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Compliance-grade answers from your 1,000 page policies

Highly accurate search that works directly with PDF, Word, Excel, PowerPoint, Webpages, CFRs, and more. Built for legal, risk, compliance, and security teams where accuracy and the chain-of-custody matter.

Trusted by Fortune 500 companies and financial institutions

Enterprise-grade Accuracy

Our agentic search system improves upon vector RAG and naive long context approaches, delivering more accurate and faster retrieval through advanced techniques like KV cache management and chain-of-memory reasoning.

Read a detailed blog post about our tech
Benchmark comparison showing superior accuracy

Agentic Retrieval

Outerport uses an LLM-native approach to retrieval instead of using vector embeddings like most RAG systems. Unlike vector RAG, Outerport handles complex queries that need reasoning or comprehensive answers.

Example: "Flag all sections that violate compliance guidelines" can't be expressed as vector similarity.

10-20x More Efficient

Our "KV-cache management" technology makes processing very long documents dramatically more resource efficient than traditional approaches, without sacrificing quality.

Get the same powerful reasoning capabilities at a fraction of the usual cost through optimized memory management. .

Vision-powered Parsing

To handle even the most complex documents, Outerport leverages in-house layout analysis and OCR models to extract information in a structured format.

Designed to run on-premises without the need for internet access or external APIs.

Multi-lingual Support

Outerport can interpret documents in any language, explaining each snippets in the user's language of choice.

Designed for global teams that need to understand regulations and policies in multiple countries.

Easy API integration for customization.

from outerport import OuterportClient

# Initialize with your API key
client = OuterportClient(api_key="...")

# Upload a document
with open("policy.pdf", "rb") as f:
  client.documents.create(file=f)

# Find a document
docs = client.documents.search(query="Policies on information security")

# Ask a question about the document
question = client.questions.create(
    documents=docs,
    question="What restrictions exist on the use of portable storage devices?",
)

# See the evidences
print(question.evidences)
Python
TypeScript

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Trusted by Fortune 500 companies and financial institutions. Built by AI engineers and research scientists from NVIDIA, Meta, LinkedIn,

Contact us at: info@outerport.com

Frequently Asked Questions