Project overview
Project overview
We built an automation platform that sits above day-to-day work as the operational layer: processes, channels, and systems resolve into one model of state, ownership, and handoffs.
The platform delivers:
- Orchestrated workflows across departments—not isolated scripts
- A single integration spine for CRM, messaging, databases, and APIs
- AI at decision and intake points, governed and auditable
- One operator control surface for visibility, monitoring, and intervention
Manual work was removed from the critical path where the model allows; everything else is visible, owned, and traceable in one system.
Delivery
How we delivered
Concrete ownership, scope, stack, and team structure—so this reads as shipped work, not a concept deck.
Our role
Draxon owned the platform as a product: workflow and domain modeling, orchestration design, integration contracts for CRM and messaging, operator UX for monitoring and exception handling, and staged rollout with production sign-off on critical paths—not a series of disconnected automations.
Project scope
- Orchestration: cross-team workflows with explicit state, ownership, SLAs, and audit—not isolated triggers.
- Integration spine: CRM, messaging, internal databases, and APIs behind versioned contracts and retries.
- Governed AI at intake and routing: classification and first-line handling with escalation and lineage.
- Operator control surface: queues, aging, exceptions, and drill-down from one console.
- Extensibility: new processes and channels attach without forking the core model.
Technologies used
- Next.js / ReactAuthenticated operator UI; density and hierarchy tuned for control work.
- TypeScript APIsIntegration boundaries, webhooks, and typed events across backends.
- Orchestration servicesState machines, assignments, monitoring, and durable execution.
- AI servicesPolicy-bound assistance at decision points; review paths where risk requires it.
- PostgreSQL + queuesOperational truth, outbox-style handoff, backoff and observability.
Team involvement
- Draxon: delivery lead, senior engineers, integration and QA on workflow regressions.
- Client: operations leadership for acceptance; IT for identity, hosting, and connector constraints.
- Cadence: pilot workflows first, then harden monitoring and expand coverage.
Context
The challenge
Operations ran on manual handoffs and tools that did not share a single picture of work.
The cost showed up as:
- Work routed through people because nothing owned the full workflow
- Slow cycle times where queues had no accountable owner
- Fragmented systems with no spine—every integration a one-off
- No reliable view of pipeline health, exceptions, or aging
- Process drift: the same work executed differently across teams
Scaling meant adding headcount, not tightening the system. That does not survive competitive pressure.
Strategy
Strategic approach
We treated the engagement as a product: an automation and control layer with explicit boundaries—not a bundle of features.
The plan:
- Map end-to-end workflows and replace manual steps with orchestrated execution where safe
- Introduce AI at structured decision and intake points—with escalation rules, not open-ended autonomy
- Centralize integrations behind stable contracts so channels and backends plug into one spine
- Ship one operator UI for monitoring, assignment, and exception handling
- Design for change: new workflows attach without rewriting the core
The architecture is built to absorb roadmap pressure without fragmenting into parallel tools.
Orchestration
Workflow orchestration
The spine of the system is orchestration: triggers, dependencies, assignments, and state that span teams. Automations are not isolated; they chain into processes that match how the business actually runs.
The layer includes:
- Cross-team pipelines with explicit state—not ad hoc task lists
- Automated assignment and handoffs tied to rules and SLAs
- Live monitoring: what is running, what is stuck, what breached
- CRM and internal tools as participants in the same graph of work
When orchestration is correct, execution gets faster because the system—not email—carries responsibility between steps.
CRM & systems of record — when orchestration must persist state beyond messaging.
Architecture
Integration spine
External systems plug into a single integration layer. The business does not operate out of five consoles; operators work from one control plane while data and events flow through governed connectors.
Connected domains include:
- CRM and line-of-business APIs
- Telegram, WhatsApp, and messaging endpoints
- Internal databases and services
- Webhooks and API contracts with versioning discipline
The platform is the hub. Integrations are adapters—not the product story.
Channels
Intelligent intake & channels
Customer-facing and internal channels feed the same orchestration layer. AI classifies, routes, and responds where policy allows; everything else escalates with context—no separate “bot product” off to the side.
In production this means:
- Intake that lands in workflow state—not unmanaged inboxes
- Routing and qualification tied to CRM and ownership rules
- Consistent responses where policy is fixed; human handoff where it is not
- Full lineage from first touch to resolution in one system
Channels are entry points into operations. They are not the platform—they feed it.
AI & automation practice — governance, routing, and production guardrails.
Product
Operator control surface
Teams do not switch tools to understand what is happening. The interface is built for operations: state, queues, exceptions, and drill-down—minimal chrome, high signal.
Design rules:
- One place to see pipeline health and aging work
- Workflow state you can trust—no shadow spreadsheets
- Fast paths for assignment, override, and audit
- Density tuned for long sessions under load
This is how the organization runs the system—not a marketing layer bolted on top.
Enterprise web & product UI — operator-grade surfaces for long sessions.
Outcomes
Business impact
Outcomes follow when manual execution leaves the critical path and work becomes observable:
- Lower operational load on teams previously acting as routers
- Faster end-to-end execution—fewer waits between owned steps
- Consistent handling: the same workflow rules apply across regions and shifts
- Scalable operations: new volume attaches to orchestration, not headcount linearly
- Infrastructure that extends with new processes without a ground-up rebuild
FAQ
Frequently asked questions
Orchestration, integrations, and control — scope questions we hear on similar programs.