Permission-aware AI for legal, finance and IT.
Real job shapes for teams that need answers with sources, not documents with a chat box on top.
Jobs, not chat wrappers
These are use cases: the questions the organisation already argues about. Who can use the agent is a separate choice, a person or a named team, under the same governance. Every answer stays inside existing permissions and arrives with its sources.
Slite’s 2026 knowledge-base security note is the right test: the only safe pattern is a permission filter before the AI retrieves a document. Exceptional AI’s RAG checklist says the same for enterprise knowledge bots: honor ACLs, group membership, region limits, and matter-based walls at query time. Do not let a service account index everything and hope prompt rules will fix it later.
Legal, finance and IT sit on one governed knowledge layer. Add another use case and that memory is already there. See the full set on the use cases page.
Legal and contracts
An answer about an indemnity cap is worthless without the clause it came from. Connected enterprise knowledge keeps the signed agreement, the playbook and the amendments related, so the clause is not a one-off search. SenangAI shows the paragraph behind each finding.
A typical question: “What did we agree on liability with this supplier?” The answer should carry the signed agreement, the playbook position and the amendment log. Draft the summary; a lawyer approves before it sends. Access to unrelated matters is denied and recorded. That approval step is the same pattern as agents with human approval.
Finance and procurement
Finance questions are rarely about the number. They are about which entries moved it, which of those were approved, and whether anyone should have noticed sooner. Invoice, approval and contract stay linked next quarter, not as a screenshot from last month.
A typical question: “Why did this cost centre move 18% this quarter?” The trail should include the ledger export, the vendor invoice and the change approval. Invoice checks can wait for a person. Spend budgets can apply to the AI itself. How those controls sit in one console is on Govern.
IT and engineering
The answer usually exists: in a two-year-old incident review, a decision record nobody indexed, or the head of an engineer who has since moved on. Runbooks, incidents and architecture decisions stay in long-term memory, so the question is answerable without granting an external tool access to production.
A typical question: “Has this failure mode happened before?” The sources should be the incident, the decision record and the failover runbook. Agents stay scoped per team, never global. For why chat and search are not this job, read where SenangAI fits.
When you want us in the room, book a demo with one of these questions. For how to judge the product around them, use the buyer questions in the sovereign AI guide.
Sources and references
- Knowledge Base Security: 7 Questions Every CSO Should Ask. Slite.
- RAG Governance Checklist for Enterprise Knowledge Bots in 2026. Exceptional AI.
- Why Your RAG Pipeline Keeps Leaking Data It Shouldn't. Simplico.
- Put the Security Check Inside the Query, Not After It. DEV Community.
- Secure Enterprise RAG: ACLs, Tenant Filters, Provenance. Oracle Developers.