NewAI Clean ships in v0.4 · auto-detects 14 issue types

Raw data to ready report.
One workspace. No exports.

Free for hobby projects under 10k rowsSOC 2 Type II in flightSQL · Python · DuckDB · Pandas
Revenue QA
Step 01 · import

Import customer_data_raw.csv

CSV

Bring your data in.

Olambus profiles schema, detects issues, and prepares a clean workspace from a single file.

customer_data_raw.csvparsed
transactions_q3.xlsxavailable
nps_responses.jsonavailable
Step 03 · clean

AI Clean plan ready

order_id
category
purchase_date
order_amount
region
A-1024
Electronics
2026-01-14
$2,410
West
A-1025
Home & Kitchen
2026-01-15
$890
South
A-1026
Books
2026-01-17
$164
North
A-1027
Electronics
2026-01-18
$1,240
West
A-1028
Beauty
2026-01-20
$420
East
A-1029
Home & Kitchen
2026-01-21
$1,105
South
Step 04 · analyze

Run SQL analysis

SQLcell · 04⌘ ⏎
-- revenue by category after cleaning
select category, sum(order_amount) as revenue
from clean_orders
where purchase_date >= '2026-01-01'
group by category
order by revenue desc;
Step 05 · visualize

Revenue chart

Revenue by category
Cleaned dataset · last 12 months
Q1Q2Q3Q4Q5Q6Q7
Step 06 · export

Report builder

OLAMBUS REPORTp.02 / 04

Revenue trend, Q1-Q4

Monthly revenue rose 2.8x after cleaning duplicate orders and normalizing category labels.

Insight. Electronics drove 41% of the lift, while Home & Kitchen held the strongest repeat purchase rate.
connected·dataset 8d4281f6
Trusted by analyst teams at fast-moving studios and small businesses
Vector Labs
Fieldnote
Northwind
Crisp Auditing
Almanac
Helix Bio
Platform

Six pieces. One workspace. No round-trips.

Each piece is good enough to live alone — but they're better when they share state, history, and a single keyboard shortcut layer.

customer_data_raw.xlsx✓ 1,017 rows
events_2024_q3.csv✓ 84,210 rows
nps_responses.jsonparsing…
+ drop file
Sheets
S3

Upload anything tabular

CSV, Excel, TSV, JSON, Parquet, Google Sheets, or paste from clipboard. Olambus profiles the shape, types, and issues before you write a line.

Uto import
SQLorPython
-- normalise ids
SELECT regexp_replace(id, '[^0-9]', '')
FROM customers
4 issues fixed · 0 remaining

Clean with SQL or Python

Switch languages mid-flow. DuckDB for joins and aggregates, Pandas for the gnarly stuff, AI Clean for the ten things you’d rather not write.

14 issue detectors built-in

Visualise without leaving

Bars, lines, distributions, small multiples — every chart inherits the active query. Tweak the SQL, the chart redraws.

9 chart types · live preview
Hypothesis · 09 May
Q3 lift is promo-driven, not organic. Check margin per category.
/cell-link → cell 04 · revenue.viz
Daksh · 2 hours ago
Confirmed — promotion ran Aug 14–28.

Notes alongside the work

A margin notebook lives next to every cell. Capture hypotheses, paste a Slack thread, and the notes follow the analysis into the report.

Markdown · /commands
01importcustomer_data_raw.xlsx
02profile18 cols · 4 issues
03cleanregexp_replace · drop_nulls
04analyzegroupby category
05visualizebar · revenue

Audit trail, automatic

Every transform, every cell, every chart — versioned with a hash. Reproduce a number from six weeks ago in two clicks.

Step-level reproducibility
OLAMBUS · p.01
Revenue trend Q1–Q3
OLAMBUS · p.02
Cohort analysis

Reports that explain themselves

One command turns a notebook into a PDF — TOC, charts, captions, and the methodology that produced each number. Branded or plain.

Eto export
How it works

From .xlsx to a stakeholder-ready PDF in four steps.

