Give every human and AI agent the Brain behind great service
Service is where your organization’s knowledge meets the customer every day, and where improving it pays back fastest.
ClearMash is a game changer.
With ClearMash’s comprehensive analytics, you can quickly identify gaps and opportunities for content enhancement and expansion.
From smart calculators to call scripts and data comparisons - ClearMash helps us deliver better service, faster.
Today, we can confidently say that all our information is consolidated in the system, updated in real time, and effortlessly searchable.
ClearMash is a significant partner in our ability to connect ONE ZERO’s innovation with the service customers actually receive.
With ClearMash, we found true partners for the journey, and together we have achieved Cellcom’s service goals while dramatically enhancing our ability to maximize our knowledge in every customer interaction.
The flexibility in accommodating changes, seamless integrations, and creative solutions made ClearMash a true partner.
ClearMash delivers knowledge intuitively to our service agents, empowering them to make swift, accurate decisions.
With ClearMash, we centralize knowledge, streamline collaboration, and ensure that every team has access to the right information - in the way that works best for them.
ClearMash’s AI-driven knowledge management system lets us manage our organizational knowledge efficiently and consistently, with quick, simple, and accurate search and retrieval capabilities.
Thanks to ClearMash, we’ve significantly enhanced our agents’ professionalism and overall service quality.
With ClearMash, we deliver knowledge quickly and accurately - boosting customer satisfaction and earning valuable praise from our B2B clients.
ClearMash has revolutionized the way we operate by enabling our employees to access vital information effortlessly, thereby significantly enhancing their efficiency and accountability.
ClearMash stands out as a comprehensive solution for anyone looking to access, engage with, and visualize information with ease.
Why this matters in customer service
Service is a knowledge operation that happens to answer phones. A service agent’s real job is to work out which situation this customer is in, what your organization’s position on it is, and what happens next, while the customer waits.
The difficulty is structural. The answer is spread across the product page, the policy document, the procedure the team actually follows, and the memory of the colleague who has been there longest. Parts of it are out of date, and part of it was never written down.
Then another channel is added. Then self-service. Then an AI agent. Each is built from someone’s own reading of the same unclear source, so the answers diverge.
Meanwhile the cost is measured every day, in seconds of handling time, in transfers, in repeat contacts, and in the quiet damage of a customer being told different things by the same company in one week.
- The challenge:
Inconsistent answers
Same question, different channel, different outcome, and no way to tell which one the organization stands behind.
With ClearMash Brain:Consistency across every channel
Phone, chat, portal and AI agent give the same governed answer to the same question.
- The challenge:
Handling time spent searching
A measurable part of every call is the service agent reading, not resolving.
With ClearMash Brain:Resolution without the search phase
Handling time falls when the answer does not have to be assembled first.
- The challenge:
Escalation to the few who know
The same handful of people are interrupted for the same exceptions, and the queue forms behind them.
With ClearMash Brain:Fewer escalations to specialists
First line handles the exception because the exception is written down and applicable.
- The challenge:
Self-service that stalls
The customer finds an article that nearly matches their situation, then calls anyway.
With ClearMash Brain:Self-service that finishes
More customers complete without contact, because the guidance fits their situation.
- The challenge:
Unsupported AI answers
An AI agent given contradictory source material will still answer, fluently and confidently.
With ClearMash Brain:AI answers the organization stands behind
An AI agent answers from the governed position, and a service agent takes over where the method says so.
- The challenge:
Training that never ends
New service agents spend months learning where things are before they learn how to help.
With ClearMash Brain:Faster time to competence
New service agents work on their own sooner because judgment is supported rather than required.
It presents as a service problem. It is a What and How problem.
What: which product, which fee, which entitlement, which policy version applies to this customer, today, on this contract. How: the steps that resolve it, the check that has to happen first, the exception that changes the outcome, and the point at which it has to go to someone else.
Leave the What or the How unclear and the effect is identical for a service agent and an AI agent. Time is spent interpreting, judgment fills the gap, and competent service agents handle the same case in defensible but different ways.
This is why adding channels rarely improves consistency, and why an AI pilot that performed well on its test cases struggles in production. What decides the answer, in every channel, is the understanding underneath it.
One governed answer, and the same action in every channel
The Brain holds the organization’s position on the situation, stated so a service agent can act on it.
A service agent asks what applies to this customer and receives the answer with its conditions attached: the version that governs their agreement, the exception their status triggers, the reason behind it, and the steps that close the case.
The self-service experience draws on the same understanding, expressed in plain language. The AI agent works from it with the defined skill that describes how your organization performs the task and where it must hand back to a service agent.
When the policy changes, it changes in one place and reaches all of them together, so the portal and the service agent say the same thing from the same day.
Improve not only what AI agents know, but how they work.
The exception arrives with the rule
Service agents are ready for the case that does not fit, because it is part of the answer.
Version and date are part of the answer
What governs an agreement signed a few years ago is available next to what governs one signed today.
Self-service inherits the same understanding
Customers receive the organization’s actual position, in their language, instead of the closest article.
AI agents get skills, not just knowledge
How a case is handled is defined, so an AI agent follows your method rather than inventing one per conversation.
What a service organization has to get right on every contact
Each of these is settled before a service contact closes.
- WHATWhat this customer is entitled to under the plan they actually hold.
- WHICHWhich version of the policy governs an agreement signed before the change.
- WHOWho can approve this exception, and up to what value.
- WHENWhen the commitment just made to them takes effect.
- WHEREWhere the treatment changes, by market, channel or regulation.
