Raghim AI is an enterprise agent platform for organizations that need AI to stay inside their own infrastructure. It runs governed agents, document search and natural-language database access under a self-hosted, managed dedicated or managed cloud deployment, so no data leaves the customer's environment. A workflow engine adds guardrails, retries, checkpoints and human escalation, and the interface is available in English and French.
It is built for IT leaders, compliance teams and data-driven enterprises in regulated industries such as legal and professional services, financial services, and healthcare and life sciences. Security officers who must keep privileged or patient information away from public models are a central audience. Analysts who want answers from company databases without writing SQL, and operations teams automating high-volume document work, also fit. Access controls include role-based permissions, audit logs, IP allowlisting and retention settings.
A law firm can search contracts, policies and matter files with governed retrieval and keep an audit trail of each query. A financial analyst can ask questions in plain language across approved databases, with SQL guardrails, row-level isolation and human approval for sensitive operations. A healthcare operations team can process clinical documents with controlled agent workflows on its own servers. Agents can post to Slack or Teams, open Jira or Asana items, work with GitHub and trigger webhooks, and teams can start in managed cloud and later move to self-hosting without lock-in. Flow templates, such as a digital teammate, give pilots a starting point before they scale into production, with approval policies, timeouts and audit visibility keeping autonomy aligned with company rules.
