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Dunamis Consulting Inc DCX Inc. helps organizations design, implement, and optimize cloud contact centers.

"Pe*******on of AI-answered calls on our network is still very small percentage-wise."That's RingCentral's CEO on their ...
10/31/2026

"Pe*******on of AI-answered calls on our network is still very small percentage-wise."

That's RingCentral's CEO on their latest earnings call, from a vendor whose AI Receptionist is now in 22,000+ customers. If the loudest AI seller says adoption is shallow, believe them.

The more you know: the 2026 earnings calls from eight CX vendors tell the same story. Customers buy AI one narrow job at a time. Missed calls. Password resets. Call analytics. RingCentral's AI Receptionist grew 4x by answering missed calls and capturing leads. Five9 customers start on password resets. A bank now resolves 70% of chat interactions with AI alone. Meanwhile RingCentral's own CEO admits AI answers "very small percentage" of calls on their network.

The myth: AI adoption means autonomous agents handling everything.
The fact: the winning deployments started with one boring, high-volume job.

How we help, the prove-it-first playbook:

1. Pick one narrow, high-volume job. Missed calls, password resets, call summarization. Where volume is high and stakes are low.

2. Prove the return before you expand. Vendors report customers who start with one AI product expand their investment multiple times, but only after the first job earns it.

3. Save the complex work for later. Multistep, regulated and autonomous workflows are where vendors themselves say the industry still struggles. Financial services and healthcare still need humans in the loop.

4. Don't skip the foundation. The same vendors report deployment teams, professional services and clean data are the real constraint. Budget for people, not just licenses.

Metric to watch: resolution rate on your first AI job versus the human baseline. If it can't beat or match people on a simple task, it's not ready for a complex one.

How we help: selecting, sequencing and staffing your first AI use cases, with the deployment capacity to actually get them live, 15 years tool-agnostic, including Genesys Cloud.

If you're picking your first AI use case now, DM "NARROW" and we'll share how the teams that got it right started.

Half the cloud you committed to may be doing nothing but collecting invoices.The more you know: Infosys research found t...
10/31/2026

Half the cloud you committed to may be doing nothing but collecting invoices.

The more you know: Infosys research found telecom companies consume only 48% of the cloud capacity they have committed to. They pay for 100% of it.

And this is the industry that runs networks for a living. Inside enterprise telephony and contact center estates, the same pattern shows up as committed-but-idle capacity: licenses provisioned for peak that never peak, environments left running after the project ended, and over-provisioned trunking and storage sized for demand that moved.

The real problem is not waste. It is blindness. Committed spend is contractual, so it disappears from the operating conversation. Nobody questions a line item that is already signed, even when half of it does nothing.

What to do:
- Pull your committed telephony, CCaaS and cloud spend in one place, including minimums and prepayments.
- Measure actual consumption against commitment by service, site and environment.
- Find the idle: dormant environments, provisioned seats nobody logs into, capacity sized for yesterday's peak.
- Rebalance at renewal. Convert what you can to right-sized commitments, and put consumption alerts on the rest.
- Make utilization a standing metric, not a one-time audit.

Metric to watch: utilization against commitment, tracked by service and environment. If it sits far below 100% quarter after quarter, you are not buying capacity, you are paying rent on it.

How we help: cost analysis and consumption audits across telephony, CCaaS and supporting cloud estates, 15 years in cloud telephony, tool-agnostic.

DM "COMMITTED" for the audit starting point.

The holiday arrived at midnight. Your phone system didn't get the memo. 📅The more you know:📌 Holiday hours live in more ...
10/31/2026

The holiday arrived at midnight. Your phone system didn't get the memo. 📅

The more you know:
📌 Holiday hours live in more places than anyone remembers: the IVR, branch greetings, agent schedules, your website and your Google Business Profile.
🎯 When even one of them is out of date, members hear three different versions of the same answer, and trust erodes quietly.
📆 One calendar, one source of truth: publish hours once, then push them to every greeting, queue and schedule at once, across every branch.
⚠️ The dangerous entries are the expired ones. Last year's hours that were never deactivated answer confidently... until they don't.
🧪 The week before any holiday, test every entry point the way a member would: main line, branch line, after-hours, and the voice or chat assistant.

