Training programme
A practical programme in cloud contact centres — how contacts are routed, how cases and customer records hang together, and where AI genuinely helps. Taught by consultants who build these systems for a living, using the same patterns we ship to clients.
Takes two minutes · nothing is charged until dates are agreed
Per seat, in US dollars. Every format covers the same material at a different depth, so the price per module barely moves — what changes is how much lab time and supervision sits around it.
Two-day intensive
2 days · 12 hours
$1,100
per seat
Modules 1–4 · $275 a module
One-week practitioner
5 days · 30 hours
$2,400
per seat
All 9 modules · $267 a module
Four-week part-time
4 weeks · 2 evenings a week
$2,200
per seat
All 9 modules · $244 a module
Career track: CCaaS and the AWS estate
4–6 months · part-time
$4,999
per seat
All 9 modules, the surrounding AWS services and a supervised build
$395 for one module taken on its own, lab included.
$22,000 for your team, up to 12 people — about $1,833 a head at full capacity.
Cohorts in Africa and other markets are quoted per client rather than at list price. Ask and we will price it properly.
Prices exclude AWS usage. Labs run in your own account, so the cloud spend is yours and typically small — a claimed number and a few hours of Connect, Lambda and storage. Nothing is charged until dates are agreed in writing.
Each module opens with the pattern as we build it for clients, then hands you the console. Nothing is demonstrated that you don't rebuild yourself the same day. Which modules a cohort covers depends on the duration you choose.
01
Claimed numbers, hours of operation, prompt management, the Contact Control Panel your agents will live in, and where recordings and logs actually land. You take a real call on day one.
Lab 01
Claim a number, point it at a flow, and route a live call to your own softphone.
45 min · your sandbox
02
DTMF menus and Lex intents side by side, the no-match and timeout branches most flows never wire up, and storing what the caller told you as contact attributes you can read later in the journey.
Lab 02
Build a three-branch menu with a Lex intent and a fallback that doesn't strand the caller.
90 min · peer review
03
Routing profiles, queue priority and delay, agent hierarchies, and how a service level of 80/20 turns into concrete decisions about overflow. We break a queue on purpose and read the damage in real-time metrics.
Lab 03
Two queues, one routing profile, and demonstrable overflow under a generated call load.
2 hr · load generated
04
Case templates and layouts, linking a case to the contact that raised it, and customer profiles as the thing that stops people repeating themselves. The difference between the record and the work.
Lab 04
Raise a case from a contact, link the two, and open it in the agent workspace.
90 min · your sandbox
05
A Lambda-backed customer lookup, attributes passed into the flow and onto the agent's screen, timeout budgets, and the error branch nobody tests until it fires at two in the morning.
Lab 05
Screen-pop a customer record from a records table inside an eight-second budget.
2 hr · pairs
06
After-contact work, dispositions, Contact Lens categories and sentiment, and the difference between a real-time dashboard a supervisor genuinely uses and a historical report nobody opens.
Lab 06
Flag a call by category, then chart the category against handle time the same afternoon.
90 min · your data
07
Deflection, call summarisation and agent assist, each measured against containment, handle time and CSAT rather than demo appeal. Includes the three places we have watched teams spend budget on AI and get nothing back.
Lab 07
Score one of your own use cases against the deflection arithmetic before you fund it.
60 min · bring a case
08
Self-service across voice, chat, email, SMS, WhatsApp and Apple Messages. Agents that resolve an issue end to end, hold context across channels, act only within set boundaries, and bring in a person with the full history. Grounding in approved content, deterministic steps for identity and payment, and guardrails on what may be said.
Lab 08
Take one containable intent end to end, then force the escalation path and check nothing is repeated.
2 hr · pairs
09
The no-code canvas where conversational applications are built: flows and nodes, slots and variables, deterministic logic beside generative and agent nodes, knowledge bases, integrations and guardrails. Build, test, deploy to an environment, observe and improve — plus how a Connect flow hands a contact into an application, and how a flow becomes a tool an agent can call.
Lab 09
Build an application on the canvas, put a guardrail on it, deploy it to an environment and read the transcripts back.
2 hr · your sandbox
What a cohort leaves with is the thing they built and the material to keep building. The deliverables below apply to the practitioner and longer formats.
The flows, queues and Lambda functions you build stay in your own AWS account when the course ends.
The same pre-flight and go-live checklists our consultants work from on client engagements, yours to adapt.
Bring a flow from your own estate on the last day and we take it apart with the cohort.
A shared channel after the course, answered by the consultant who taught your cohort.
PrerequisitesAn AWS account with administrator access to a sandbox, a headset, and enough console familiarity to find IAM. No prior Amazon Connect experience is assumed.
Four formats cover the same material at different depths. This is a registration of interest, not a booking or a payment — we confirm dates, pricing and joining details with you by email before anything is committed. If none of the four is quite right, say so in the last box and we will work around it.