. You can refuse below, or with any content blocker.

Who holds this, and how to make us act

Write to this address; a person answers.

Controller and contact

avva is an independent beta run by its founder, who is the controller of the data described here. Write to support@avva.chat. We answer within 30 days.

What you can ask for

A copy of what we hold about you, correction, deletion, restriction, objection to processing based on legitimate interest, and portability where it applies. Account deletion is self-service in the dashboard.

Who processes data for us

Netlify (hosting, functions, storage, and database), Google (sign-in and analytics), and Mailtrap (delivering the emails described above). Netlify and Google operate in the United States; Mailtrap is in the European Union. No one else receives your data, and avva sells nothing to anyone.

Complaints, children, breach

You may complain to the data protection authority where you live or work. avva is not for anyone under 16. If a breach affects your data we notify you and the relevant authority as the law requires. Your sources are never sent to us. The cases you approve are stored: as a draft for up to 7 days, then as your model until you delete it.

Privacy requests: support@avva.chat. Legal terms: Terms of Use.

Common questions

Does connecting more tools give avva access to everything?

No. Your AI app controls tool access. avva receives only decisions your AI proposes and you explicitly approve.

Can I open the raw decisions avva received later?

No. The text as your AI sent it is not stored, so there is no avva archive of it to reopen; what is stored is the model built from it. During extraction your AI is told to save the records on your side, in a file named for that model, like avva-decisions-b2b-pricing.json, so building a second model cannot write over the first. Beside it your AI saves a printout of every record, which you read before you approve.

That file is the only copy that exists, and what your AI builds from when you update the model later; like the printout, it never reaches us. Studio shows what the draft contains before you publish. It has no editor. We do not offer a published-model file to download.

Does avva train a model on my data?

No. avva does not train an LLM. Your own AI does the extraction and your clients’ own AI applies the published Decision Model.

Build your Decision ModelBrowse Decision Models

Professionals’ past decisions, for your AI to check before it answers. Free during beta.

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