Loading…
Representative engagement · Internal systems & automation
Categorisation, summarisation, and triage automated across an operations team's daily workload. Graceful degradation when the model is unavailable — never hard-fail.
Outcome
10×
faster operations triage
Capabilities
The lede
A growing services-based business was struggling to scale operations. As client volume increased, core workflows relied on a mix of spreadsheets, inboxes, and disconnected third-party tools — bottlenecks, manual errors, limited visibility.
Objectives
Approach
A systems design challenge, not a tooling exercise. 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.
→ By replacing fragmented processes with a unified automation platform, the business gained operational clarity and leverage. Teams focused on higher-value work while the system handled routine execution, coordination, and error handling. New workflows could be added incrementally.
Engineering highlights
Workflow orchestration
Centralised task engine coordinating multi-step workflows across internal and external services
AI decision layer
AI-assisted classification, prioritisation, and routing for ambiguous inputs
Integration layer
API-based connectors to CRM, email, billing, and external data providers
Validation & guardrails
Schema validation and rule-based checks preventing invalid state propagation
Observability
Real-time dashboards for task status, failures, retries, throughput
Scalability
Event-driven architecture supporting horizontal scaling under load
Outcome
10×
faster operations triage
Reflection
Intelligent automation and systems thinking can turn internal operations from a growth constraint into a competitive advantage. Workflows treated as first-class infrastructure — supported by AI where appropriate, protected by validation and observability — scale quietly and reliably.
Further reading
SaaS Platform
A product-led business needed a SaaS that could support multiple frontends, partner integrations, and future expansion without repeatedly reworking core logic.
Read
Modernisation
A working platform that had outgrown its original architecture. Auth, data, and observability rebuilt without a service interruption — the customers never noticed.
Read
AI Platform
A documentation platform that reads code and emits prose a non-engineer can act on. Used internally on every Canarlo build.
Read