When the model isn't sure,
a human is.
Tiered confidence routing — auto-approve when the model is sure, fast-track to humans when it's not. Sub-60s SLA, multilingual, with decisions feeding back into training.
Built for production, not just demos.
- Confidence-band routing (auto / review / expert)
- Sub-60s p50 SLA for tier-1 categories
- 60+ languages with native-speaker reviewers
- Per-domain expert pools (medical, legal, finance, code)
- Tier escalation rules + adjudication queue
- Feedback loop into SFT and RLHF datasets
- Live dashboards + SLA + accuracy + drift alerts
- API + webhook integration with your stack
How a typical engagement runs.
Route
Your model returns a confidence; routing rules direct above/below threshold.
Review
Reviewer sees context + model rationale + history; makes calibrated decision.
Escalate
Ambiguous or high-severity cases go to adjudicator pool with audit trail.
Respond
Action propagates back to your platform within SLA via webhook / API.
Feedback
Decisions automatically enriched as training data for SFT / RLHF / classifier retraining.
What you get in your bucket.
Questions, answered.
What confidence threshold should I use?
Depends on cost of error vs review budget. We co-design with you — typically 0.9 for tier-1 actions, 0.75 for tier-2. Auto-tuned monthly based on production metrics.
Can reviewers see PII?
Configurable. We support PII redaction at ingest, role-based access (only escalation-tier sees PII), and full audit.
How do you integrate with my queue?
REST/webhook is the default. We also support Kafka, AWS SQS, Pub/Sub for high-throughput. Most integrations live in 1-2 weeks.
What happens during regional outage?
Automatic failover across 3 regions; SLA maintained. We publish quarterly uptime + failover drill reports.
Ready to build
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