EXPERTISE
Workflow & Automation Engineering
Redesigning the workflow before automating it, then orchestrating people, software, data and agents with the requirements of a production system.
Capabilities
Capabilities
From business context and decisions through to production: understand, architect, build, secure, industrialize and evolve without artificially separating information systems, software, data, automation and AI.
Workflow & Decision Redesign
Mapping and Process Intelligence/
Mining where logs allow it Decision Contracts
Human × Software × Agent allocation
Integrations/
APIs Rules
Human-in-the-loop
Exception design
Runtime
Retries/
idempotency Observability
Workflow registry and governance
Engineering approach
Designing what must remain under control.
Code, rules, Data or AI: technical choices serve the system’s needs.
Discover our approachEngineering approach
Low-code accelerates some workflows; code remains preferable for complex, extensively tested, high-performance or specialised components. The architecture must combine both while preserving governance and observability.
OUR ENGINEERING
Problem first
Decisions, processes, users, data, constraints and responsibilities before tools.
Production by design
Security, performance, availability, scalability, CI/CD, observability, rebuilding and maintainability shape the architecture from the outset.
Evidence before promise
Tests, metrics, traces, acceptance criteria, Evaluation, Verification and regression testing provide evidence of quality.
Technologies
Technologies
- Airflow
- BPMN
- Camunda
- GraphQL
- Kafka
- n8n
- Prefect
- Redis
- REST API
- Temporal
- Webhooks
Related work
Related work
Frequently asked questions
Frequently asked questions
Low-code or custom development?
Both. We use the level of abstraction suited to each component.
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LET’S TALK
Let’s discuss your challenge.