1. Retrieve
Semantic and keyword search pull candidate passages from allowed collections.
Understand content with trusted AI
Surface answers, summaries, and insights with AI that reads between the lines—and always shows its sources.
WHY IT MATTERS
Answers without evidence create risk.
Unphepha’s Understand layer is built for decision-ready intelligence: grounded retrieval, clear citations, and controls that keep humans in charge.
- Ask natural-language questions across your corpus
- Get summaries with citations back to source passages
- Spot risks, obligations, and themes across document sets
- Keep responses inside your permission boundary
HOW IT WORKS
Retrieval-augmented generation with governance.
Every answer is assembled from content the user can access, ranked for relevance, and presented with provenance.
2. Reason
Models synthesize an answer constrained to retrieved evidence and policy prompts.
3. Cite
Users can open the underlying documents, pages, and snippets immediately.
4. Learn
Follow-up questions stay in context so investigations move faster.
USE CASES
Where Understand creates leverage.
From board packs to vendor reviews, teams use chat and insights to compress hours of reading into minutes.
Executive briefings
Summarize long report sets into decision-ready narratives with links to source evidence.
Risk discovery
Ask what changed, what’s overdue, or which clauses introduce termination risk.
Onboarding accelerators
New hires get trusted answers from current policies instead of outdated slide decks.
Cross-team synthesis
Combine Legal, Finance, and Ops context without forwarding endless email threads.
FAQ
AI trust questions.
How Unphepha keeps Understand responsible and useful.
Can the model invent facts?
Responses are grounded in retrieved content. When evidence is insufficient, Unphepha says so instead of guessing.
Which models do you use?
Deployments can use platform defaults or customer-approved model endpoints depending on your enterprise agreement.
Are prompts and documents used to train public models?
Customer content is not used to train public foundation models. See Security for data handling details.