Legal & Compliance

Automate Compliance
at Scale

Extract contract clauses, screen regulatory changes, process GDPR subject access requests within the 30-day deadline, and build RAG-powered legal research systems. Every pipeline runs on your infrastructure with full audit trails.

<10ms
p99 latency
4
compliance pipelines
30-day
GDPR SAR deadline met

Legal Pipelines

Four Production-Ready Pipelines

Compliance automation that runs on your infrastructure. Full audit trail, zero data egress.

Contract Clause Extraction

5 nodes

Ingest contract documents, use AI to identify and extract key clauses (indemnification, liability caps, termination rights, non-compete), structure them into a searchable format, and store for downstream compliance review.

file-source prompt-template json-extract field-mapper imap-sink
Clause extraction | Structured output | Audit trail

Regulatory Change Screening

8 nodes · two-stage AI

Monitor regulatory feeds for changes, use a first-pass AI to classify relevance to your business, then a second-pass AI to assess impact severity and generate actionable summaries. Route high-impact changes to compliance teams with full context.

file-source prompt-template json-extract if-relevant
prompt-template json-extract alert-sink & archive-sink
Two-stage AI | Impact assessment | Auto-routing
GDPR

GDPR SAR Processor

5 nodes · Article 15/17

Process Subject Access Requests (Article 15) and Right to Erasure requests (Article 17) automatically. AI identifies personal data across documents, compiles response packages, and flags items requiring manual legal review. Designed to meet the 30-day GDPR response deadline.

file-source prompt-template json-extract if-manual-review imap-sink
GDPR Compliance

Meets the 30-day SAR response deadline (Article 12(3)). AI classifies personal data categories, identifies data controllers, and generates structured response packages. Manual review routing ensures human oversight for edge cases while automating 80%+ of routine requests.

Legal Document RAG

12 nodes

Build a full Retrieval-Augmented Generation pipeline for legal research. Ingest documents, split into semantic chunks, generate embeddings, store in vector database, then answer natural language queries with cited sources. Includes relevance scoring and hallucination guards.

file-source text-splitter llm-embed vector-store imap-sink
query path: file-source llm-embed vector-search prompt-template json-extract imap-sink
RAG pipeline | Vector search | Cited sources

Ready to Automate Compliance?

See these pipelines running live with sample legal documents. Book a 30-minute demo with our team.