your agent is talking to your users.
you have no idea how it's going.
abracadabra analyzes every conversation your agent has, surfacing friction, intent, and user health in plain english.
sarah connor · enterprise · billing flow
billing 32% · bug-report 28% ↑ · export 22% ↑ · onboarding 18%
12 new in last 5m
the blind spot
your traces are green.
your users are giving up.
your agent is having hundreds of conversations a day. latency is fine. infrastructure is healthy. uptime is 99.9%.
none of that tells you that your best enterprise account tried to export a report three times this week and gave up. or that forty users are looping on the same unresolved intent. or that sentiment has been falling for six days straight and nobody noticed.
you find out when they file a ticket. or when they don't renew.
the gap
you see the ticket. you missed the conversation.
by the time support gets a message, the decision to leave is already made. the signal was in turn three. nobody read it.
the illusion
uptime 99.9%. users quietly giving up.
latency is fine. your best enterprise account has looped on the same intent four times this week without the agent noticing. your infrastructure dashboard has no idea.
the question
"which flow is breaking enterprise users?" nobody can answer that.
product has a trace. cs has a ticket. nobody has the conversation, and nobody has the pattern across thousands of them.
what we show you
every conversation, read and annotated before you open the workspace.
abracadabra classifies intent, friction, sentiment, deflections, and loops at ingestion — no manual labeling, no waiting. below is what one conversation looks like when every signal is already tagged and every problem already surfaced.
that's one conversation. you get all of them — searchable by meaning. ask "show me enterprise users who failed on billing this month" and get ranked sessions with the friction already marked, not a spreadsheet request.
user history
every session a user has had with your agent — all their intents, all their signals — linked across time. click any user to see the full arc from first message to the moment they gave up.
events
discrete moments — tool errors, intent loops, escalations, sentiment drops — tagged as they happen and queryable across your whole conversation history, not just the current session.
intent patterns
what your users are actually trying to do, classified and aggregated across every conversation. see which intents spike, which have the highest friction rate, and which your agent consistently fails at.
how your team uses it
every role gets what it needs. nobody hunts for context.
product asks questions. cs acts on queues. everyone reads from the same source. here are the three surfaces your team opens every day.
morning brief
know what changed while you slept.
intent spikes, friction rate changes, at-risk users, and an ai-written summary of what your agent got right and wrong overnight. starts your day with signal, not questions.
rescue queue
users who need help, with context pre-loaded.
ranked by health score. cs opens the queue and sees the user, the conversation, the turn where it broke, and what the agent did wrong. no digging. just act.
sprint fuel
which flows are breaking which users.
filter by intent, segment, and signal type. "where do enterprise users fail on billing?" becomes a 3-second answer with ranked examples, not a week-long data project.
under the hood
classified at ingestion. every turn, every conversation.
we don't wait for you to tag things or run batch jobs. the moment a conversation arrives, every turn is read and classified. the signals are already there when you open the workspace.
see your agent clearly, for the first time.
join the design partner program. we're onboarding teams with live agents in production.
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