Own your data operations. No code. No queues.

Connect your sources. Prepare and reshape. Automate on schedule. Add safeguards. Share the result. One platform — no code, every step visible.

No credit card. Drops to Free if you don’t subscribe — nothing you build gets deleted.

Pipeline (7) Describe your transformation… Export Publish 1. Source FashionRetailer_Jan_And_Feb 2. Conditional Filter where billing_country in (UK, US, FR) 3. Math Function (discounts) / gross_sales 4. Bulk Replace on product_title — AI Spelling Match 5. Extract Text from product_title — left of '-' 6. Send to Dataset Sales_Clean (auto-sync ON) T product_title (72) Count T billing_country (26) Count T product_type (9) Count # product_price Count referrer_source product_type product_title colour product_vendor order_id DirectShirtsWinter Work ShirtBlackSCRT772799627 SocialSweats-HoodsLe Monde HoodieBlackSCRT783775694 DirectSweats-HoodsHerbs HoodieBlackSCRT784002383 SocialOuterwearCord Trim PulloverBlackSCRT755043237 DirectOuterwearCord Trim PulloverOliveSCRT749136019 SearchOuterwearCord Trim PulloverBlackSCRT788269170 DirectT-ShirtsMock Neck LongsleeveKombu GreenSCRT765661904

In production at

The platform

Five steps from messy source to automated, governed output.

01

Connect

Powerful

Your data lives in 12 places. Different formats, different systems, different update schedules.

Bring it all in. Native connectors for the sources teams actually use — databases, cloud warehouses, spreadsheets, APIs. Need something custom? On Enterprise, our team builds it in a week.

Sources Snowflake BigQuery Postgres MySQL S3 Salesforce Drive Sheets Excel REST API SFTP Dropbox Databricks OneDrive Custom ENTERPRISE

02

Prepare

Easy

The analyst who knows the cleanup logic keeps it in their head. When they’re out, nobody can reproduce it.

Every step visible in a pipeline. Click a column and pick an operation, or describe what you need in plain English. Before and after, side by side. The logic lives in the system, not in someone’s memory.

1. Source vendor_master.csv 2. Conditional Filter active = TRUE 3. Bulk Replace AI Spelling Match 4. Send to Dataset Vendors_Clean

03

Automate

Reliable

Monday morning: open laptop, run the same script, email the same report. Every week. By hand.

Set the pipeline to run on a schedule. Daily, hourly, or triggered by an event. No cron jobs. Your Monday-morning report is done before you arrive.

Orchestration — Weekly close Every Monday at 06:00 UTC 06:00 Pull files from SFTP 06:02 Refresh Snowflake views 06:04 Run reconciliation pipeline processing… 06:07 Approval gate — CFO waiting for sign-off 06:?? Send report to leadership

04

Control

Transparent + Secure

The payment file went out with bad data once. Now nobody trusts the automated version.

Approval gates that pause the pipeline until a human signs off. Validation rules that catch bad data mid-run. Audit trails up to 7 years. Nothing moves until it should.

Pipeline paused — awaiting approval Validate row count ≥ 10,000 Reconcile vs. source totals Approval gate Push to payment file CFO sign-off required Sent to approver · 2 mins ago Approve

05

Share

Easy + Powerful

500 stakeholders need the dashboard. Your BI tool charges per seat.

Live dashboards — describe what you want, production-ready in minutes. Dashboard viewers are always free, always unlimited. Every plan, including Free.

EMEA sales — Q1 2026 Live REVENUE £2.41M +12.4% ORDERS 8,712 +5.1% AOV £276 +6.9% Revenue trend (12 weeks)

AI Inside

Use AI for the question. Use Mammoth for the answer that runs every week.

ChatGPT can clean a CSV. Claude can write a transformation. For a one-off question, use them. We would.

But the work that runs your business repeats every week, follows the same format, and pauses until someone signs off. AI in a chat can’t hold that. A platform can — and AI makes the building faster.

AI in a chat
Mammoth (with AI inside)

Everything on the left, plus:

In production

Real teams. Real data. Specific outcomes.

Arla Foods

In production

0 hrs saved/yr

Sales reporting unified across 17 countries. Regional teams generate their own reports — no more central IT bottleneck.

Starbucks

Retail

0 % year-one ROI

53% cost reduction. Store-level teams now self-serve their own reports — no IT tickets, no waiting.

RethinkFirst

Healthcare

0 + hrs saved/mo

Manual data work eliminated. The team got time back for the work that actually moves the needle.

BAT

200+ competing products tracked daily

Bacardi

Trade data unified on shared dashboards

NielsenIQ

Cross-market reporting standardized

Everest Detection

Weekly prep cut from 20 hours to 2

Built for

The people who actually do the work.

When the people closest to the data can act on it directly, the whole organization speeds up — not just the analyst.

The analyst who lives in spreadsheets

You merge vendor reports every Monday. You've built the same pivot table forty times. Mammoth lets you build it once and never think about it again.

The team lead who needs control without bottlenecks

Your team needs independence; compliance needs audit trails. Approval gates, permission layers, version history — without you reviewing every change.

The executive who wants the IT backlog gone

Every data request through IT takes weeks. Mammoth puts the tools in the right hands, with security your IT team can sign off on.

The consultant managing many clients

One platform across engagements. Separate projects per client. Build dashboards they view for free — unlimited viewers on every plan, including Free.

Switching

Replacing something? We've seen it.

Replacing Alteryx

Same-day switch. 15-minute learning curve. Pro includes 10 users at $6,708/year vs. $60K–$100K+ on Alteryx.

Replacing AI chat

Use AI for the question; use Mammoth for the answer that runs every Monday. Or use both — AI runs inside the platform.

Replacing spreadsheets

Excel breaks at a million rows. Mammoth handles a billion. Copilot can't run on a schedule. Mammoth does. Same familiar feel, real scale underneath.