Everyone else puts knowledge in your technicians’ back pockets. Knowledge is still a stack of documents somebody has to interpret standing in front of the equipment. Ascendo puts an expert there instead: it reasons across every manual, ticket and service record you hold and comes back with the likely cause, the step to try, who has fixed it before and the part they will probably need.
The whole industry has settled on the same promise: put all the knowledge in the technician’s pocket. But a document is not a decision. Six relevant manuals, spread across a CRM, a ticketing system, a wiki and old email threads that do not talk to each other, is still homework.
What they want is what a senior colleague standing next to them would give: the likely cause, the step worth trying first, who has seen this before, and which part to have on the van. That is a different job from returning a search result.
The recording follows a real gas ignition fault the whole way, in about two minutes.
Describe the problem, then choose the data sources and product groups in play — before the agent starts.
It analyses content rather than matching keywords, so a fault described one way reaches a fix written up in other words.
Not a reading list: a plain-language summary of the resolutions worth trying, with the ranked sources underneath.
Rephrase it by tone, format or length, then pass it to the Knowledge Agent to publish.
Three capabilities a general-purpose enterprise search has no way to produce against equipment data.
Top technician surfaces the most experienced people for this issue, parts recommended the replacements likely needed, and root cause categories the underlying source rather than the symptom. None of that is retrievable from documents alone — it needs an install base, a skill matrix and parts data.
“The top technician feature highlights the most experienced experts available for support.”
Results are ordered by context, by date of creation, and by feedback from the agents who used them. Your technicians do the tuning, so it converges on your vocabulary and your failure modes.
“The documents are ranked from highest to lowest relevancy based on context, date of creation and agent feedback.”
You get a synthesised resolution summary and the ranked documents it was built from. The summary is what to do; the documents are how you check it.
“The suggested solution cuts through any technical jargon and is easy to understand.”
Most service organisations have already tried at least two of these.
Fails the moment terminology drifts, which is constantly. The fix exists, written in words nobody thinks to type.
Indexes documents competently, but with no install base, skill matrix or parts data it can never produce a top technician or a recommended part.
No source attribution, no feedback loop and no product-group scoping. Nothing improves over time and nothing can be checked.
Works, does not scale, and the knowledge leaves the building when they retire.
Terms you will hear in the recording.
What happens when search comes up empty: pull the expert in, and capture what they know on the way past.
How manuals and spec sheets become searchable knowledge in the first place.
The product page, with the wider capability and published customer results.
Intelligent Search
Pick a problem that keeps coming back and we will show you what Ascendo surfaces from your own documentation and ticket history.
Talk to us