Untangle your data with AI.

datathere makes partnerships and integrations simple.
Not simpler. Simple.

Customer Orders CSV
Order #SKUQty
ORD-7802APC-152012
ORD-7803SNG-33004
Product Catalog API 
GET /products/APC-1520

  "sku": "APC-1520",
  "description": "USB-C Cable 2m",
  "weight_kg": 0.12
Regional Pricing XML 
<price sku="APC-1520"
       region="US-West">
  <amount>14.99</amount>
  <currency>USD</currency>
</price>

Ready to map

SKU = SKU SKU = SKU Region = Region
Customer Orders CSV
SKU
Region
Product Catalog API
SKU
Regional Pricing XML
SKU
Region
Validation Results271 passed, 13 failed
95.4%
Passing (271)Failing (13)
Valid Order Format
Matches ORD-0000 pattern
100%ErrorReject
Restricted Product Check
Description excludes restricted terms
98.9%ErrorQuarantine
Price Range Check
unit_price > 0.25 AND unit_price < 3000
99.6%ErrorQuarantine
Weight Within Spec
weight_kg > 0 AND weight_kg < 50
100%ErrorReject
Region Format
Matches XX-XXXXX pattern
96.1%WarningFlag
3
Sources
5
Fields
5
Mapped
100%
Success
Order Number
order_id
100%
Unique purchase order number from ERP system
SKU
sku
100%
Stock keeping unit identifying the product across all sources
Description
description
95%
Product name and spec from catalog, matched by SKU
Unit PriceCurrency
unit_price
91%
Region-specific unit price and currency for the ordered SKU
Quantity
quantity
100%
Number of units ordered per line item

Pipeline Run

Complete
2 min ago Daily at 2:00 PM PST 831 / 844 records
Data Flow
Orders 284 Products 142 Pricing 418 Passed 831 Quarantined (13) Mapped 831 Output 831
Vendor Order Feed JSON 

  "order_id": "ORD-7802",
  "sku": "APC-1520",
  "description": "USB-C Cable 2m",
  "unit_price": 14.99,
  "currency": "USD",
  "quantity": 12
See How It Works
95%+ First-Pass Mapping Accuracy GDPR/CCPA Ready 120M+ Records Processed MCP Ready 15 min to First Partner Connection Enterprise Ready 90%+ Join Discovery Accuracy Multi-Provider AI 95%+ First-Pass Mapping Accuracy GDPR/CCPA Ready 120M+ Records Processed MCP Ready 15 min to First Partner Connection Enterprise Ready 90%+ Join Discovery Accuracy Multi-Provider AI

Connect anything

Partners send data in different formats. datathere handles all of them through the same mapping workflow — including joins across sources with complex expressions.

CSV
JSON
XML
PDF
TXT
API
See how it works →

How it works

Connect

Upload files or connect an API. CSV, JSON, XML, PDF, TXT — handled through the same workflow regardless of format.

Map

AI analyzes field names, data types, and sample values to generate mappings with confidence scores and reasoning. Edit in plain English.

Certify

Review mappings, transformations, joins, and quality rules. Certification validates the configuration and locks it for production.

Run

Trigger manually, on a schedule, on file drop, or via webhook. An 8-phase pipeline processes records with quality enforcement at each step.

Industries

Logistics and supply chain

ERP, WMS, TMS, and carrier data unified across a fragmented system landscape.

See the guide

Financial services

KYC, risk, fraud, and compliance data from external providers, normalized to a canonical schema.

See the guide

Retail and consumer

Supplier catalogs, channel syndication, compliance PDFs, and inventory reconciliation.

See the guide

Manufacturing

Part master data, vendor spec sheets, and procurement consolidation across ERP and PLM.

See the guide

SaaS and technology

Customer data unified across product, CRM, billing, and support. Implementation onboarding without engineering tickets.

See the guide

AI That Shows Its Work

AI generates field mappings, transformations, join conditions, and quality rules. Every suggestion includes a confidence score and the reasoning behind it.

Review. Certify. Run.

Every mapping is editable in plain English. Every transformation is visible before execution. Only certified mappings reach production.

Any Source, One Workflow

CSV, JSON, XML, PDF, and API sources follow the same integration workflow. Join across sources on any condition, including complex expressions.

Data Quality Profiling

datathere profiles your source data and creates quality rules. Run them independently or make them part of your pipeline's run rules.

Production-Grade From the Start

An 8-phase pipeline with scheduled, webhook, and file-drop triggers. Real-time job tracking with phase-level progress. Built as production infrastructure from day one.

Enterprise Without the Wait

SSO via SAML and OIDC. GDPR and CCPA compliance. Audit logging with user attribution. Encryption at rest. Multi-tenancy.

MCP Ready

Integration as a tool in your AI stack

datathere exposes its capabilities through the Model Context Protocol. AI agents and LLM-powered workflows can create mappings, run transformations, and trigger pipeline jobs programmatically.

Integration becomes a capability inside your AI workflows — available wherever your agents operate.

MCP Tool Call
// AI agent creates a mapping
tool: "datathere.create_mapping"
// Parameters
"source": "partner_feed.csv",
"destination": "product_catalog",
"auto_certify": false
// 12 fields mapped, 3 transformations generated
// Awaiting human certification

Why datathere?

AI Data Mapping Tools: An Evaluation Guide

Most AI mapping tools run an agent on every row — and inherit its prompt drift. The alternative: AI builds the mapping once, code runs the rows deterministically.

Read more

ETL vs ELT vs reverse ETL: where each one fits

ETL transforms before loading. ELT loads first and transforms in-warehouse. Reverse ETL pushes warehouse data back to SaaS. Three letters, three architectures.

Read more

Universal Connectors vs Custom Connectors: What Actually Works

Universal connectors handle the documented APIs — Salesforce, NetSuite, Shopify. Custom code handles partner files and shifting APIs. Which to reach for, when.

Read more

Data integration fundamentals

Deterministic vs LLM-based data mapping: configuration-time vs runtime architectures

AI data mapping can place the LLM in the runtime data path or use the model only at configuration time. The two architectures have measurable differences in determinism, model behavior, cost scaling, audit, and data exposure.

Read more

How to handle schema drift in data pipelines

Schema drift is a silent failure mode where source structures change between runs and the downstream system absorbs wrong data without raising an error. Detection methods, response policies, and the operational pattern that catches drift in hours instead of months.

Read more

What is AI data mapping?

AI data mapping uses a model to propose how fields in a source schema correspond to fields in a destination. The category covers three different architectures with sharply different production behavior.

Read more
Featured

iPaaS vs ETL — How the Data Integration Categories Differ and What They Don't Cover

iPaaS connects SaaS apps to known APIs. ETL moves structured database data. The categories overlap in marketing but address different problems in practice.

Read the guide Featured

AI Data Mapping and AI Integrations: The AI-First Approach

AI for the mapping, deterministic code for execution, human review in between. The separation is what makes AI-first integration production-grade.

Read the guide
The barrier to entry for production-grade data integration has never been lower.

Enterprise security, built in

SSO
SAML 2.0 & OIDC
GDPR/CCPA
Data subject requests
Audit Logging
User attribution & export
Encryption
Encryption at rest
Multi-Tenancy
Organization isolation

Start integrating.