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Here’s where QUEL-418 — “Rate-limit the ingestion API” — stands this week:
-
Rate limiter merged
- Token-bucket shipped behind ratelimit_v2; PR #2291 merged with CI green.
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Load tested at scale
- Held at 5k req/s with p99 under 180ms.
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Rollout is the last step
- Staged rollout owned by Dwayne, targeted Thursday.
- Redis quota store (QUEL-402) is already Done.
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QLY-214 / Threads
From Jira
Improving chatbot handoff accuracy
Orbit raised 4 questions
QUEL-418 / Orbit Chat
Here are the open risks and blockers on this unit right now:
1. Blocked on the intent model
Handoff currently relies on explicit keywords like “agent” or “human support”, and misses softer / frustrated language. Retraining is blocked until:
- The labelled escalation dataset lands from Support — owner is out until Thursday.
- Staging access to the NLU service is approved (request open 3 days).
2. Risks worth flagging
- Scope creep: the thread now includes sentiment routing, which wasn’t in the original spec.
- False positives: a looser trigger risks escalating conversations the bot could resolve.
- Dependency: the rollout flag ratelimit_v2 must ship before this can go live.
Two of these need a decision from you before the next sprint:
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We’re seeing too many chatbot conversations stay with the bot even after the customer clearly asks for a human. The biggest issue is when they say “can I speak to someone?”…
Agreed — the handoff logic only catches explicit phrases like “agent.” When it does fire, the customer should be told what’s happening, not dropped into a queue.
Improving chatbot handoff accuracy
overview
We’re seeing too many chatbot conversations stay with the bot even after customers clearly ask for a human. The handoff logic relies on explicit keywords (e.g. “agent”, “human support”) and misses softer language like “this isn’t helping” or “I need someone,” causing delayed handoffs, repeated questions, and customers arriving already annoyed.
next steps
- Analyse recent conversations
- Pull the last 30 days of chats where handoff should have fired but didn’t.
- Label them “correct resolution”, “missed handoff”, or “unnecessary handoff”.
- Improve handoff intent detection
- Add a broader intent layer beyond simple keyword matching.
- Combine intent with confidence scores and conversation context.
requirements
- Detect handoff intent from indirect phrasing, not just “agent”.
- Combine detected intent, bot confidence, and repeated attempts.
- Show a clear message to the customer when a handoff is triggered.
QLY-214
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Implement the process and system integration for improving chatbot handoff accuracy based on the provided diagrams.
Success criteriaAccurate handoffs with no errors across the specified nodes and edges.
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Handoff sync · QLY-214
12:04
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