The volume layer. Then the control plane.
If your team is doing the same operational motion every day, we automate the throughput and route the rest. Pair with Outcome BPO when you also need us to own the exception desk.
Map the workflow
If the exception paths are not written down, we will not automate the happy path and call it done.
- Walk the real queue with the people who run it today
- Name the 80% path and the exception classes that sit outside it
- Decide what the model may close versus what a human must own
- Agree the audit artifact before we pick a model
Build the pipeline
Bots, jobs, extraction, and routing — the volume layer.
- Document intake, extraction, and structured handoff
- Scheduled jobs, real-time triggers, and alerts
- Messaging connectors where the team already works (Telegram, WhatsApp, Slack)
- A queue UI so operators see aging work instead of hunting in chat
Run the control plane
DeployAI-class planning: sequence the work, watch the queue, escalate the hold.
- Workload sequencing and pod assignment — architecture, not a scored “neural” claim
- TechPulse-style telemetry: stuck, aging, failing the agreed window
- AssistIQ-style first pass with a named owner on the exception
- Handoff into Outcome BPO when you want the desk, not just the software
You keep the desk.
We ship the pipeline and the queue. Your team owns exceptions. This is the AI automation cut — useful when you already have reviewers and need throughput.
Scope a pipeline →We take the desk too.
Outcome BPO adds governed labour on top of the same control plane. AI does the volume. We own exceptions, audit, and outcomes.
See Outcome BPO →Tell us the queue that is breaking.
We will say whether Outcome BPO or AI automation is the right cut — and what we would own. No seat quotes. No manpower pitch.
Talk to us →