AI Decision Agents
An intelligence layer for this capability
AI Decision Agents answers questions, summarizes evidence, and prepares documents or next steps for review and approval.
Operational AI
Generative AI
LLM solutions grounded on private data, with RAG, access controls, and traceability — useful answers with citations, not chat for the sake of chat.
- Corporate RAG
- Citations
- Per-role permissions
The problem
Where companies lose time, resources, or control
Generative AI without grounding produces fluent answers that look right and aren't. The fix is private data, explicit retrieval, and citations — not a fancier prompt or a different model.
What 7 Business Solutions does
From business problem to operational software
- Corporate RAG over private documents, policies, and structured data.
- Answers with citations and traceability back to the source.
- Per-role access controls and document-level permissions.
- Deployment in private cloud, VPC, or on-premise as required.
- Continuous evaluation of answer quality with feedback loops.
- Vector search tuned for enterprise document corpora.
Use cases
Operational scenarios for this capability
Concrete situations where this capability can support operations.
- 01
Internal knowledge assistant grounded on policies and runbooks.
- 02
Documentation search across product catalogs and SOPs.
- 03
Consultant assistant over methodology and reference projects.
- 04
Customer-support assistant grounded on product knowledge.
- 05
Compliance assistant answering policy questions with citations.
- 06
Domain-specific Q&A over private structured and unstructured data.
Capabilities and technologies
Stack and capabilities we apply
- LLMs
- RAG
- Vector search
- Citations
- Per-role permissions
- Evaluation harness
- Prompt engineering
- Private deployment
What we deliver
Deliverables you can operate and audit
- RAG architecture with documented data sources.
- Retrieval pipeline with quality checks.
- Permission model aligned with corporate policies.
- Evaluation harness with regression tests.
- Operations runbook and update cadence.
- Citation pattern and answer format spec.
Your next version
What should move first in your operation?
Let us turn that answer into a focused diagnosis, a first deliverable, and a path to scale.
01Problem and context
02Scope and first evidence
03Evolution path