Knowledge search
Answer across policies and documents with source citations.
ENTERPRISE AI AGENT & RAG Move enterprise AI from answering to safely completing work
Build governed knowledge retrieval, RAG and AI agents that connect approved data, workflows and existing systems.
What are enterprise AI agents and RAG?
RAG retrieves approved enterprise sources before generating an answer. An AI agent can additionally call systems and complete tasks within defined permissions and audit controls. Successful adoption depends on data quality, access boundaries, human review and measurable outcomes, not model size alone.
High-value starting points
Service assistant
Standardize responses and escalate complex cases to people.
Workflow automation
Summarize data, create documents and update existing systems.
Decision support
Analyze unstructured information under explicit review rules.
From PoC to production
Data and risk audit
Map sources, sensitivity, access and quality.
Measurable PoC
Test real questions against accuracy and failure cases.
RAG and agent architecture
Design retrieval, tools, permissions and review.
Operations baseline
Monitor cost, latency, failures and content freshness.
Choose the appropriate AI pattern
| Pattern | Best for | Primary risk |
|---|---|---|
| Knowledge RAG | Answers grounded in company documents | Stale content and retrieval quality |
| Workflow AI | Repeatable content and data tasks | Undefined exception rules |
| AI agent | Multi-step actions across systems | Excessive permissions and incorrect actions |
Enterprise AI FAQ
Architecture can use enterprise APIs and controlled retention settings. Provider terms and every data flow must be verified during design.
Related expertise
Start with one measurable workflow
Share the data sources, user roles and most time-consuming task. We will help determine whether RAG, workflow AI or an agent fits.
Provide a contact name or company, an email or phone number, and a short description. Budget and referral source are optional.