Johnny J · Zendesk Solutions & Systems Architect

Support operations designed to work as one system.

Zendesk architecture, ITSM, SLAs, AI, automation, custom applications, APIs, integrations and analytics, with hands-on work across Freshdesk, Jira, Gorgias and Intercom.

100+ Zendesk projects and platform engagements

Support + ITSM Customer support, internal service and engineering workflows

End-to-end Requirements, architecture, build, rollout and optimization

Native + custom Platform configuration, AI, APIs, apps and connected systems

Core platforms

Connected when needed

Automation & intake: Zapier, Typeform, Monday.com, ClickUp, Trello · CRM / commerce: Salesforce, Shopify · Collaboration / backend: Slack, Cloudflare, GitHub · Data: Google Sheets, Excel

What usually needs solving

The hardest support problems rarely belong to one setting.

They usually sit between process, people, platform behavior and connected systems. The architecture starts there.

Support has grown faster than the workflow

Routing, forms, ownership, priorities and SLAs have accumulated over time and are now difficult to understand, maintain or scale.

Agents spend too much time finding context

Customer, organization, product or operational information is spread across too many places, slowing down decisions and increasing handling effort.

Support and engineering do not stay in sync

Technical issues depend on manual handoffs, duplicated updates and constant status chasing between Zendesk and Jira.

Automation exists, but the operation is still manual

Rules overlap, repetitive work remains, or integrations fail without a clear recovery path.

Reporting exists, but does not answer the business question

The data is there, but the workflow and ticket structure were never designed around the decisions leadership needs to make.

AI is available, but needs boundaries

AI needs accurate knowledge, controlled escalation, testing and governance so automation improves support without introducing new risk.

Support operating architecture

Channels, routing, SLAs, agents and data should behave like one service system.

The strongest setups connect what happens before the ticket reaches an agent, what controls the service while it is active, and what the business learns after it is resolved.

Customer channels

Email Messaging Live Chat Social Voice / Talk Help Center

Intake & classification

Ticket Forms Custom Fields Intent Reason Codes AI Classification Custom Objects

Routing & service control

Omnichannel Routing SLAs Business Hours Priority Skills Capacity Queues Escalation Breach Management

Agent experience

Agent Workspace Views Macros Customer Context Organization Context Copilot Custom Apps

Resolution & collaboration

Jira Internal Teams Approvals Action Flows Human Handoff External Systems

Data & improvement

Explore CSAT WFM Voice Analytics Trend Analysis Data Reconciliation

Service control is the engine. Routing decides where work goes. SLAs define the service commitment. Priority, business hours, skills, capacity and escalation decide how the operation protects that commitment.

Business value

Better support architecture should create measurable operating leverage.

The exact metric changes by business, but the value usually comes from the same places: less manual work, less risk, faster resolution and better use of the systems already being paid for.

Lower cost-to-serve

Remove repetitive checks, duplicate handling and avoidable manual processing so agent time is used where judgment adds value.

Protect revenue & retention

Make important accounts, renewals, escalations and unresolved customer risk visible before they disappear inside a queue.

Resolve issues across teams faster

Connect support, engineering and operations so context and status move without constant manual chasing.

Increase agent capacity

Reduce context switching, repetitive actions and unnecessary ticket volume so the same team can focus on more valuable conversations.

Make reporting trustworthy

Structure the data from the workflow level so dashboards support staffing, service, customer and commercial decisions.

Get more from the platform investment

Use native capability well first, then extend the platform only when custom work removes a real constraint or operating cost.

Where ROI usually appears Avoided agent hours, fewer duplicate or unnecessary tickets, faster handoffs, better SLA performance, improved self-service, reduced operational risk and stronger retention visibility.

Proof of work

A few problems that needed more than another configuration change.

Client names and sensitive details are intentionally removed. The useful part is the problem, the system decision and what changed for the team using it.

AI, knowledge & agent experience

AI that can automate without losing the handoff.

Advanced AI work across email and messaging, including dialogue flows, structured reason codes, knowledge controls, model-specific troubleshooting and human escalation with useful context carried into the agent experience.

Client value: more automation coverage while keeping complex or high-risk conversations visible and actionable when an agent takes over.

Advanced AI · AI Agents · Copilot · Dialogues · Knowledge · Escalation · Governance

Support ↔ engineering

Zendesk and Jira working as one support-to-engineering workflow.

Support cases can create or link engineering work, pass the relevant technical context and keep workflow status aligned across both systems. The work also includes field synchronization, Jira automation, audit-log troubleshooting and OAuth / integration reliability.

Client value: fewer manual handoffs, less status chasing and better visibility for both support and engineering without forcing either team out of its primary workspace.

Zendesk · Jira · Auto Creation · Linking · Field Sync · Status Sync · Automation · OAuth

Zendesk Customer case, support context, ownership

→

Jira Engineering work item, technical workflow, status

→

Zendesk Status and engineering context returned to support

Automation, recovery & data quality

When an intake workflow fails, the missing records still need a safe path back.

External form submissions were traced through the automation chain, missing and failed records identified, historical entries reconstructed and replayed into Zendesk with reconciliation and duplicate controls.

Client value: restored operational records, cleaner reporting and a safer recovery process when external automation does not complete as expected.

Typeform · Zapier · Zendesk · Data Reconciliation · Recovery · Duplicate Controls

Typeform branching workflow connected to Zendesk

Operational analytics

Reporting built around the questions the business actually needs answered.