- WHYWhy it lands this way, in words that can go to the customer in writing.
- HOWHow it is handled end to end, including the part after the call ends.
The agreement was signed in February. The fee changed in April.
The service agent states the position and closes the case.
A customer calls. The service agent’s screen fills with what applies, how it is handled and the context that decides - the superseded version repaired to the one that governs this agreement - and the answer goes back down the line, so the case ends on the call instead of being referred.
What Entitlements · Fees · Policy
- Fee schedule
- Refund rule v3
- Plan terms
- Entitlement
- Exception rule
- Goodwill limit
- Charge codes
- Eligibility
- Service level
- Policy version
- Contract terms
How Handling · Discretion · Wording
- Handling steps
- Identity check
- Exception path
- Approval limit
- Escalation rule
- Wording to use
- Follow-up step
- Case closure
- AI agent skill
- Handover point
- Callback rule
Context Decides which What and which How to act on, for this contact
- Who This customer
- When Contract date
- Where Channel
- Which Plan held
- Why Reason to give
- Service agentsresolve it on the call
- Customersfinish without calling back
- AI agentsfollow the same method
- The call is filed as it ends
What it looks like on an ordinary Tuesday
A customer calls about a charge. Their agreement was signed in February. The plan changed in March, and the fee was removed for new agreements in April. The service agent does not need that history. They need to know that the fee applies, why it applies, what discretion they have, and what to say.
Today that costs a search, a colleague, or a guess, and the answer varies. With a Brain it arrives with the case: the version governing this agreement, the exception their status triggers, the goodwill limit this service agent may exercise, and wording consistent with what the portal would have told the same customer an hour earlier.
Where a Brain sits between the queue and the case
The switch keeps routing, the CRM keeps the account and the desk keeps the case. The Brain reads them together and answers between them.
The Brain sits on top of your CRM, and on top of the switch and the case system with it. What it adds above them is the layer that reads the queue, the record and the case together, and settles what applies to this customer before a service agent has to work it out with someone waiting.
What the Brain reads when a contact arrives decides whether the answer is right. Where the service answer lands decides whether the customer hears that answer in every channel, the portal included.
What the Brain reads when a contact arrives
- Queues, IVR and chat routing Which queue it landed in, what the caller chose, and what has been said.
- CRM and the account record The plan this customer holds, the entitlement behind it, and the history.
- Service desks and case history The case that is open, and what the last one with these symptoms needed.
- Product, pricing and plan terms The fee, the tier and the conditions in force when this was signed.
- Policies, procedures and published pages What the organization has already written about this, wherever it lives.
Knowledge orchestration layer
ClearMash Brain
What · How · Context
What this customer is entitled to, and what to say.
Where the service answer lands
- The service agent’s desktop Beside the record and the case already on screen.
- The live conversation Into the call or the chat while it runs, in the channel they chose.
- Self-service and the portal The same position in public, in the customer’s words.
- AI agents on first contact The knowledge and the method an AI agent gets, and the point where a service agent takes over.
- Email and written replies The position in writing, in the words the portal and the service agent used.
The switch, the record and the case stay where they are. What changes is that they now agree.
Service agents
Fewer tabs, less interpretation, and a clear position on the situation in front of them.
- Shorter handling time
- Fewer transfers
- Confidence on unfamiliar cases
- Shorter path to competence
Customers
The same answer whichever way they get in touch, and enough guidance to finish without calling.
- Lower effort
- Fewer repeat contacts
- Higher self-service completion
- Consistent treatment
AI agents
Relevant knowledge for the case and a defined method for handling it, with a clear boundary.
- Fewer unsupported answers
- More consistent behavior
- Less context carried per task
- Cleaner handover to your service agents
Tangible impact
The changes a working Brain makes, in the order a service floor meets them.
Business impact
- Reduction in inquiry handling time 28%
- Reduction in expert escalations 65%
- Increase in self-service adoption 30%
- Increase in customer satisfaction 15%
- Increase in first contact resolution (FCR) 40%
- Increase in employee satisfaction 62%
- Reduction in new employee onboarding 70%
- Reduction in compliance violations 14%
Technological impact
- AI agent accuracy from 85% to 97%
- Increase in AI agent speed 25%
- Reduction in AI costs 74%
Additional measures
Beside those figures, the measures a service floor already reports:
- Average handling time
- first-contact resolution
- transfer and escalation rate
- repeat contact rate
- self-service completion
- time to competence for new service agents
- the volume of organizational context consumed per AI interaction
All of them are instrumented on a service floor already, so a change in the knowledge behind an answer shows up in the numbers the floor runs on.
Your knowledge base stays
What the Brain adds is the path from a customer’s situation to your organization’s position on it, which a service agent can act on without interpreting anything in between.
Self-service and the AI agent take the same path, so every channel arrives at the same place. Once the material is applicable, each channel is a matter of delivery.
Why ClearMash for service
ClearMash takes responsibility for the organization’s understanding itself: that it is correct, current and applicable to the case in hand.
It serves the human agent, the self-service customer and the AI agent from that same understanding, so consistency stops being a coordination exercise between teams.
Every answer has an owner
Every position a service agent relies on has a named owner, an approval behind it and a version history, and access rules bind the AI agent exactly as they bind the service agent. Customer records stay in your service systems, and the Brain holds what they mean. The detail, and the certifications, live on the Security page.
See one governed answer reach every channel
Book a demo and we will show you an answer arriving with its version, its exception and its next step: in a service agent’s window, in self-service, and in what an AI agent replies.
Prefer to start with the numbers? The impact estimator works them out