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Supaboard
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Supaboard vs Looker

Supaboard vs Looker on price, AI analysts, deep reasoning, generated dashboards, MCP, connectors and accuracy — every figure sourced to Looker's own pages.

Supaboard compared with Looker across seventeen capabilities, from price and AI analysts to alerts, MCP support and answer accuracy, each figure linked to the vendor page it was read from
Price$99/seat/moOr $83 billed annually. Usage credits are in the seatQuotedNo list price. Standard, Enterprise and Embed, each including 10 Standard and 2 Developer userssource, checked
AI nativeYesThe agent is the product, not a panel added to a dashboard toolNoConversational Analytics is Gemini added on top of LookML
AI data analystsYesAgents tuned on your business rules and metric definitions, with the SQL shown beside every answerPartialConversational Analytics answers against a modelled Explore
Deep reasoningYesDeep Dive answers why a number moved and what to do next, not only what it isYesWith the Code Interpreter: forecasting, cohort analysis and driver analysissource, checked
Data apps, AI madeYesLive data apps on your own design system, from a promptPartialExtensions, built by a developer against the Looker API
Dashboards, AI madeYesA live dashboard from a single promptYesThe MCP server exposes tools for creating dashboards and Lookssource, checked
AI workflowsYesOne prompt builds the whole chain: detect, analyse, export and route the resultPartialRules and schedules only; no agent step after the delivery
AlertsYesThreshold and anomaly alerts described in plain English, which analyse the change rather than only announce itYesOn query-based or Look-linked dashboard tiles, set up tile by tilesource, checked
Automated reportingYesScheduled reports written by an agent and delivered as PDF, PowerPoint or ExcelYesScheduled dashboard delivery to email, webhook, an S3 bucket, SFTP or Slacksource, checked
Cross-source data queryYesOne question spanning every connected sourceNoOne connection per model; joins live inside LookML
Python scriptsYesSQL and Python in one editor, over every connected sourceYesWritten by the Code Interpreter: pandas, numpy and scikit-learn are availablesource, checked
Slack, Teams, Claude, ChatGPTYesSlack, Teams, Claude, ChatGPT and CursorPartialClaude and other MCP clients, through the Looker-managed MCP serversource, checked
MCP supportYesIn both directions: we expose one, and we read yoursYesA Looker-managed MCP server over the Conversational Analytics APIsource, checked
Query benchYesSQL and Python with schema-aware autocomplete, and AI edits proposed as a diff you approveYesSQL Runner, alongside LookML development
Context and memory managementYesRulesets, knowledge, dropped files and MCP sources such as NotionYesLookML: strong governance, and a modelling project before the first question
Connectors700+Connectable, 124 of them without talking to us48SQL dialects. Databases and warehouses onlysource, checked
Answer accuracy97.8%On LegendEHR's tuned agent in production, with a confidence score on every answerNoneNo accuracy figure published
Why choose SupaboardConversational Analytics only sees what LookML describes, and data tokens beyond the monthly allowance are billed from 1 October 2026. Supaboard needs no model written and reviewed like code before the first question, and its usage credits are in the seat.

Why choose Supaboard over Looker

Conversational Analytics only sees what LookML describes, and data tokens beyond the monthly allowance are billed from 1 October 2026. Supaboard needs no model written and reviewed like code before the first question, and its usage credits are in the seat.

Read the full guide: Best Looker Alternatives for Modern Analytics in 2026

Supaboard vs Looker, in our own words

Looker's centre of gravity is LookML: metrics defined once, held in version control and reviewed like code. It is also the reason Looker is expensive and slow to stand up — the model has to exist before the first question gets an answer.

The trade Looker asks you to make

Google publishes no list price — Standard, Enterprise and Embed are all "call sales", and each platform includes ten Standard and two Developer users before you add anyone. Behind that, LookML is a modelling language, which means a Looker deployment has a build phase, an owner and a review process. Teams that invest in it get consistency. Teams that do not get an expensive dashboard tool.

Supaboard carries that context beside the agent instead: rules and knowledge you give it in plain language, memory it accumulates from conversations, and verified queries you have blessed and can reuse. A definition is written in a sentence and revised the same way, which is why the first answer arrives in minutes rather than after a modelling project.

Where we are the better fit

  • Time to first answer. About five minutes against a connected source, against a modelling project.
  • Breadth of sources. 700+ connectable, 123 without talking to us. Looker is at its best over a warehouse, and a lot of the questions people actually have live in operational systems that never reach one.
  • Cost predictability at the edges. Looker's Conversational Analytics is billed in data tokens. Each tier includes a monthly allowance — 60M input and 1.2M output on Standard — and beyond it the rate is $3.00 per million input and $20.00 per million output, with overage billing starting 1 October 2026. Ours is in the seat, with no allowance to track.

What to test if you trial both

Take a metric two teams currently disagree about and ask both tools for it. Supaboard returns a number and the SQL behind it, so the derivation is on screen and the disagreement is settleable in the room rather than in a modelling review. Then ask both for forty questions nobody has modelled, and see which one answers them this week.

Frequently asked questions

How does Supaboard keep metric definitions consistent?

Per agent: rules and knowledge written in plain language, memory carried across conversations, and verified queries you have blessed and can reuse. Definitions are written in a sentence and revised the same way, and every data-backed answer shows the SQL it ran.

What does Looker cost?

Google publishes no list price: Standard, Enterprise and Embed are all “call sales”, and each platform includes 10 Standard and 2 Developer users. Supaboard's prices are published — $83 per user per month billed annually, or $208 on Business.

How long does each take to stand up?

Looker's value comes from LookML, which is a modelling project with an owner and a review process. Supaboard's first analysis takes about five minutes against a connected source.

How is conversational AI billed in each?

Looker gives each tier a monthly data-token allowance — 60M input and 1.2M output on Standard — then charges $3.00 per million input and $20.00 per million output, with overage billing from 1 October 2026. Supaboard's usage credits are included in the seat, and Enterprise can route to its own model provider keys.

Can Supaboard run in our own cloud?

Yes, on Enterprise: single-tenant container images in your VPC or data centre, no outbound dependency on Supaboard at runtime, and model traffic going straight from your environment to your chosen provider.

Your data has the answers

Start free trialBook a demo

Supaboard starts at $83 per user per month billed annually, with a 14-day free trial and no credit card. Every plan is per seat with usage credits included, so the fifth question in a session costs nothing. SOC 2 Type II covers every plan; HIPAA BAA: on Enterprise, as an add-on on Business.