RAGSuite AI - keeen GmbH
Cited Answers at Enterprise Scale Manual search time ↓72% · p95 latency ↓68% (5.8s → 1.9s) Turning scattered knowledge into precise, explainable answers, securely, at scale. Key Results Reduction in manual searches: 72% Answer latency: ↓ 68% (5.8s → 1.9s p95) First-contact resolution: +41% Content freshness window: < 10 minutes from source update to index
Client
Confidential (Enterprise pilot)
Industries
Knowledge Management · Enterprise SaaS
Services
Data Connectors & Ingestion
Project Scope
Enterprise RAG System Implementation
Challenge
Teams were drowning in scattered knowledge, wikis, tickets, PDFs, dashboards, and endless Slack threads spread across systems with different formats and permissions. Earlier agents and chatbots had already been tested, but they delivered slow, inconsistent answers and occasionally hallucinated, eroding confidence.
What stakeholders needed instead was a system that could deliver trustworthy, cited responses across multiple repositories while respecting strict access controls, including row- and document-level permissions. It also had to stay in sync with near-real-time content changes and demonstrate clear, measurable improvements in support resolution and analyst productivity.
Solution
Connectors & Ingestion
Prebuilt pipelines for Confluence, SharePoint, Google Drive, Git, ticketing systems, and data warehouses. Supports incremental crawls, change capture, and per-source schemas.
Smart Chunking & Enrichment
Domain-aware chunking for headings, tables, and code blocks, with metadata tagging and section anchors to boost retrieval precision and citation quality.
Hybrid Search Retrieval
Dense embeddings + BM25 with re-ranking, plus source-diversity guardrails to avoid single-document bias.
Policy-Aware Querying
Query-time authorization using ACLs and group roles, ensuring users only see permitted content down to the paragraph.
Grounded Generation
LLM restricted to retrieved context with citation injection, refusal rules, and optional tool adapters for live lookups.
AI Architecture Flow
AI Technical
Stack
Confluence
SharePoint
Google Drive
GitHub/GitLab
Jira/Zendesk
Websites/Sitemaps
CSV/Parquet
Apache Solr
Elasticsearch (BM25)
FAISS
OpenAI
Anthropic Claude
Google Gemini
Azure OpenAI
Tracing/Logging (provider-agnostic)
Feedback/Eval Suites
0%
Manual hunt time dropped 72%, helping people find answers faster, with p95 response times under 1 second for common queries.
0%
First-contact resolution rose 41% thanks to grounded, cited responses and stricter guardrails, resulting in better answers and fewer escalations
0X
Permission checks at query time and audit trails ensured content freshness and compliance, boosting stakeholder trust.
0%
Feedback loops and evaluations continuously reduced hallucinations and improved groundedness scores across releases.
AI Architecture Flow
Client's
feedback
“RAGSuite gave our teams instant, trustworthy answers with citations, no more ping-ponging across tools. Productivity went up, escalations went down, and leadership finally had observability into how knowledge is used.”
Ralf Schindler
Managing Partner keeen GmbH
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