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Language: English
Demo

Calculators

Is your contact center ready for AI agents?

Answer ten questions about your data, channels, processes, team, and infrastructure. The assessment shows your readiness level and the areas to improve before you launch AI agents.

Questions

Answer 10 questions

  1. Do you know your top 10 contact reasons and their share of volume?
  2. Where do agents look for answers to customer questions?
  3. How many channels do you support, and are they in one place?
  4. Do your systems – CRM, booking, billing – have an API?
  5. Are frequent requests handled the same way every time?
  6. Do you measure service level, handle time, and first contact resolution?
  7. How do you check conversation quality?
  8. How does your team feel about automation?
  9. What phone system do you use?
  10. What are your requirements for storing customer data?

Result

How the assessment works

Each answer scores 0 to 3 points in one of five areas. Your total shows your readiness level and the stage you're at. The two areas with the lowest share of points are your first priorities.

Takeaways

What to do with your result

  • Stages 1-2: start measuring key metrics, and run one narrow pilot workflow.
  • Stage 3: launch AI agents on frequent requests, together with integrations.
  • Stage 4: add real-time suggestions for agents and speech analytics on every conversation.
  • At any stage, estimate the impact with the AI agent savings calculator.

More

Where to use it

Knowledge base Collect answers in one place for both agents and the AI agent Learn more Omnichannel inbox Handle every channel in one window with a shared customer history Learn more Voice AI agent Hand your frequent calls to an AI agent Learn more Chatbots Answer customers in messaging apps 24/7 Learn more AI assistant for agents Get suggestions during the conversation Learn more Speech analytics Score every conversation against a QA scorecard Learn more

Glossary

Terms on this page

API (application programming interface)
The way programs exchange data with each other without a person in the loop. Learn more →
Knowledge base
All answers, policies, and prices in one place – for agents and AI. Learn more →
Speech analytics
The system analyzes recorded calls automatically: topics, script adherence, customer emotions. Learn more →
IP PBX
A company phone system that runs over the internet and your local network. Learn more →
IVR (interactive voice response)
A phone menu: the caller hears a greeting and picks the right department. Learn more →
Call queue – callers waiting to be answered
Callers waiting for an available agent. Learn more →
CRM – customer relationship management
Where a company keeps its customers, deals, and full communication history. Learn more →
Service level (SL)
The share of calls answered within a set time – for example, 80% in 20 seconds. Learn more →
FCR – first contact resolution
How many issues get resolved the first time, so the customer doesn't have to call again. Learn more →
Supervisor
Leads a team of agents: watches the queue and quality, helps and coaches. Learn more →
Cloud deployment (cloud)
The platform runs on the vendor's servers, and agents connect over the internet. Learn more →
Call recording
Calls are saved so they can be replayed and disputes settled. Learn more →
Data center
A building with servers, backup power, cooling, and network links. Learn more →
Omnichannel customer service
All channels in one agent workspace, with the customer's full history alongside. Learn more →
Chatbot
Answers customers in chat and messaging apps from a scripted flow with buttons. Learn more →

Blog

From the blog

All articles →
AI agents · 8 min read What an AI voice agent can and cannot do in a contact center today What an AI voice agent really handles in a contact center, where it still gets things wrong, and how to launch one: use cases, integrations, and handoff. Read the article → Services · 7 min read Custom development of your contact center platform for your processes When contact center settings are not enough: integrations, modules, AI workflows. How to tell development from configuration and estimate the payback. Read the article → Management · 9 min read How many agents does your contact center need? Erlang C in plain English Calculate contact center staffing with Erlang C: workload, service level, shrinkage, and headcount by shift – all in one worked example. Read the article →