Known
The configured signup-entry click was observed in the generated fixture.
Monolytics Assistant
Ask a question about your website or product. Verify the answer before you act on it.
Monolytics is an AI-assisted session replay and product analytics platform. Its Assistant answers product questions with inspectable evidence and exposes missing data instead of guessing.
Deterministic synthetic product example: generated fixture data, not customer activity or a promised result.
Anatomy of a verified answer
Every answer shows its scope, evidence, and limits
- Finding: the exact value with its numerator and denominator.
- Period and scope: the closed analysis window and domain the answer covers.
- Evidence status: whether the committed evidence fully supports the answer.
- Sources: representative replays and evidence you can open and inspect.
- Limitation: what the answer deliberately does not claim.
Anatomy of an evidence gap
When the evidence is incomplete, Assistant says exactly what is missing
A useful partial answer keeps the nearest verified observation and states four things: what is known, what cannot be concluded, why, and the concrete event, property, Survey, or recording step that would close the gap. Missing evidence is never silently converted to zero.
Deterministic synthetic product example: an observed Free-plan signup-entry click is kept as a generated partial result, while completed signup remains unknown because the fixture contains no completion event. This is fixture data, not customer activity or a promised result.
Cannot conclude
Completed Free-plan signup cannot be calculated from that click.
Missing signal
Add and verify the configured signup-completion event before asking for a completion rate.
Question families
Ask about behavior the evidence can actually show
Assistant supports question families across acquisition, behavior and content, friction and reliability, configured conversion and funnels, usage and adoption, activation, retention, segmentation, trust, and data readiness. What an exact answer needs is a defined page, flow, event, segment, or outcome—and the instrumentation to observe it.
“Which checkout step shows repeated abandonment this week?”
“Do listing-page visitors who use search reach contact more often than browsers?”
“Where do trial users stall between signup and the configured activation event?”
“What share of form starters abandoned before submit in the last closed week?”
Not every question has an exact answer. When the required signal, identity, or window is missing, Assistant states the gap instead of guessing.
Finding sessions vs. answering questions
Record Search finds sessions. Assistant answers questions.
- Natural-language Record Search finds or filters sessions for manual review—use it when the job is building a review set.
- Monolytics Assistant answers a defined question with verified scope, period, values, and sources—use it when the job is a decision you need evidence for.
Verification and causal boundary
Verify before you conclude
- Answer values, periods, scope, and source references of committed evidence-backed answers are deterministically verified.
- A representative replay shows what happened; it does not prove why. Assistant surfaces observed behavior and scoped evidence for a team to verify.
- A browser client is not a verified person; recordings, events, and identified users are different units and are never silently substituted.
Data readiness
An exact answer needs an observed signal.
If the event or property behind your question is not instrumented yet, the setup guide shows how to add and verify it.
Events, properties & data readiness
Define the signals behind your question, verify they are observed, and check whether an exact answer is supported yet.
Open the setup guide →AI Session Replay Analysis Workflow
Move from a product question to relevant sessions, repeated behavior, verification, and the next action.
Read the workflow →Session Replay Evidence Confidence Matrix
Separate an investigation lead from a repeated pattern or a supported finding before prioritization.
Review the matrix →AI Session Replay Analysis Checklist
Verify scope, representative sessions, competing explanations, and supporting signals before acting.
Use the checklist →Bring one real product question to the evidence.
Start free, ask about a specific flow, and verify the scope, sources, and stated limits before your team changes the product.
From the Monolytics blog
Review Assistant findings against inspectable session evidence.
Use these guides to evaluate AI-surfaced issue candidates, rage clicks, ignored CTAs, and form drop-off without treating a replay pattern as proof of cause.
AI Session Replay Analysis Workflow
How to use AI-assisted replay analysis to surface likely issue patterns, verify representative sessions, and choose the next action.
Read on the blog →AI Session Replay Analysis Checklist
A practical gate for checking AI-surfaced replay findings before filing a bug, shipping a UX fix, or launching a survey.
Read on the blog →AI Bug Triage From Session Replay Evidence
How to turn assistant-surfaced bug candidates into clearer triage notes with visible symptoms and representative sessions.
Read on the blog →How to Validate AI-Surfaced UX Issues
A workflow for validating UX issue candidates with successful-session comparison and supporting signals.
Read on the blog →Session Replay Evidence Confidence Matrix
How to classify assistant-surfaced bug and UX candidates before deciding whether to fix, survey, instrument, or monitor.
Read on the blog →