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Home/Capabilities/RAG
Capability #09 · Knowledge

Retrieval-Augmented Generation

Enterprise knowledge search, document grounding, vector databases, semantic search and policy-aware retrieval.

Document groundingHybrid retrievalPolicy-awareFreshness
#09
Capability
Knowledge
Category
Live
In production
Day 1
Available
Knowledge

Retrieval-Augmented Generation

Enterprise knowledge search, document grounding, vector databases, semantic search and policy-aware retrieval.

  • Vector + lexical hybrid retrieval
  • Document grounding with citations
  • Semantic search across enterprise corpora
  • Policy-aware, RBAC-respecting retrieval
  • Per-source freshness and provenance
Policy.pdf ANSWER Approved up to $50K… …with two-tier sign-off. [ Policy.pdf p.12 ] [ SOP-2024 §4.3 ]
How it works

Six pillars of Retrieval-Augmented Generation.

Each pillar can be enabled, configured and audited independently.

Document grounding

Citation-anchored answers.

Hybrid retrieval

Vector + lexical for precision.

Policy-aware

RBAC-respecting at retrieval time.

Freshness

Per-source provenance and TTL.

Reranking

Cross-encoder reranking by relevance.

Curation

Owner-managed corpora and policies.

How it works

Grounded answers, policy-aware retrieval.

Every answer cites its sources. Every retrieval respects access rights. No more plausible-but-wrong hallucinations in production.

1

Ingest

Documents, wikis, tickets, contracts, transcripts and structured data are ingested with ACLs, freshness, and provenance preserved.

2

Index

Hybrid vector + keyword + entity index supports semantic, exact-match and structured queries.

3

Retrieve

Each query retrieves only what the requesting role and policy permit. PHI / PII / classification rules enforced at retrieval time.

4

Ground

The reasoning engine cites every retrieved chunk used. Answers without grounding either trigger retrieval or are blocked.

5

Refresh

Source-of-truth changes flow into the index continuously. Stale or contradicted chunks are flagged or retired.

Outcomes

What customers measurably ship with this capability.

Real numbers from production deployments — across banking, healthcare, telco, manufacturing and the public sector.

Policy
-aware retrieval
Citations
Mandatory
Hybrid
Vector + keyword
Freshness
Streaming
Time-to-value

Knowledge as a controlled asset

Your contracts, policies, runbooks and customer history shouldn't leak to every agent. Retrieval is policy-checked the way any other action is.

Risk reduction

No hallucinations to production

Agents that can't ground an answer either go fetch supporting evidence or escalate. They never confidently make things up.

Industry use cases

How RAG & knowledge grounding shows up in production.

Six concrete patterns from regulated enterprises across financial services, healthcare, telecom, public sector, energy and manufacturing.

Banking

Policy-grounded advisory

Customer-care agents cite the exact clause behind every answer about fees, products or compliance.

Insurance

Coverage interpretation

Claims agents cite the exact policy wording supporting any coverage decision.

Healthcare

Evidence-grounded recs

Clinical agents cite the studies, guidelines and formularies behind every recommendation.

Telecom

Knowledge-grounded support

Tier-1 agents cite official KB articles and product docs in every customer response.

Public sector

Statute-grounded determinations

Eligibility decisions cite the statute and case precedent supporting each outcome.

Manufacturing

SOP-grounded operations

Quality and safety agents cite the relevant SOP for every operational instruction.

Why xyner

Open-book LLM vs. policy-aware RAG.

Pasting documents into the prompt is a starting point. Production RAG is governance, freshness and access control.

Dimension
Without xyner
With xyner
Citations
Sometimes
Mandatory, per chunk
Access control
None
Role + policy at retrieval
PHI / PII
Best effort
Tagged + redacted at the right layer
Freshness
Stale by design
Streaming updates, retirements
Hallucinations
Detected late
Blocked at generation
Evaluation
Spot checks
Continuous grounding accuracy
Citation-anchored answers won the policy team over. Our agents quote our actual policy, not paraphrase it.
Director, Compliance · Health System
FAQ

Common questions, straight answers.

Which vector DBs?

xyner native + Pinecone, Weaviate, pgvector, Azure AI Search and OpenSearch.

Can answers cite sources?

Yes — every grounded answer includes citations with policy-aware visibility.

How quickly can we adopt this capability?

Most customers adopt new capabilities in 2-4 weeks through starter packs and onboarding workshops.

Does this require new infrastructure?

No. The capability runs on your existing xyner deployment — cloud, hybrid, on-prem or sovereign.

Do you provide migration help?

Yes — our customer success team and partners deliver guided migrations and pilots.

Get started

Ready to put autonomous agents to work?

See xyner in your environment with a guided executive demo.

Request a demo Contact us
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