Operational dashboards and analysis across ticket volume, escalations, response activity, handling time, product or channel trends and replacement patterns, with the underlying support data structured so the output can be trusted.

Client value: clearer operational visibility, better trend detection and reporting that can support staffing, service and commercial decisions.

Zendesk Explore · Custom Metrics · Dashboards · Trend Analysis · CSAT · WFM

Custom applications

Small tools can remove surprisingly large support bottlenecks.

Custom apps are used where the agent experience, data model or operational workflow needs something more focused than another field, macro or browser tab.

Agent Notification Center

Brings customer replies, SLA breaches, action-required tickets and other important signals into one agent-side view.

Client value: fewer missed actions and less reliance on agents remembering where to look.

Bulk Workflow Execution

Applies a selected Zendesk macro across tickets in a view beyond the native 100-ticket limit, with a controlled job workflow.

Client value: less repetitive bulk processing and a faster way to handle large operational queues.

Organization Context Workspace

Surfaces selected organization data such as account tier, renewal details, partner status and internal notes directly where the agent is working.

Client value: better account-aware service with less navigation and stronger visibility into customer context.

Other custom work includes: AI Knowledge Dashboard for querying support data, intelligent duplicate / ticket consolidation workflows, structured operational applications backed by Zendesk Custom Objects, role-based application behavior, ticket-side support intelligence, and custom actions used inside broader Action Flow automation.

Architect-level depth

The parts that keep a support platform stable after launch matter just as much as the build.

Enterprise work is not only implementation. It includes governance, service control, reliability, data design and the decisions that keep the platform maintainable over time.

SLA & service management architecture

Business hours, service targets, priority, escalation, breach management, queue health and ownership designed together rather than as separate rules.

Voice / Zendesk Talk architecture

IVR, call routing, business hours, queues, voicemail, callback, agent status, abandoned calls, missed call legs and Talk reporting.

Knowledge & self-service architecture

Help Center structure, article visibility, request journeys, agent knowledge, AI retrieval and knowledge controls designed as one content system.

AI governance & production rollout

AI Agents, Copilot, knowledge, procedures, testing, human-in-the-loop escalation, permissions, evaluation and controlled production changes.

Data architecture & Custom Objects

Structured records, relationships, custom fields, Custom Objects, reconciliation, historical recovery and data quality designed around future workflows and reporting.

Security, governance & change management

Roles, permissions, authentication considerations, sandbox testing, dependency checks, rollout planning and safe changes across live environments.

Reliability, troubleshooting & RCA

Reproduce, isolate and trace complex issues across Zendesk, integrations, APIs, AI, scripts and connected services when the obvious configuration fix has already failed.

Action Builder & advanced automation

Native actions, third-party connectors, custom actions, API calls, branching, JavaScript transformations, human steps and failure-aware multi-system workflows.

Internal service management

Internal request forms, routing, approvals, specialist queues and service workflows that extend the platform beyond external customer support.

Documentation & enablement

Architecture notes, operating guidance, workflow documentation and practical handover so teams can understand and maintain what has been built.

Platform depth

Choose a platform to see where the work goes deeper.

Zendesk is the primary specialization. Freshdesk and Jira have substantial hands-on project work, while Gorgias and Intercom are supported for implementation, administration and workflow setup.

Connected services & supporting systems

Used as integration, automation, commerce, CRM, collaboration or backend services where the support workflow requires them, rather than presented as primary platform specializations.

Zapier Typeform Shopify Monday.com Salesforce Slack Cloudflare ClickUp Trello GitHub Google Sheets Excel

Where the work fits

Different industries, the same need for support operations that stay clear as complexity grows.

The portfolio reflects live environments across customer support, technical support, internal service and multi-system operations.

E-commerce & retail

Orders, returns, warranty, customer operations, Shopify-connected workflows and automation around high-volume support.

Consumer products & electronics

Troubleshooting, warranty, replacements, product-specific support, AI flows and structured investigation processes.

SaaS & IT support

Technical support, SLAs, Jira collaboration, escalations, AI, internal service and operational reporting.

Cybersecurity

Technical support architecture, support-to-engineering handoffs, service operations and workflow reliability.

Education & testing

Internal requests, compliance workflows, forms, validation, routing and CRM-connected operating processes.

IT consulting & managed support

Platform administration, optimization, reporting, integrations, ongoing support and multi-client operational environments.

Global support operations

Multi-region teams, WFM, timezone alignment, channels, routing, SLAs, voice and operational visibility across distributed support.

Client confidentiality: client names, logos and sensitive operating details remain private unless there is explicit approval to publish them. Industry and operating-model descriptions are used instead.

How projects move

Understand the operation first. Add complexity only when it earns its place.

The work starts by tracing the business process and the systems around it, then deciding what belongs in native configuration, automation, integration or custom development.

Map the operation

Understand the customer journey, support model, teams, ownership, service targets and the points where work is slowing down.

Design the system

Connect channels, data, routing, SLAs, automation, integrations and reporting before building isolated fixes.

Build & validate

Implement the solution and test normal paths, edge cases, permissions, failures, SLA behavior and downstream impact.

Stabilize & improve

Watch how the system behaves in live operations, remove noise and refine the architecture as the support model changes.

Native first where it works. Custom engineering is used when it solves a real platform gap, removes meaningful manual effort or creates a better support experience. Not simply because it is possible to build.