Understand your
documents and policies.
Get evidence-based, reasoning-based answers to your questions about your internal documents and policies with chain-of-memory reasoning.
Trusted by leading startups and Fortune 150 financial institutions
Transparent reasoning you can trust
Unlike black-box vector RAG systems, Outerport provides reasoning for every retrieval, enriching them with context.
- ✓See exactly which parts of your documents were used
- ✓Understand the AI's step-by-step reasoning process
- ✓Verify sources and trace back to original documents
“Is our asset inventory management policies compliant with PCI DSS?”
No. Current asset inventory management tracks make, model, and serial numbers, but lacks explicit tracking of device physical locations, which is required by PCI DSS 9.9.1.
Find mappings across multiple documents
Outerport can handle tasks that don't look like traditional search, such as mapping between security frameworks and finding relevant controls.
- ✓Automatically map between different documents each with hundreds of pages
- ✓Save hundreds of hours of manual document searching
“Find mappings for portable storage device policies”
Flag compliance issues just from policies
Detecting compliance violations in sales calls requires reasoning through complex regulations and context, not just keyword matching.
- ✓Automatically identify regulatory violations from call transcripts
- ✓Provide exact citations and reasoning for each violation for review
- ✓Connect complex regulations to specific parts of conversations
“Find potential violations from this call transcript: [transcript]”
Easy API integration for developers.
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?",
)
Why reasoning-based retrieval?
Beyond Vector Similarity
Vector databases force you to think in terms of nearest neighbors, making complex queries difficult or impossible to express.
10-20x More Efficient
Our intelligent processing makes long context reasoning dramatically more resource efficient than traditional approaches, without sacrificing quality.
Smart Document Processing
Unlike basic Q&A systems, our chain-of-memory approach builds understanding progressively, perfect for complex documents where context matters.
Unlimited Document Length
Process documents of any size while maintaining consistent high quality, unlike traditional LLMs that degrade with length.
How it works
Smart Reading
Like a careful reader, our AI breaks down your document into natural sections, understanding how different parts connect and flow together.
Chain-of-Memory
As it reads, our system builds a chain of memories, remembering important details and making connections across the entire document, just like a human would.
Fact Checking
Every insight is double-checked against your original document, ensuring our AI only provides information that's actually present in your text.
Understanding
This verified memory chain helps our AI understand your entire document as one complete story, making it possible to answer questions that require deep comprehension.
Get access
immediately.
Trusted by financial services and leading research institutions. Built by a team that built AI and GPU systems at NVIDIA, Meta, LinkedIn.
Contact us at: info@outerport.com