Metric to watch: calls answered with a holiday message that contradicts the hours published on your website or Google listing. Every one is a member who showed up to a closed door or called back twice.

How we help: Dunamis Consulting builds holiday and seasonal scheduling into your cloud telephony platform from day one, so hours are managed centrally and every branch, IVR and greeting stays in sync. Modernize cloud telephony and customer experience, end to end.

Learn more at getdunamis.com

The more you know: during an outage, silence isn't neutral. If customers hear nothing for two hours, they assume the wor...
10/31/2026

The more you know: during an outage, silence isn't neutral. If customers hear nothing for two hours, they assume the worst, then they call, twice.

The opposite problem is just as real: 40 updates in a day and your message becomes noise customers stop reading. Trust lives in the rhythm between those two.

The fix is a communication cadence designed before the storm, not improvised during it:

📣 First update fast, even if the only honest message is "we know, and we're working on it"
⏱️ Updates on a predictable rhythm: every 30–60 minutes during active restoration, so customers stop refreshing and calling
📱 Same news everywhere: IVR, SMS, app and status page say the same thing, so no channel contradicts another
🌤️ Wind-down updates too:"power's restored to 95%" prevents the calls from the 5%
🧭 Honest ETAs or none at all: a wrong restoration time costs more trust than no time at all

How we help: Dunamis builds outage-communication cadences into the cloud contact center, proactive notification triggers tied to outage events, consistent messaging across voice, SMS and digital channels, and IVR that reflects the latest status so customers don't have to call to find out what's happening.

Metrics to watch: inbound "just checking" call volume during events, update cadence adherence, and sentiment on restoration communications.

If your updates only happen when someone remembers to send them, let's talk: https://getdunamis.com

Modernize cloud telephony and customer experience, end to end.

A complaint clock starts the moment the customer dials. Does anyone own it?The more you know: In financial services, a v...
10/31/2026

A complaint clock starts the moment the customer dials. Does anyone own it?

The more you know: In financial services, a verbal complaint is a regulated event with a deadline attached. When intake lives in a queue, notes in an agent's notepad, and follow-up in someone's memory, the clock runs quietly and the first real handoff happens after the due date is already at risk.

How we help: Treat the phone channel as a formal intake route. Classify the interaction at the point of capture, so a complaint is tagged the moment it is spoken, not weeks later during review. Route it to one named case owner with a documented acknowledgement, and record the complaint date, category, and root-cause area in the same step. Give agents a short, consistent script for acknowledging the complaint and stating what happens next. Keep a single ticket trail that links the call recording to the case, so the customer is never asked to explain the same issue twice. Make resolution steps and the next customer contact due date visible to everyone who touches the case. Watch for repeat contacts on the same issue: they are the earliest sign a case is drifting.

A practical measure: the percentage of complaints acknowledged within one business day with a named owner and recorded deadline, plus the share resolved inside the regulatory window.

Future-proof this journey before the next due date slips. Visit getdunamis.com.

AI agents just got added to the org chart.RingCentral's October 2026 RingCX update extends live supervision, quality sco...
10/31/2026

AI agents just got added to the org chart.

RingCentral's October 2026 RingCX update extends live supervision, quality scoring, journey analytics and staffing forecasts to AI agents. The same tooling supervisors already use for people. One dashboard. One workforce.

The more you know: AI agents handle a growing share of customer conversations, but in most centers nobody "manages" them. No schedule. No scorecard. No forecast line. Their performance is invisible until a customer calls back frustrated.

How we help, a one-workforce operating model:

1. Put AI agents on the live view. If a supervisor can't see what the agent is handling right now, they can't intervene before the experience breaks.

2. Score every interaction against one rubric. Same quality standard for humans and bots, sentiment scored, compliance included.

3. Forecast both together. Plan AI and human capacity on one line (seasonal surges, overnight coverage, escalation handling) so schedules reflect the whole workforce.

4. Route on escalation data. One bank found AI-handled fraud disputes had the highest escalation rate of any intent, so they moved those calls straight to humans. First contact resolution went up.

Metric to watch: AI-to-human escalation rate by intent. Rising or lopsided escalations tell you which conversations belong with people from the first ring.

How we help: designing unified human-plus-AI operating models, quality frameworks and capacity plans across cloud telephony platforms, 15 years, tool-agnostic, including Genesys Cloud.

