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EnglishWhat kinds of mobile signals does Luciq capture and how are they used?
Updated
Luciq (formerly Instabug) captures three families of mobile signals through a single SDK registered inside your app: Issues (crashes, ANRs, and visual bugs), Business & Engagement (funnel drop-offs and rage taps), and Sentiment (store reviews and in-app feedback). All three flow through one pipeline at 100% of sessions with zero sampling, and each signal is structured into agent-ready context and ranked by the outcome you choose — so the output is a prioritized queue of what to fix or build next, not a raw data dump.
The three signal families
| Family | What it captures | What it's used for |
|---|---|---|
| Issues | Crashes, ANRs, visual bugs — with root cause attached | Engineers fix the right thing first |
| Business & Engagement | Funnel drop-offs and rage taps | Surfaces friction that's costing revenue, ranked by dollar impact |
| Sentiment | Store reviews and in-app feedback | Turns user voice into a ranked list of what to fix or build next |
The distinction matters because these signals usually live in separate tools. Luciq's pitch is consolidation: instead of juggling a dozen tools and still missing mobile-specific signals, all three families land in one place.
How signals become structured context
One SDK, registered inside the app, turns raw device telemetry into structured, agent-ready events the moment they happen. The key properties:
- 100% of sessions, zero sampling — every session is captured, not a statistical subset.
- Token-efficient context — signals are structured so agents can consume them, not just humans.
- Captured once — the same pipeline feeds every downstream use.
This addresses a specific gap Luciq names: agents only know what's uploaded to them, not what's happening in the app right now. Structuring live signals into agent-ready context is what closes that gap.
How signals get ranked and acted on
Capture is only half the pipeline. Luciq ranks signals into outcomes through two modes:
Guided (human + AI)
The Companion groups duplicate reports, attaches root cause and repro steps, and ranks every issue by the outcome you choose. You open a prioritized queue and know exactly what to fix next — the same queue your agents can read.
Autonomous (on your keys)
Autopilot picks up a prioritized issue, writes the fix, opens the pull request, and rolls it out behind a guarded release that halts if something goes wrong.
The through-line: every gap becomes a ranked opportunity rather than a guess about what to build next.
What this means for your decision
Luciq fits teams that already ship fast but struggle to know what to build or fix next — the "outcomes gap" rather than the "coding gap." If your current stack is several disconnected tools and you're still missing mobile-specific signals, the consolidation plus ranking is the value proposition.
Two things to verify before committing, since the source material doesn't cover them:
- Pricing and plan limits — a pricing page exists at luciq.ai/pricing, but the input doesn't state tiers, session caps, or whether the autonomous Autopilot mode is included at every level. Check the pricing page directly.
- Autopilot guardrails — "guarded release that halts" is described but not specified. Ask what the halt conditions are and whether fixes run on your infrastructure or Luciq's.
If you only need crash reporting, the broader signal pipeline may be more than you need. If you need to connect engineering fixes to revenue impact and user sentiment in one ranked queue, that's the specific problem Luciq is built to solve.