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OptimaFlo AI Roles

Your AI Data Team

These are the jobs that pile up when there is more data work than people. Here is what each AI teammate actually does, what it hands back for you to approve, and where it stops.

Every role

Manager

AI data team Manager: how it plans and delegates work

OptimaFlo's Manager takes a plain-English goal, works out which teammate handles each part, calls them in order, and reports back. What it actually does, what it stops for, and honest limits.

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Ingestion Engineer

AI Ingestion Engineer: how it connects a source, and its limits

OptimaFlo's AI Ingestion Engineer authenticates, browses, and infers schema for a new source conversationally, then hands off a connection the rest of the team can build on. What it does, what needs your OAuth click, and what it can't connect to.

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Data Engineer

AI Data Engineer: what it builds, what it costs, and its limits

OptimaFlo's AI Data Engineer turns a plain-English request into a working pipeline: source context, task breakdown, generated SQL, and a canvas ready to review. What it actually does, what you approve, and honest limits.

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Analytics Engineer

AI Analytics Engineer: SQL generation, validation, and its limits

OptimaFlo's AI Analytics Engineer writes, validates, and revises the SQL behind every model against your real schema, with multi-turn memory so you can undo and try a different approach. What it does, what you approve, and honest limits.

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Analyst

AI Data Analyst: how it answers questions, and its limits

OptimaFlo's AI Analyst matches your question to governed metrics and dimensions when they exist, and checks whether your connected tables can plausibly answer it before it writes SQL. What it actually does, what a person still owns, and honest limits.

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BI Developer

AI BI Developer: how it builds and edits dashboards

OptimaFlo's AI BI Developer turns a prompt into a full dashboard, then edits it live through conversation: add, update, remove, or reorder widgets, each change validated before it applies. What it does, what you approve, and honest limits.

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Quality Engineer

AI Quality Engineer: how it generates data quality checks

OptimaFlo's AI Quality Engineer analyzes schema and patterns, generates checks with a confidence score, and routes low-confidence ones to a person instead of auto-approving everything. What it does, what you approve, and honest limits.

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Frequently asked questions

Manager, Ingestion Engineer, Data Engineer, Analytics Engineer, Analyst, BI Developer, and Quality Engineer. Together they cover a data workflow end to end: connecting sources, building pipelines, writing and validating SQL, answering questions, building dashboards, and watching for bad data.

No. It adds capacity, not judgment. Every role hands its output back for a person to approve: a pipeline before it deploys, a dashboard before it ships, a data quality check before it goes live. AI does most of the work; a person still decides what the numbers mean.

No. Every role is included in Standard, $50,000 a year, with no monthly caps. Cloud compute and your own LLM key bill separately, at cost.

More data work than people? Add AI teammates.

From raw data to live dashboards in one conversation.

Now in early beta. One flat plan, no per-query tax. Runs in your cloud, and your tables stay in your account.