Documentation - Entity Enricher

Documentation

Everything you need to integrate Entity Enricher into your data pipeline.

Getting Started

Get up and running in minutes:

  1. Create an account and set up your organization
  2. Configure your LLM provider API keys
  3. Generate or upload a JSON schema for your entity type
  4. Start enriching entities — individually or in batch
  5. Use the API for programmatic access with organization access keys

Interactive API Docs

Interactive API documentation with request/response examples. Requires authentication.

Swagger UIReDoc

Authentication

The API supports two authentication methods: Bearer JWT tokens for web clients, and API keys (format: ent_XXXX) for programmatic access via the X-API-Key header.Learn more →

Documentation

Getting Started

Quick links, authentication, and Swagger / ReDoc API explorers.

Core Concepts

Schemas, expertise domains, enrichment strategies, and the quality controls that make output reliable.

Enrichment Flow

Step-by-step walkthrough of the enrichment pipeline from input to structured output.

Strategies

Single-pass vs expert-domains vs multi-expertise — when to use each.

Classification

Pre-flight entity-type check that prevents enriching the wrong kind of thing.

Multi-Model Fusion

Field-level conflict detection with rule-based merging or LLM-arbitrated resolution.

Multilingual

Enrich in 40 languages with one portable, database-agnostic JSON format.

Semantic IDs

Stable, org-scoped IDs that dedupe the same entity across enrichments, languages, and time.

Document Attachments

Attach PDFs, images, Office documents and text files to any enrichment job.

Hallucination Prevention

8 defense layers that stop LLMs from fabricating structured data.

Cost Optimization

How prompt caching, schema subsetting, and smart gating keep enrichment cheap.

AI Generation

Generate a JSON schema from natural language or a sample document, with LLM self-correction.

Schema Editor

Visual editor with drag-drop, inline editing, and AI-assisted refinement.

Validation Rules

8 validation rules that catch broken schemas before they reach a model.

Batch Processing

Enrich up to 100 entities in parallel with real-time progress and export.

Playground

Test custom prompts against any AI model with response formatting, token tracking and persistent history.

Records

Browse, filter, and analyze every enrichment result with grouping, search keys, and batch operations.

Cost Dashboard

Real-time cost analytics with time-series charts, performance metrics, and per-model breakdowns.

Organizations & Roles

Multi-tenant management with 4 roles, team invitations, and per-org API keys.

Models & Pricing

LLM model management, automatic pricing sync, health checks, and BYOK support.

Model Benchmarks

Compare models on a saved enrichment scenario — output and cost, side by side.

Benchmark Scoring

How quality scores are computed against a gold reference — equivalence, arrays, sub-scores.

API Keys

Programmatic access via X-API-Key, scopes, and organization access keys.

n8n Connector

Official n8n community node: actions, dynamic dropdowns, and SSE-backed enrichments.

Make.com Connector

Make.com Custom App with 7 first-class modules and dynamic RPC dropdowns.

MCP Server

Embedded Model Context Protocol server for Claude Desktop / Code / Cursor — call enrichments directly from a chat.

Ollama Tunnels

Run local Ollama against the hosted API via reverse WebSocket — no public ports, no SSH.

API Reference

Complete REST API reference with authentication, endpoints, and code examples.

Use Cases

Pharmaceutical

Drug labels, ATC codes, indications, multilingual product info.

Finance

Public-company financials, regulatory filings, structured market data.

Legal & Compliance

Entity due diligence, sanctions screening, contract metadata extraction.

Academic Research

Author profiles, paper metadata, institutional affiliations.

Real Estate

Property data, market comparisons, zoning and regulatory context.

E-commerce

Product catalog enrichment: attributes, categories, compliance, multilingual content.

Compare

vs Clay

How Entity Enricher differs from Clay’s waterfall B2B enrichment.

vs Apollo

How Entity Enricher differs from Apollo / ZoomInfo fixed B2B data.

vs DIY LLM Pipeline

Buy the orchestration vs building it yourself with Instructor, BAML, or LangChain.

vs People Data Labs

Schema-driven multi-model enrichment vs a fixed B2B dataset API.

vs LlamaExtract

Enrich from model knowledge and the web vs extracting structure from documents.

vs Diffbot

Enrich the entities you define vs querying a prebuilt web knowledge graph.

vs Clearbit

Standalone schema-driven enrichment vs HubSpot's Breeze Intelligence credits.

vs Cognism

Any-entity enrichment vs phone-verified EMEA B2B contact data.

vs Explorium

Generated, cross-validated records vs aggregated third-party B2B datasets.

Features

Multi-Model Enrichment

Why running multiple LLMs in parallel beats single-model output.

AI Schema Generation

Generate accurate JSON schemas from natural language descriptions.

Batch Processing

Process hundreds of entities in parallel with real-time status.

Guides

What is Entity Enrichment?

Definition, approaches, and where LLM-based enrichment fits.

MCP Data Enrichment

Use Entity Enricher from claude.ai, Claude Desktop, Claude Code, or Cursor via MCP.

Badge

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