RAG agent with knowledge base
Respond promptly to any internal or customer queries with a AI agent connected to yours knowledge base. Search, reason and cite sources accurately, reducing response times, errors and costs while generating more opportunities and qualified leads.
Knowledge agent with AI for businesses
one RAG agent (Retrieval-Augmented Generation) turns your scattered documentation into useful and verifiable answers. It connects to repositories, manuals, procedures, contracts or tickets and retrieve relevant fragments before writing the answer, citing its source. This way you avoid guesswork, accelerate support and scale the knowledge base without changing your systems.
With Daimatics, the phone, web chat and email become intelligent channels: the agent understands the intent (“return policy”, “steps of’implementation”, “SLA of’incidents”", "how make appointments”), unifies versions and delivers the right answer to each role. Plus, it learns from interactions: new questions and improvements become structured content, raising the quality of self-service and your documentation.
How a RAG agent with knowledge base works
A pipeline “"from document to verified answer"” designed for precision and governance:
Intake and normalization: connectors to SharePoint, Confluence, Drive, intranet, HTML/PDF, emails or tickets. We segment into optimal "pieces", we generate metadata (author, date, permissions) and we clean up duplicates and versions.
Vector indexing: we believe embeddings and store in a vector DB with filters for permits and expirations. We control freshness so that the agent prioritizes the most recent.
Recovery with controls: for each query, the agent searches for the most relevant fragments (semantics + BM25) applying controls quality (similarity threshold, diversity of sources, minimum date).
Generation with quotes: the LLM composes a clear answer, with clickable quotes and warnings if data is missing or ambiguous. If it detects sensitivity, it refers a person.
Connected actions: from the answer can create qualified leads in the CRM, make appointments, open incidents, update FAQs or send a summary by email.
Analytics and improvement: we save queries, clicks and feedback to refine recall/precision, detect content gaps and feed the roadmap editorial and automation. KPIs: resolution rate, first response time and documentary coverage.
All together with controls security (roles, PII masking, evidence logging), real-time monitoring and anti-hallucination strategies (source-based responses and “I don't know” when appropriate).
How can Daimatics help you?
At Daimatics we combine consultancy, applied AI and data governance to make your RAG agent generate business from the first month. We design use cases, connect content, train prompt and policies, and we deliver dashboards with measurable impact on customer service, sales and operations.
Specific benefits:
Go-live in weeks: guided pilot with 50–200 critical documents, clear KPIs and orderly transition to production.
Full integration: ready-made connectors for ERP/CRM, SSO (Azure AD/Okta), corporate search engines and tools support (Jira/ServiceNow/Zendesk).
Governance and compliance: GDPR by design, inherited permissions, retention, response auditing and “mandatory sources”.
Continuous optimization: retrieval tuning, taxonomies, multichannel writing and forecast content demand to prioritize your roadmap.
FAQ'S
It is an AI agent that recover fragments of your documents before generate the answer. This maintains rigor, cites sources and reduces errors when faced with chatbots that respond “from memory”. It works on your existing content and respects permissions.
Through connectors and SSO. The agent indexes only what is allowed, inherits permissions by group/role and applies controls access to each question. If a user cannot see a document, the agent does not use it in the answer.
PDF, DOCX, HTML, Confluence/SharePoint, tickets, FAQs, policies, catalogs or manuals. We clean formats, deduplicate and version. We measure precision/recall, coverage and “response with appointment” to detect gaps and plan the roadmap.
Yes. The agent can trigger flows: create incidents with SLA, make appointments in diaries, register qualified leads in the CRM or send summaries by email, always with validations and logs for auditing.
Depends on volume and systems. We propose a pilot (2–4 weeks) and deployment by content domains. Model of costs: setup (integration, taxonomy, security) + monthly fee for use and support, with ROI measured in time savings and reduction of escalations.
