Yes. Brilo AI’s Knowledge Base Learning enables Brilo AI to ingest an existing knowledge base and use that content at runtime to improve answer relevance and accuracy. When configured, Brilo AI performs knowledge base ingestion, builds a searchable index, and uses semantic search and retrieval-augmented generation (RAG) to surface precise answers while applying answer-quality controls and human review gates. This process can be scoped by document type, intent, and sensitivity so the Brilo AI voice agent returns safer, more consistent responses. Enablement typically requires a one-time ingestion and periodic updates plus validation by your team.

Can Brilo AI use my company documents as a source?

Yes. Brilo AI can ingest documents and use semantic search to improve answers while enforcing your configured safety rules.

Will Brilo AI automatically change its behavior after ingesting our KB?

Brilo AI can adapt answers using ingested content, but learning is controlled through configured review, testing, and deployed answer-quality rules.

Does Brilo AI merge KB content with live conversation context?

Yes. Brilo AI combines the current call context with retrieved KB content to produce responses using retrieval-augmented generation (RAG).

Buyers ask this because existing documentation and knowledge bases represent a large, trusted source of company answers. Enterprises want to know whether Brilo AI can reuse those assets to reduce manual updates, improve first-call resolution, and keep voice responses consistent with published policies. Procurement, legal, and support teams also want clarity on scope, control, and auditability before allowing an AI voice agent to read or summarize internal documents for customers.

Brilo AI’s Knowledge Base Learning workflow typically follows three stages: ingest, index, and serve. During ingestion, Brilo AI pulls or receives your documents (PDFs, FAQs, KB articles, support scripts) and converts them into a searchable index. At runtime, the Brilo AI voice agent uses semantic search over that index and retrieval-augmented generation (RAG) to construct answers that combine KB content with live call context and intent classification.

Knowledge base ingestion imports and normalizes your documents so the voice agent can search and reference them during calls. Retrieval-augmented generation (RAG) is the runtime pattern where the agent retrieves relevant KB passages and uses them to produce a focused spoken answer.

Key technical terms you’ll see in Brilo AI workflows include knowledge base ingestion, semantic search, vector embeddings, indexing, retrieval-augmented generation (RAG), and intent classification.

Brilo AI applies configurable safety boundaries to Knowledge Base Learning to limit scope and reduce risk. Typical guardrails include restricting which KB folders are ingested, setting document-level sensitivity labels, enforcing citation or read-only behavior, and routing any uncertain or high-risk questions to a human. Brilo AI also supports thresholded answer-quality checks so responses below confidence thresholds trigger a fallback.

The answer quality model is the set of rules and confidence checks that decide when a generated response is acceptable for auto-responding versus when it must be reviewed or escalated.

What Brilo AI will not do by default: autonomously publish KB edits back to your canonical documentation, disclose internal-only PII without a validated workflow, or replace human review for high-risk policy or healthcare decisions unless explicitly configured.

Brilo AI voice agent workflows can hand off to a human agent or another workflow in several ways: immediate transfer (agent takeover), scheduled callback creation, or creating a ticket in your case system. You can configure handoff triggers based on intent, KB confidence score, caller emotion signals, or explicit caller requests. When a handoff occurs, Brilo AI can pass the retrieved KB passages and the call transcript to the receiving agent to shorten resolution time and provide context.

Can Brilo AI ingest any file type?

Brilo AI accepts common document formats for ingestion, but file-type support and preprocessing requirements should be confirmed during onboarding. Large or non-text formats may require conversion or extraction before indexing.

How often will Brilo AI refresh the knowledge base?

Refresh frequency is configurable. You can schedule periodic re-ingestion or trigger updates after you publish a new KB batch. Production schedules should align with your change-management process.

Will Brilo AI expose confidential data from our KB to callers?

Brilo AI will only surface content from the documents you permit during ingestion; apply sensitivity labels and redaction before ingestion. Configure answer-quality and confidence gates to route uncertain or sensitive requests to humans.

Can Brilo AI attribute answers to the original KB article?

Yes—Brilo AI can be configured to cite the source article or present a short reference to help the receiving agent or caller verify the response, subject to your citation policy.

Does Knowledge Base Learning replace human training?

No. Knowledge Base Learning reduces repetitive work and improves consistency, but human oversight is necessary for policy changes, regulatory interpretation, and high-risk decisions.

If you want to proceed, contact your Brilo AI account representative or open a conversation in the Brilo AI dashboard to start a KB ingestion pilot and review configuration options.