01

Drop in your data

CSV, Excel, JSON, or paste. Olambus profiles types, ranges, and the 14 most common issues before you touch a key.

audit · 0.8s · 18 cols
02

Clean it your way

SQL for joins, Python for the rest, AI Clean for the boring twelve. Every operation is reversible and recorded.

audit · 4 ops · reversible
03

Find the story

Run analysis cells, swap chart types live, annotate findings inline. Notes follow the cells they describe.

audit · 11 cells · 3 charts
04

Ship the report

One command renders a PDF with TOC, methodology, and a stable URL. Send to stakeholders, archive in your warehouse.

export · pdf · 4 pages
Solutions

Built for the people who actually look at the data.

Data analysts

Stop pasting numbers between four tabs.

Move from raw extract to deliverable in one workspace. SQL for the heavy joins, Python for the unusual reshapes, and a report that already cites the queries that produced each number.

  • DuckDB engine, milliseconds on 10M rows
  • Pandas, NumPy, scikit-learn pre-installed
  • Pinned snapshots for reproducible numbers
ANL
Small business owners

Understand your business without a data team.

Connect your Shopify export, your accountant’s spreadsheet, your POS dump. Ask Olambus ‘why was July down’, and ship the answer to your investor email.

  • AI Clean handles messy headers, mixed dates
  • Plain-language explanations on every chart
  • One-click PDF for board updates
SMB
Accountants

Reconciliation that explains itself.

Roll forward last quarter’s templates, drop in this quarter’s GL extract, and let the audit trail be your work paper. Every adjustment is linked to a source row.

  • Step-level reproducibility for audit
  • Variance analysis with reasons attached
  • PDF deliverables match firm templates
FIN
Founders

Investor updates without a BI consultant.

Pull from Stripe, your CRM, and product analytics into one canvas. Build the cohort chart your board keeps asking about — and reuse it next month.

  • Live data sources, refreshable
  • Templates for monthly investor letters
  • Comments and shared workspaces
FND
Why a single workspace

The four-tool workflow, replaced.

If your current stack is a spreadsheet, a notebook, a charting tool, and a doc — here's what gets simpler.

OlambusExcelTableauNotion + Sheets
Upload mixed messy data (CSV, Excel, JSON)~
SQL + Python in the same notebook~
AI-assisted cleaning~
Visualisations bound to live queries
Inline notes & annotations
Automatic step-level audit trail
One-command PDF report~
Reproducible from row to insight
Pricing

Simple tiers. No row-limits-disguised-as-credits.

All plans include the full keyboard shortcut suite, the audit trail, and unlimited PDF exports.

Hobby

Free
For weekend projects and learning.
  • 3 projects · 10k rows each
  • Local CSV / Excel uploads
  • Community support
  • PDF export with watermark
Choose Hobby
Most popular

Pro

$24 / user / month
For analysts shipping work daily.
  • Unlimited projects · 10M rows
  • SQL · Python · AI Clean
  • Branded PDF exports
  • Comments & shared workspaces
  • Email support
Start a Pro trial

Team

$48 / user / month
For teams with shared data sources.
  • Everything in Pro
  • SSO + SCIM
  • Live warehouse connections
  • Advanced audit & roles
  • Priority support
Choose Team
Field reports

From people who used to keep four tools open.

We replaced a Sheet, a notebook, and a Notion doc with Olambus. The first month I shipped four reports I’d been putting off for a quarter.
AR
Ananya R.
Senior Analyst, Fieldnote
The audit trail is the killer feature. When the CFO asks ‘where did this number come from’, I send a link and walk away.
KM
Karan M.
Finance Lead, Northwind
I’m not technical. I dropped my Shopify export in and Olambus told me my margin story before I knew which question to ask.
PS
Priya S.
Founder, Crisp Coffee
FAQ

Questions, answered.

Didn't see yours? Talk to the team →

Is this a notebook or a BI tool?

Both — and a doc. Olambus is one canvas where the notebook, the chart, and the report share state. The notebook is for transforming data; the chart is for understanding it; the report is for shipping the answer. They’re three views of the same workspace.

What languages and engines run inside?
Where does my data live?
How does the AI Clean feature work?
Can I use my company’s branding on the PDF?
Do you offer SOC 2 / SSO / SCIM?
Early access · May 2026

Stop pasting between tabs.
Start shipping reports.

We're onboarding ~50 teams a week. The waitlist is short for analysts and accountants.