AI Agent Development

What this service covers

AI agents create value when they are grounded in real work, approved knowledge, access rules, and clear escalation paths. We design the responsibility boundary before the agent is allowed to answer, act, or update business systems.

• Enterprise knowledge agents and RAG portals for documents, emails, wiki pages, and web references
• Document ingestion, chunking, vector retrieval, keyword fallback, citations, and answer traceability
• Role-based permissions, department rules, LDAP or SSO integration, and controlled source access
• Cloud, private endpoint, self-hosted vector store, and local model options such as Ollama where the environment requires it
• Evaluation, guardrails, human handoff, dashboards, zero-hit review, and managed improvement after launch

How we work

We start narrow: one responsibility, frequent demand, accessible knowledge, clear exceptions, and a measurable outcome. For a knowledge agent, that usually means selecting one high-demand domain, importing approved current sources, testing whether staff can ask in natural language, and checking whether each answer links back to the original evidence.