How is dataface.ai priced, and why are there no per-seat fees?
An annual platform fee plus execution credits. Users are unlimited, because charging per seat would tax the exact behaviour the product exists to create.
Three tiers, all contract-based, none of them per seat.
Pilot
A time-boxed evaluation of eight to twelve weeks against one governed use case, using your own data. It includes a security and architecture review, sandbox and datasource setup, and success criteria plus conversion terms agreed before it starts.
Business
An annual platform fee with included execution credits. Unlimited users, unlimited governed datasources, workspace and datasource access controls, advanced analytics and API access.
Enterprise
A custom agreement for on-source execution at scale, including the edge runtime, dedicated or VPC or on-premise deployment, SSO, residency terms, and an SLA.
Why unlimited users
The product wins when the fifth analyst stops being a bottleneck for forty other people. Per-seat pricing would put a price on inviting those forty, which is the one behaviour worth encouraging. Consumption is metered instead, through an append-only credit ledger that attributes every model call to the agent that made it, with latency and outcome recorded.
Where this comes from
See it against your own data
A pilot is scoped to one governed use case and time-boxed to eight to twelve weeks, with success criteria agreed before it starts.
Get started freeRelated questions
- What is dataface.ai?dataface.ai is on-source conversational analytics. Ask a question in plain English, and it generates read-only SQL from your schema metadata and runs it on the systems you already own. No warehouse copy, no pipeline.
- How do you run analytics without moving our data?dataface.ai reads your schema and a few example values per column, generates read-only SQL, and executes it on the source system itself. Your tables are never copied: no pipeline, no warehouse copy, no second place to secure.
- What does the LLM actually see from our data?By default the model sees your catalog: table names, column names, types, and a few example values per column. It never receives your tables, and it only sees query results if a user turns on AI analysis.
- How do you stop an AI from writing to or damaging our database?Generated SQL is SELECT-only. INSERT, UPDATE, DELETE and DDL are blocked, queries are parameterized against injection, and every request passes both a workspace gate and a datasource gate.