Canarlo
AI Automation

AI-Driven Operations & Workflow Automation Platform

Representative Engagement — Internal Systems & Automation

Overview

A growing services-based business was struggling to scale its operations. As client volume increased, core workflows relied on a mix of spreadsheets, inboxes, and disconnected third-party tools — creating bottlenecks, manual errors, and limited visibility.

Objectives

Replace spreadsheet- and inbox-driven workflows with a unified internal system

Automate high-frequency operational tasks using AI-assisted decision logic

Integrate multiple third-party services into a single orchestration layer

Provide real-time visibility into workflow state, throughput, and exceptions

Design a scalable architecture that could expand without rewrites

Our Approach

We approached the problem as a systems design challenge, not a tooling exercise. Rather than stitching together automation tools, we designed a central orchestration layer responsible for ingesting inputs, validating data, coordinating workflows, and applying AI-assisted logic where human judgement previously slowed execution. Automation was treated as infrastructure — built with the same care as a production SaaS platform. Every workflow was designed to be observable, extensible, and resilient by default.

Engineering Highlights

Focus AreaWhat We Delivered
Workflow OrchestrationCentralised task engine coordinating multi-step workflows across internal and external services
AI Decision LayerAI-assisted classification, prioritisation, and routing for complex or ambiguous inputs
Integration LayerAPI-based connectors to CRM, email, billing, and external data providers
Validation & GuardrailsSchema validation and rule-based checks preventing invalid state propagation
ObservabilityReal-time dashboards for task status, failures, retries, and throughput
ScalabilityEvent-driven architecture supporting horizontal scaling under load

Outcomes

70–80% reduction in manual operational workload

Faster turnaround times for inbound and internal processes

Consistent decision-making through structured AI-assisted logic

A single source of truth for operational state and workflow progress

Improved reliability through validation, retries, and observability

Ability to scale operations without proportional staff growth

Business Impact

By replacing fragmented processes with a unified automation platform, the business gained operational clarity and leverage. Teams were able to focus on higher-value work while the system handled routine execution, coordination, and error handling. New workflows could be added incrementally, allowing the platform to evolve alongside the business rather than becoming a bottleneck.

Reflection

This project illustrates how intelligent automation and systems thinking can transform internal operations from a growth constraint into a competitive advantage. By treating workflows as first-class infrastructure — supported by AI where appropriate and protected by validation and observability — we delivered a platform that scales quietly, reliably, and without increasing complexity. This same systems-first approach underpins how we design and deliver AI-powered SaaS and internal platforms at Canarlo.

Related Capabilities

Workflow AutomationInternal PlatformsAI OrchestrationSystems ArchitectureOperational Tooling

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