When a process is repeatable, it should not depend on a person to repeat it.
Production-grade workflow automation for regulated environments. Custom pipelines, multi-point validation, third-party integrations, and the compliance layer built in from the start.
WHAT IMAGEPLUS AUTOMATES
Any process where the rules are knowable.
FIG · 01 · AUTOMATION LANDSCAPE
Any process where the steps, conditions, and validation points can be defined precisely.
HOW IMAGEPLUS BUILDS PIPELINES
Three principles. Applied to every pipeline.
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01 · Map the process before automating it
A pipeline built on a process that was never mapped properly will automate the wrong thing. Every engagement starts from the process as it actually runs, not as it was described in the kick-off meeting. We use BPMN 2.0 notation, the shared language between business and technical teams that makes the automation defensible, documented, and auditable from day one. Forward Deployed Engineering is where that mapping happens.
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02 · Multi-point validation by design
Regulated processes need checkpoints. Identity verification before contract execution. Stock validation before release. Human sign-off before a critical step proceeds. Those gates are designed into the pipeline from the start, not enforced by hope.
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03 · Third-party complexity handled cleanly
Identity verification, contract signing, external authentication, supply chain partners. Where a third party is part of the process, the pipeline is built to accommodate that relationship without creating a fragile dependency.
AI-ASSISTED PIPELINES
Where AI is part of the workflow, the same rigour applies.
One production system running multiple AI models with separation of duties across them for quality control, AI output guardrails, human-in-the-loop gates, full logging, and documentation that meets EU AI Act requirements. Not a prototype. What regulated AI automation looks like in production.
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Separation of duties
One model produces. Another validates. The guardrails enforce the boundaries. No single model has unchecked authority over the output.
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Human-in-the-loop
Where a human decision is required, the pipeline waits for it. The gate holds under load, by design.
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Full logs and documentation
Every call, every output, every decision point is recorded. The audit trail is complete. The deployment is defensible.
THE FOUNDATION
Every pipeline ships with the same operational baseline.
Each engagement inherits what it requires. The cryptographic audit trail comes on for regulated work. The SLA comes on where uptime is the commitment. The rest is standard.
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Monitoring
The pipeline is watched end to end. Failures surface immediately.
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Error handling
When something fails, it fails cleanly. The state is recoverable. The team is notified.
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Cryptographic audit trail
Where the engagement calls for it, every step is cryptographically signed and traceable.
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GDPR compliance
Data handling designed to meet regulatory requirements at every point in the flow.
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Defined RTO/RPO
The organisation knows exactly what happens if a pipeline fails and how long recovery takes.
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SLA
Service level agreements available on all engagements, subject to separate arrangement.
HOW IT CONNECTS
Automation rarely stands alone.
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Forward Deployed Engineering
Every automation starts from the process as it actually runs. The FDE method and BPMN mapping happen before the pipeline is built.
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Platform integrations
Pipelines connect systems. Where the integration layer needs to be built or extended, the two engagements run together.
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AI orchestration
Where the pipeline includes AI, the orchestration layer manages the models, the guardrails, and the governance.
Tell us which process should not depend on a person to run it.
We will tell you what the pipeline would look like and what it would take.
COMMON QUESTIONS
Asked before starting.
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What kinds of workflows do you automate?
Any process where the steps, conditions, and validation points can be defined precisely. Compliance pipelines, onboarding workflows, stock management, document processing, AI-assisted pipelines with human oversight. If the process is repeatable and the rules are knowable, it can be automated.
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Why do you use BPMN 2.0 before building a pipeline?
BPMN 2.0 is the shared language between business and technical teams. It makes the process mappable with precision before a line of code is written, and it produces documentation that makes the automation defensible and auditable. A pipeline built on a process that was never mapped properly will automate the wrong thing.
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What is multi-point validation and when is it required?
Multi-point validation means the workflow enforces checks at defined stages before proceeding. Required wherever a process has regulatory, compliance, or quality requirements that cannot be skipped. The validation points are designed into the pipeline, not added afterwards.
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Can you automate workflows that involve third-party systems?
Yes. Third-party authentication, identity verification, contract signing, and external API calls are all part of the automation landscape. Where a third party is the client's own client, the pipeline is designed to accommodate that relationship cleanly.
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What is separation of duties in an AI pipeline?
Separation of duties means different models handle different roles in the pipeline. One model produces. Another validates. The guardrails enforce the boundaries. No single model has unchecked authority over the output. Required under the EU AI Act for high-risk AI systems.
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Do you build on no-code tools or custom code?
Both, depending on what the pipeline requires. Regulated, complex, or high-stakes pipelines are built as custom code on our modular foundation. Where a tool like n8n fits the requirement, we use it. The decision is made by what the pipeline needs to do and what it needs to survive, not by what is fastest to configure.
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Is an SLA available?
Yes. Service level agreements are available on all workflow automation engagements, subject to separate arrangement.