Everything you need to evaluate Tavuni honestly.
Start with the product itself. Then the facts an engineer will want, and the answers to the questions buyers ask first.
See it, then read about it.
The live verification
The compiler running on an example operations workbook in your browser. No account; nothing uploaded.
Open itHow it works, step by step
One workbook from formulas to a verified system, with the product’s own output at every step.
Read the walkthroughCompare the alternatives
Where low-code platforms and AI builders are stronger, and where Tavuni is different.
See the comparisonAPI reference
The OpenAPI description of the backend, served by this installation.
Open the referenceCreate an account
Sign up, name an organisation and build its model in the platform.
Get startedTalk to us
About a pilot, a demonstration or a technical evaluation.
Get in touchThe facts, briefly.
| Architecture | A Next.js web tier that holds no database and makes no authorisation decision, in front of a Python (FastAPI) backend that owns every rule. |
|---|---|
| Databases | SQLite or PostgreSQL. The backend test suite runs on both. |
| Compiler | Spreadsheet parts read directly (formulas and stored values), a formula engine with 178 Excel functions, an analyser that proposes record types and relationships, and a deterministic rule runtime. |
| Verification | Two levels: every formula against the workbook's stored value, and the generated system run on records alone. Rounding-midpoint cases reported separately. |
| Tenancy | Organisation context is structural; cross-tenant access answers not found. Customers can have their own address. |
| Identity | Email and password, OIDC and SAML single sign-on, SCIM, multi-factor authentication. |
| Interfaces | REST API with scoped keys, signed webhooks, OAuth 2.0 connectors with PKCE, a credential vault. |
| Testing | Over 3,000 backend tests, unit tests for the compiler packages, and browser tests against a production build. |
Limits that matter to an evaluator are on the About page.
Frequently asked.
Has anyone used Tavuni in production?
Not yet. The product is engineered and tested — over three thousand backend tests on SQLite and PostgreSQL, browser tests against a production build — but no business runs on it today. We are looking for one real process to pilot, and we say so on every page rather than imply otherwise. Talk to us about a pilot.
What if the AI gets something wrong?
The AI never edits your system. It may only propose operations from a fixed vocabulary — add a field, add a rule, add an approval step. Deterministic code validates them, applies them to a copy, runs them against your records and shows you the difference. Publishing is a person’s decision.
When the AI describes your business, every fact is traced to the sentence it came from, and it cannot claim that something was derived by the platform. How the AI is governed.
Can I see what a change will do before it goes live?
Yes. A change arrives as a diff in business terms — “added rule: orders over $10,000 need manager approval” — together with how many of your existing records it affects and what they add up to. Nothing is live until a person approves it as a new version. See the example.
Does it replace my spreadsheet, or sit beside it?
It replaces the spreadsheet as the system people work in, and keeps it as the answer key. Tavuni reads the workbook’s structure and formulas, compiles them into a model and rules, and checks the result against the values the workbook stored. Spreadsheet bugs are reproduced faithfully — the business runs on those numbers today — and that is said out loud, not hidden.
Which spreadsheet functions are supported?
178 of Excel’s roughly 500 functions, covering the lookups, aggregations, conditionals, rounding and dates that operational workbooks rely on. Every import produces a coverage report that names anything unsupported, and an unsupported formula is reported as such — never silently dropped.
Who can see what?
Access is decided by the server, not hidden by the screen. Roles carry explicit actions; record access can be all, own, team or none; individual fields can be restricted and are then never sent to a browser that may not read them. Organisations are isolated structurally, and asking for another organisation’s record answers “not found”. Governance in detail.
What does it cost?
There is no public pricing yet. During the pilot stage we agree terms with each pilot directly — tell us about your process.
Does my data train an AI model, and which provider is used?
The public demonstration sends nothing to any AI service. Inside the platform, AI is switched off until an administrator registers a provider and model for their organisation, with a monthly budget and every call metered. Whether that provider trains on your data is governed by your agreement with that provider — Tavuni does not train models.
See it work on a real workbook, in your browser.
The example operations workbook opens in Tavuni with no account and nothing uploaded. Every number on this site comes from that same pipeline.