Workflow discovery
Map systems, people and exceptions. Establish a baseline for cycle time, quality and manual effort.
AI TRANSFORMATION
Make AI part of how your business operates.
Connected workflows. Accountable people. Measurable progress.
Redesign the work across your teams, data and systems, then put AI into the steps where it can make a practical difference.
Start where work slows down.
We follow a workflow from the first request to the final outcome. Together we identify repeated handoffs, missing context and manual coordination, then agree a focused opportunity and the evidence needed to judge it.
Your existing business is the starting point. Your people stay responsible for the decisions.
From opportunity to everyday operation.
Process and agent design
Define which steps agents can handle, what context they need and where a person must approve the next action.
Integration and rollout
Connect approved tools and data sources. Evaluate representative cases before a controlled production rollout.
Ongoing improvement
Review execution evidence, resolve failure patterns and expand only when the workflow is ready.
How an engagement runs.
Discover the opportunity
Choose a workflow, map its dependencies and agree success criteria with the people who own it.
Build and validate
Implement the integrations and agent behavior. Test normal cases, exceptions and human handoffs.
Deploy and improve
Roll out with monitoring, access controls and a runbook. Use operational feedback to guide the next change.
A clear scope from the start.
The detail follows discovery. The work begins with a shared understanding of the task and who owns each decision.
- Workflow discovery and opportunity assessment
- Process redesign and agent implementation
- System integration, evaluation and controlled rollout
- Monitoring, team enablement and operational handover
A few practical questions.
Do we need to replace our existing systems?
We begin with your approved tools and data. Any change to your stack is discussed and scoped around a concrete need.
How do you measure progress?
We agree a baseline and acceptance criteria before implementation. Depending on the workflow, these may cover cycle time, exception rates, manual effort or output quality.
Can we begin with one department?
Yes. A bounded workflow gives us a practical place to test the approach before considering wider adoption.
Customer stories from Amotion
Shared engineering experience from our sister company, with original attribution.
Customer storyBotree SoftwareDistribution management softwareAI Transformation · 7 minute read
How Botree automated documentation for large codebases using Claude
Botree worked with Amotion AI to create an AI-ready knowledge base in each repository using Claude Code.
- Claude Code documentation
- AI-ready codebases
- Repository knowledge bases
- Agentic SDLC
- Human review
Customer storyAutomatonsXEnterprise technology products and servicesAI Transformation · 4 minute read
How AutomatonsX brought agentic development into products and services
AutomatonsX worked with Amotion AI on ADLC, Claude Code, Linear and custom agents, supporting work across 20+ repositories and teams involving 100+ people.
- Agentic development lifecycle
- Claude Code
- Linear workflows
- Custom AI agents
- Human-in-the-loop systems
Customer storyHydralogicCodebase analysis and change planningAI Transformation · 4 minute read
How Hydralogic prepared complex codebases for change
Hydralogic worked with Amotion AI on MCP tooling, Claude Code plugins, documentation, FRDs and impact analysis before major code changes.
- Codebase impact analysis
- Claude Code plugins
- MCP server development
- Repository documentation
- Functional requirements documents
LET’S PUT AI TO WORK
Bring us the work that gets stuck.
One workflow. The systems it touches. The outcome you want to change. Let’s work out a useful first step together.
Discuss your workflow