Turn every conversation into an approved next action.
Aivoral captures meetings, email, calls, and documents, then proposes commitments, CRM updates, tasks, and follow-ups in one review queue. Nothing changes until a person approves it.
Live: Achieved in a production deployment.
Every action
Approval gate
Meetings + mail + calls + docs
Input channels
Multi-tenant
Workspace model
Source-linked
Auditability
The challenge
Agency work runs on promises scattered across calls, inboxes, documents, and chat. Teams lose commitments, update the CRM late, and spend hours translating conversations into tasks while generic automation acts without enough context.
How it works
Aivoral continuously captures operational context and turns it into concrete proposals. Every item quotes its source, enters one review queue, and can be approved, edited, or dismissed before a validated action updates the workspace.
Outcomes
- Commitments and decisions become owned, dated work instead of forgotten notes
- CRM and project records are proposed from real client conversations
- No task, message, or record update executes without human approval
- Every approval traces back to its source and reviewer
Capabilities
Unified capture
Brings documents, meetings, inboxes, calls, calendars, and project context together.
AI review queue
Turns raw context into source-linked proposals for tasks, CRM, commitments, and follow-ups.
Human approval
Lets teams approve, edit, or dismiss every proposal before the system changes anything.
Operational memory
Keeps decisions, commitments, project health, and executive reporting connected over time.
Workflow
- 1
Capture
Ingest conversations, documents, meetings, and calls into the workspace.
- 2
Propose
AI identifies decisions, commitments, risks, and concrete next actions.
- 3
Approve
A team member checks the quoted source and approves, edits, or dismisses.
- 4
Execute
Validated actions update projects, CRM, tasks, and follow-up queues.
Platform stack
Deployment: Multi-tenant production application using NeuroCluster-hosted inference and embeddings.
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