Key Highlights
Motadata ServiceOps AI Text Intelligence packs six natural-language features into the ticket record: sentiment, summarization, drafted and refined replies, three-source solution search, and duplicate detection, each reviewed by the technician.
Know the requester's state before you reply. A record-header signal, not a separate report.
Sentiment Analysis evaluates a Request's subject, description, conversations, and feedback.
It classifies the Request as Positive, Negative, or Neutral.
The classification appears as a record-header icon, visible the moment a technician opens the ticket.
Sentiment recalculates on each update, so the signal tracks the conversation, not one moment.
A frustrated requester reads differently from a calm one at a glance. No need to read the full thread.
Condense long ticket histories into a clear summary the moment a technician needs context.
Ticket Summarizer condenses long Request and Service Request threads into a concise summary with one click.
Ideal for reassigned or escalated tickets, where re-reading days of back-and-forth wastes time.
The summary regenerates as the ticket evolves, so it always reflects the latest state.
A technician picking up a handed-off ticket starts from the summary, not the first message.
Turn ticket context into a ready, professionally-toned reply while staying inside the record.
Response Generator drafts contextual replies in the Work tab from the actual Request content.
Reply types: Acknowledge, Request Details, Follow Up, or Closure Confirmation.
Tone Enhancer rewrites selected text as Professional, Empathetic, Concise, or Expand.
It works in Reply, Comment, Solution, and Description fields.
Refined text shows side by side with the original and is never auto-saved.
Each draft is a starting point: technicians review, edit, and send, and nothing is sent automatically.
Bring the right fix into the Solution field in one pass: internal, then proven, then external.
Solution Assistant runs a three-phase search on Request and Problem records.
It searches the internal Knowledge Base, then resolved similar records, then the external web.
The chosen fix inserts into the Solution field in one click, with no copying between tabs.
Searching resolved records first reveals fixes that already worked in your environment, before the open web.
The technician selects, edits, and applies the suggestion. The search assists. It does not replace the decision.
Catch the duplicate or prior fix the moment a ticket takes shape, not after parallel investigation begins.
Similarity uses semantic matching to identify related and duplicate records on the fly.
It covers five record types: Request, Problem, Change, Release, and Knowledge Base.
Matches appear in the Similar Incident panel during creation and the Similar Tickets tab inside an open record.
A Suggested Knowledge panel sits alongside.
It understands meaning, so "laptop not turning on" matches "device not powering up", no keyword overlap required.
Records are never merged or closed automatically. Each match is a suggestion, and all actions stay with the technician.
All features live where technicians already work and stay under administrator control.
Each of the six features is toggled independently under Admin > AI > Text Intelligence.
Manage Text Intelligence permission gating on each.
Suggestions, summaries, and matches appear inside the open record, no separate tool, console, or context switch.
The semantic matching layer is backed by the Vector Store, with embeddings stored in PostgreSQL and matched via cosine similarity.
Nothing requires model training or a data science team.
The features read live ticket text the moment they are enabled.
Intelligence
A twice-failed requester reads identical to a calm typo report until the full thread is read. Reassigned tickets mean re-reading days of back-and-forth before useful action, the same outage spawns parallel investigations because no one checked, and reply quality depends on who picked up the ticket. The knowledge is already in the system but not in front of whoever needs it at the moment they need it.
AI Text Intelligence closes that gap by reading the ticket, gauging tone, summarizing history, surfacing matches, drafting the reply, and pulling the fix inside the record as work begins. Getting to the fix is the slow part, and that is what the suite compresses.
How It Works
Apply natural-language understanding to ticket text, conversations, and notes. No model training required.
Classify Request sentiment as Positive, Negative, or Neutral, displaying a live header icon on updates.
Summarize long Request and Service Request threads on demand, updating as conversation history evolves.
Generate contextual replies and refine tone in editor fields, requiring technician review before sending.
Cross-source search:Search KB articles, resolved records, and web sources, matching over 5 record types via Vector Store.
Toggle features independently under Admin > AI > Text Intelligence, gated by admin permissions.
Each ticket read, summarized, and answered inside the record, with the technician in control of all actions.
Role-Based Value
Make resolution quality a property of the platform, not of whoever picked up the ticket.
Make resolution quality a property of the platform, not of whoever picked up the ticket.
Standardize how all technicians read, reply to, and resolve tickets, with no scripted macros and no policing tone by hand.
Standardize how all technicians read, reply to, and resolve tickets, with no scripted macros and no policing tone by hand.
Open a ticket and start at the answer with sentiment analysis, ticket summary, duplicate detection, Response Generator, and Solution Assistant already working.
Open a ticket and start at the answer with sentiment analysis, ticket summary, duplicate detection, Response Generator, and Solution Assistant already working.
See your published knowledge actually reach technicians at the point of resolution.
See your published knowledge actually reach technicians at the point of resolution.
From Visibility to Control
First response is faster: Response Generator drafts the acknowledgement or closure note from the ticket itself.
Tone stays consistently professional and appropriately empathetic, regardless of who is at the keyboard.
Duplicate investigation drops: Similarity flags the matching or in-progress record before parallel work begins.
Solution Assistant brings Knowledge Base articles, prior resolutions, and web guidance into one search.
New technicians lean on the same sentiment cues, summaries, and suggested fixes the experienced ones rely on.
Explore More
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