ds@mcpanalytics.aiA data scientist you can email your data and question to, and get a reliable response. Not AI slop.A data scientist you can email. Not AI slop.
How we build it

Built on your data, checked, and run once more before you see it.

When no analysis in the library fits your question, one is built for it. Your data is profiled, the analysis is written in R and run on your data, code checks the results, a separate pass reads them against your question, a repair step fixes what fails, and the finished analysis is run once more after it is deployed.

Walk the steps ↓ The product overview →

Prebuilt analyses live in the library.

A build, livewhat the build tracker shows
✓ Exploring your data
✓ Computing the core analysis
✓ Checking the analysis against the estimate
▶ Evaluating the analysis…
○ Running it once for real
a failed check goes to the repair stepchecked and tested

The steps, in order

These are the steps a build goes through today, named as the build tracker names them while you watch.

Question + Dataset PROFILE + BRIEF Your data's real values, your estimate's places BUILD + RUN Write the analysis in R, run it on your data CHECK Code checks, then a read against your question fail → repair step → checked again REPORT + DEPLOY Cards laid out, saved RUN ONCE
1

Exploring your data

Profile first

Your dataset’s real values are profiled before any analysis is written, so the work starts from the data you actually have.

2

Your estimate becomes the brief

The places, the questions, the method

The estimate you reviewed sets the brief: each place in the report, the question it must answer, and the method. The estimate’s numbers are not carried over; they are computed again from your data.

3

Computing the core analysis

R, run on your data

An analyst agent maps your columns and writes R that computes a result for every place: a set of named numbers, a table, or per-row data. This is the code that runs again when you run the analysis on new data.

4

Checking the analysis

Code checks

Code confirms the R ran, produced an answer, and holds a result for every place, or records why a place could not be computed.

5

Evaluating the analysis

A separate read

A separate model pass reads a profile of the results against your question and each place’s question, and checks that the numbers agree with each other and with your data.

6

Fixing the analysis

When a check fails

A repair step reads what failed and changes the R, and the result goes through the checks again.

7

Laying out the report

Cards and sentences

Each result is laid into its card and every card is checked against the card format. A plain-English sentence is written under each card from the numbers it holds; a sentence that states a number its card does not hold is removed when the check finds it.

8

Running it once for real

Tested after deploy

The analysis is saved to your account and run end to end once. If that run fails, it goes back to the repair step.

What you keep

A built analysis is yours. It stays in your account as a report and as an analysis you can run again.

report

The report

Cards with their numbers

Each place from your estimate as a card, with its numbers, its chart or table, and the sentence written from those numbers.

method

The method

Named on the page

The method each card used, named, so the report can be cited and checked.

code

The code

On the report

The code behind the report is shown on the report itself.

re-run

Run it again

On new data

Run it again on new data, from your account or from your AI agent.

When a check fails

A failed check is not handed to you. It goes to the repair step, and the repaired analysis goes through the checks again.

1

The check says what failed

A code check records the place and the problem; the evaluation pass writes down its reasoning.

2

The repair step changes the R

It reads what failed and why, and changes the analysis to answer it.

3

Checked again

The repaired analysis runs again and goes back through the same checks.

4

Repairs have a limit

Repairs are limited to two rounds. A build that still fails ends as a failure rather than being delivered, and failed builds are never billed.

Bring a question

Bring a CSV and one question. Review the estimate, watch the build live, and get back an analysis you can cite, share, and run again, charged only if the build succeeds.

Create your analysis →
WHERE NEXT

Where to start

One email with your data and your question. We take it from there.

Cymple

Data Scientist

Send me your data and question, I’ll send you the analytics.

ds@mcpanalytics.aimcpanalytics.ai

Try it on your own data

14 days free.

Answers, analytics and custom analytics. No card, no call, nothing to install.

14 days free. →
mcpanalytics.ai

Send Cymple my data →