Want a quick sanity check on how you're supervising your AI agents today? DM "WORKFORCE" and we'll share a starting framework.

Every vendor says AI revenue is up. Few of them mean the same thing.The more you know: three earnings seasons, three def...
10/31/2026

Every vendor says AI revenue is up. Few of them mean the same thing.

The more you know: three earnings seasons, three definitions.
One vendor counts AI product revenue as a share of subscription revenue: 15%, about $39M in a single quarter.
Another reports $362M in AI ARR, a figure that includes a recently acquired AI business.
A third reports $400M+ in AI ARR, defined as the total ARR of any customer who bought at least one paid AI product. The customer counts. The AI spend may be small.

Same headline stat, three different numbers behind it. Benchmark vendors on these figures without reading the definitions and you are comparing apples to weather.

What to do:
- Ask what counts as AI revenue: product usage, customer adoption, or estimated attribution.
- Ask what the percentage is a percentage of. A share of subscription revenue and a share of total ARR are not the same base.
- Ask what is excluded, including acquired revenue and services.
- Let your own pilot data break the tie. Results on your journeys beat any disclosed number.

Metric to watch: the definition behind every AI claim you compare. If two vendors define AI revenue differently, the comparison is marketing, not math.

How we help: tool-agnostic platform assessments and cost analysis that separate disclosed claims from what will actually run in your environment, backed by 15 years in cloud telephony.

DM "BENCHMARK" for the vendor-claim checklist.

62% of UK companies say data sovereignty and privacy risks are the biggest factor slowing their AI projects in the publi...
10/30/2026

62% of UK companies say data sovereignty and privacy risks are the biggest factor slowing their AI projects in the public cloud.

Now put that number in a voice context. Every call recording, transcript and AI voice interaction your contact center generates is data with a location. And increasingly, regulators, boards and enterprise buyers are asking exactly one question about it: where does it live, and who can reach it? 🌍

The more you know: sovereignty used to be a data center decision. In the AI era it is a design decision. The new research behind that 62% stat, plus a wave of sovereign cloud, AI and voice suites launching in markets like the UK, shows vendors responding to demand for workloads that stay in-country. But moving AI voice workloads into a sovereign environment is not a checkbox toggle. It changes what you can process, where, and with which models.

What to do:

1️⃣ Map your voice data residency today. Every recording, transcript, analytics feed and AI agent workload: where is it processed, where is it stored, which third parties touch it in transit? Most teams cannot answer this in one page. If you cannot, that is the finding.

2️⃣ Classify by sensitivity, not by system. Regulated voice data and high-stakes customer conversations may deserve region-pinned processing even when the rest of your stack does not. Blanket rules either overpay or under-protect.

3️⃣ Ask sovereignty questions in writing before you buy AI, not after. Where do model inference and training happen? Can processing be pinned to a region? What is the documented exit path if requirements change? Get the answers in the contract, not the demo.

Metric to watch: percentage of voice and AI workloads with a documented, contractually-backed processing location. If that number is low, your AI roadmap has a silent dependency that the 62% already flagged.

How we help: we assess data flows, platform architecture and vendor readiness for cloud telephony and AI voice programs, 15 years, tool-agnostic.

Planning an AI voice rollout with residency requirements? DM "RESIDENCY" and let's talk. 🔒

Before you say hello, do you know who's calling?Sharing caller details with the person who answers means a returning cus...
10/30/2026

Before you say hello, do you know who's calling?

Sharing caller details with the person who answers means a returning customer isn't asked to repeat their name, account, or reason for calling. A little context at the start of a call can shape the whole conversation.

Dunamis Consulting brings 15 years of cloud telephony experience to helping businesses connect their phone system to the information their teams already use.

If your team answers calls cold today, let's talk through a better start.

Your team isn't always at the same desk. Your business number shouldn't be either.When a colleague works from home, a cl...
10/30/2026

Your team isn't always at the same desk. Your business number shouldn't be either.

When a colleague works from home, a client site, or a different office, customers calling the business line still expect to reach them. A cloud phone system lets the same number follow the person, so calls land in the right place without a customer having to try twice.

Dunamis Consulting brings 15 years of cloud telephony experience to helping businesses set up calling that fits how their teams actually work.

If hybrid work is part of your week, let's talk through what your phone setup needs.

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