Autolake Logo

The Agentic Lakehouse that runs itself.

Autolake automates your entire data lifecycle and runs governed AI on top — all inside your own cloud.

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Good morning,
Alex Johnson
Here's what's happening with your data lake today
Evening Wrap-up

Your data lake ran smoothly today with 42 of 47 tables refreshed across 8 active sources, maintaining a strong 97.8% pipeline success rate and 94.2% data quality score.

Quality

Quality score sits at 94.2% — validation rules are consistently passing across all core oracle-prod and mysql-analytics tables.

Action

Investigate why the email_campaigns pipeline hit rate limit errors twice today and review the API quota.

Pipeline Success
2.1%
94.2%
7-day success rate
Data Sources
8 total
Pipeline Health
93% Healthy
18 unique pipelines · Past 7 days
Data Tables
47
Total Storage
1000.0 GB across all tables

Built by the team behind lakehouses at

Wells Fargo
Ford
Deloitte
Fidelity
Intuit
BNY Mellon
Newscorp
Robert Half
City of San Francisco
Clearing House
Santa Clara County
T. Rowe Price
Wonderful
Engie Impact
SnapLogic
Alameda County
Wells Fargo
Ford
Deloitte
Fidelity
Intuit
BNY Mellon
Newscorp
Robert Half
City of San Francisco
Clearing House
Santa Clara County
T. Rowe Price
Wonderful
Engie Impact
SnapLogic
Alameda County

Enterprise AI doesn't have an AI problem. It has a data problem.

Generic AI fails on enterprise questions because the data underneath is scattered, stale, and ungoverned. Autolake fixes the data first — so the AI on top can be trusted.

01

Grounded answers.

AI answers come from curated, governed datasets — not whatever happened to be lying around.

02

Permission-aware.

The AI sees exactly what each user is allowed to see. Access controls carry through to every answer.

03

In your cloud.

The platform, the data, and the AI all run inside your own AWS account. Nothing leaves it.

Capabilities

A complete lakehouse underneath.

Ingestion to distribution, AI chat to agents, alerts to scheduled reports — the entire data lifecycle runs in one platform, autonomously, inside your AWS account.

Connect

Every source, ingested automatically.

Point Autolake at a source and it handles discovery, cataloging, and loading — no pipelines to write.

  • 250+ connectors for databases, APIs, SaaS, files, and streams
  • Incremental, snapshot, and full loads
  • Self-healing pipelines that retry and recover on their own
Snowflake
Salesforce
MySQL
MongoDB
Kafka
Slack
Oracle
Stripe
BigQuery
ServiceNow
Google Sheets
···
How it works

Set up your data lakehouse in minutes, not months.

A custom build-out takes months and millions. Autolake is six steps from zero to a fully managed, production-ready lakehouse — no pipelines to write.

Define Your Data Lake
01

Define Your Data Lake

Enter your lake name, budget, and team tags. Autolake handles the rest.

Connect Your Sources
02

Connect Your Sources

Pick your database, API, or file source — and start ingesting in clicks.

Curate Your Data
03

Curate Your Data

Transform, mask, and prepare analytics-ready datasets with built-in SCD support.

Distribute Everywhere
04

Distribute Everywhere

Share curated data via REST APIs, BI tools, and AI/ML platforms instantly.

Monitor Everything
05

Monitor Everything

Track usage, cost, and performance from a single built-in dashboard.

AI: Talk to Your Data
06

AI: Talk to Your Data

Ask questions in plain English and get instant answers powered by your curated data lake.

And the depth underneath — everything an enterprise lakehouse needs:

Data quality checksColumn-level maskingData meshTable & column lineageSCD historySchema evolutionPII detectionSelf-healing pipelinesIncremental & snapshot loadsPipeline chainingAuto-scaling computeCost intelligenceAnomaly detectionApproval gatesRole-based access controlFull audit loggingAI-written reports+ much more…
Scale

Built for scale and speed.

250+

Connectors

Pre-built integrations for databases, APIs, SaaS, and more.

<15min

Setup time

From zero to running data pipeline, fully configured.

99.9%

Reliability

Enterprise-grade uptime with automatic error recovery.

30+

Autonomous features

From PII detection to self-healing retries — no babysitting required.

Autoflow

Agents that move work forward.

Autoflow is the agent builder inside Autolake. Describe what you want — an agent assembles the workflow on a visual canvas, wires it to your lake and your apps, and runs it under your rules.

passfail

SQL Server connected

1,000 tables

AI maps schemas

Bulk ingest

parallel pipelines

All loads OK?

Load to lakehouse

curated zone

Notify team

Retry failed tables

Open an issue

Chat model

Source schemas

Naming rules

Describe it. Autoflow builds it.

Tell the built-in agent what you want — it assembles the workflow on a visual canvas, ready to run.

Triggered by your lake and your apps.

Lake events, schedules, and SaaS apps can all start a flow — the same 250+ connectors, now as triggers and actions.

Approvals before anything writes.

Governed by default: flows pause for sign-off at the steps you choose, and every run is audited.

Security

Your cloud is the security boundary.

Autolake deploys into your AWS account and is built entirely on AWS-native services — no third-party tooling, no vendor SaaS in the middle, for the platform or for the AI. Your data, your keys, your audit trail.

Access

Role-based access control

Permissions are enforced at the lake level — and the AI inherits them on every query.

Privacy

Column-level masking

Sensitive fields stay masked for people and AI alike, by policy rather than convention.

Provenance

End-to-end lineage

Every record is traceable from source to answer, so AI output is explainable, not a black box.

Audit

Full audit logging

Every access — human or AI — lands in your audit trail, inside your own account.

100% AWS-native
Industries

Built for how your industry works.

The same autonomous lakehouse, tuned to the compliance frameworks and source systems of your world.

BCBS 239SOXPCI DSSLearn more
Financial Services
Demo

Watch Autolake in action.

See how teams go from raw data to a fully managed lake in under five minutes.

FAQ

Frequently asked questions

Get started

Stop building pipelines. Start asking questions.

See it live on your own sources — a 30-minute walkthrough with a founding engineer. No prep needed.

See pricing
Runs in your AWS account100% AWS-nativeLive in minutes, not months