We publish outcome figures only with the customer's written approval, so this slot stays empty until one is signed off. In the meantime the mechanism above is the honest version.
Better numbers on every metric you report
Containment, average handle time, first-contact resolution and CSAT all move for the same reason: the customer stops repeating themselves, and your agents stop searching for answers.
- Start with one module
- No rip-and-replace
- Hosted in the region you choose
Illustrative interface. The figures are sample data from a demo tenant — not a benchmark, a containment rate or any other performance claim. The screen shows an OptiML analytics overview for a customer-experience leader: containment, average handle time, first-contact resolution and quality-score tiles above a weekly conversation chart splitting volume contained by AI agents from volume handed to human agents.
What the platform measures for you
Not a sample, not a survey response rate, and not four tools that count the same thing three different ways. One conversation model underneath every number on this page.
What you're measured on
Six numbers decide whether the year went well. Each one moves for a mechanical reason, and the right-hand column names that mechanism instead of implying it.
| Metric | What OptiML changes |
|---|---|
| Containment | AI agents resolve end to end, grounded in your own content, rather than deflecting to a form |
| Average handle time | The copilot has the answer before the agent finishes reading the question; context arrives with the handover |
| First-contact resolution | Cross-channel history means the second contact isn't a repeat of the first |
| CSAT / NPS | Surveys run automatically post-interaction and feed the improvement loop |
| Cost per contact | One platform instead of six licences, with a provider router that puts a floor under AI spend |
| Quality coverage | 100% of interactions scored on 15 dimensions, not a manual sample |
What changes in your week
- You stop reconciling numbers from four tools that count things differently.
- Coaching conversations start from evidence rather than from the three calls someone had time to review.
- The emerging issue surfaces in topic mining in week one instead of in the monthly review.
- The board question “what is AI doing for us” has a report behind it.
The parts of the platform that move those numbers
Every one of these is included in the platform rather than licensed alongside it, and they all read from the same conversation record.
Knowledge & grounding
Hybrid retrieval with citations and a groundedness gate before the agent speaks. KnowledgeAgent Desk
Live copilot, customer 360, call controls and AI wrap-up in one workspace. Agent DeskQuality management
Every interaction scored on 15 dimensions, with calibration and coaching plans. QualityAnalytics & reporting
76 reports, custom dashboards, topic mining and full-text conversation search. AnalyticsChat & omnichannel
Eight channels, one universal inbox, shared routing, memory and analytics. OmnichannelVoice AI agents
Real-time voice with barge-in, provider failover and mid-call language switching. Voice AIBefore it reaches a customer
These are the four things a CX leader is asked about in the first review. Each one is answered by how the platform is built, not by a roadmap slide.
Grounded, or it says so
A groundedness gate blocks an ungrounded answer before the agent speaks, and every answer carries a citation to the source it came from.
Scored, not sampled
Every interaction is evaluated on 15 dimensions, AI-handled and human-handled, voice and chat. The result becomes a coaching plan.
Run by us, in your region
OptiML runs in OptiML Cloud, provisioned in the region you choose and operated, patched and scaled by RMT against a 99.9% monthly uptime commitment.
Live in 6–11 weeks
Standard time to go-live is 6–11 weeks across five phases, and you can start with one channel or one queue.
Objections you'll hear, answered
These three come up in every evaluation, usually from someone who was right to be sceptical the last time. Each answer is about architecture, not enthusiasm.
“Our customers hate bots.”
They hate menu trees and scripted deflection. A voice agent is a different experience if the caller can interrupt it mid-sentence, if it answers from your actual policy with a citation, and if it hands over to a human with the full context. The groundedness gate means it says “I don't know, let me get someone” rather than inventing.
“We tried AI and it hallucinated.”
Ungrounded AI does. Retrieval-grounded AI is a different architecture, not a better prompt: a groundedness gate before it speaks, a hallucination grader, a citation auditor and 15-dimension scoring on every answer.
“This is a two-year migration.”
Standard go-live is 6–11 weeks across five phases. You can start with one channel or one queue and expand, on the same platform.
Where this goes next
The same argument, read from the seat next to yours. The customer story will sit here once a named customer has approved it in writing.
Customer quotes and outcome numbers need written approval from the named customer, so this slot stays visibly empty until one exists. An invented one would be worse than the gap.
BPO Operations
The same platform read as margin per programme, per seat. BPO OperationsCustomer Service Leader
Deflection, time to resolution and the knowledge gap loop underneath them. Customer Service LeaderContact Centre solution
The whole operation on one platform — desk, supervision, workforce, quality. Contact CentreThe platform underneath
Everything on this page is the OptiML CX Platform configured for Head of CX, not a separate product. These are the modules it leans on.
See it handle one of your real conversations
Bring a call recording, a policy document or a WhatsApp thread from your own operation. We ground an agent in it and run it live on the call — not a canned demo.
- 30 minutes
- A working agent grounded in your content
- No slide deck unless you want one
Book a demo
30 minutes, on your own content. No slide deck unless you want one.
Your details stay private. We never share them.