New · Snowflake-native data readiness pipelines

GenAI-ready data
starts here.

Transform complex unstructured files into clean, structured, secure data ready for AI agents, migrations, and enterprise workflows.

Built for enterprise data teams moving from messy files to AI-ready systems.

Sources
PDFs
Spreadsheets
Contracts
Exports
ReadyLayer Engine
Ingest0
Detect schema1
Validate2
Map columns3
Expand rows4
Load5
Destinations
Snowflake
Databricks
Azure
AI Agents
invoices_q4.xlsxsource
Acme Co.INV-1042$12,300
GlobexINV-1043$4,800
InitechINV-1044$22,150
invoices (Snowflake)structured
customer_nameinvoice_idamount_usd
Acme Co.INV-104212300.00
GlobexINV-10434800.00
InitechINV-104422150.00

Designed for the modern enterprise data stack

SnowflakeDatabricksAzureS3SharePointPostgres
The problem

Your AI is only as good as the data it can use.

Most enterprise data is trapped in unstructured files, inconsistent spreadsheets, legacy exports, and operational documents. Before agents can reason, migrate, automate, or act, the data needs to be cleaned, structured, validated, and connected to the right systems.

Unstructured files slow down AI initiatives

Manual data cleanup does not scale

LLM extraction can hallucinate or drift

Migrations break when source data is messy

Agents need trusted structured context

Product

Convert messy files into structured data pipelines.

ReadyLayer ingests unstructured and semi-structured files, understands their structure, creates clean schemas, validates outputs, and loads ready-to-use data into your warehouse or AI workflows.

File ingestion

Upload PDFs, CSVs, XLSX, contracts, reports, and operational exports.

Schema generation

Automatically create structured, deterministic schemas from source data.

Row-level extraction

Turn each spreadsheet row and file section into a clean structured record.

Validation & traceability

Outputs grounded in source data with clear field-level mapping.

Warehouse delivery

Load directly into Snowflake today — Databricks and Azure coming next.

Agent-ready outputs

Give AI agents clean structured records instead of messy documents.

How it works

From unstructured to AI-ready in four steps.

01

Connect or upload files

Bring in spreadsheets, CSVs, documents, reports, exports, or operational files.

02

Generate structure

ReadyLayer identifies fields, schemas, and row-level structure automatically.

03

Validate & transform

Data is cleaned, normalized, and checked against the source for traceability.

04

Load & activate

Send structured data into Snowflake, Databricks, Azure, or agent workflows.

Use cases

Built for the teams turning enterprise data into action.

AI agent readiness

Prepare the structured context agents need to answer, reason, and act reliably.

Data migrations

Convert messy legacy exports and spreadsheets into clean destination-ready tables.

Document-to-database

Turn contracts, forms, reports, and PDFs into usable structured records.

Spreadsheet automation

Transform inconsistent Excel and CSV files into governed datasets.

Enterprise data onboarding

Standardize incoming files from customers, vendors, and legacy systems.

Operational workflows

Feed downstream automations with reliable, structured records.

Why now

GenAI created the demand. Data readiness is the bottleneck.

Enterprises are racing to deploy AI agents, copilots, and automated workflows. But most internal data is not structured enough, secure enough, or reliable enough to power those systems. The next wave of AI infrastructure will be built around data readiness.

Security

Built for secure enterprise data workflows.

Enterprise AI requires more than extraction. It requires security, access control, traceability, and trustworthy outputs.

Encrypted destination credentials
Per-organization warehouse configurations
Key-pair authentication for Snowflake
No hallucinated columns
Output fields grounded in source data
Audit-friendly structured outputs
Integrations

Designed for your modern data stack.

Start with files. End with structured data in the systems your teams already use.

Available now
Snowflake
Coming next
DatabricksAzureS3Google DriveSharePointBoxPostgresAPIsAI AgentsInternal workflows
Differentiation

Not another document parser.

Others
ReadyLayer
Document parsers extract text.
We create structured, destination-ready data.
LLM wrappers generate answers.
We generate clean records.
Manual migration scripts break.
We create repeatable data readiness pipelines.
Traditional ETL assumes structured sources.
We start where enterprise data actually lives: messy files.

Make your data ready for AI.

Turn unstructured enterprise data into clean structured pipelines for agents, migrations, and analytics.