Lead qualification and sales routing
Turn inbound leads into a scored queue with missing-data flags and clear routing.
- Lead scoring with review steps
- Company enrichment and missing-data flags
- Clear handoff to sales or founders
AI workflow automation for real business processes
I design and build AI-assisted workflows that connect existing tools, move information between steps, and keep people in control of sensitive decisions.
A bounded workflow build, not a chatbot layer.
The first release connects the smallest useful set of systems, keeps consequential actions behind a named human decision, and leaves a clear operating record.
- Best fit
- A repeated process with a clear owner, stable inputs, visible exceptions, and a delay or rework cost worth reducing.
- First release
- One workflow, its integrations, review states, failure paths, and acceptance tests. Broader autonomy waits for production evidence.
- Commercial starting point
- First AI workflow builds start from €7,500. When scope or risk is still unclear, the workflow audit is €2,500 fixed.
Workflow automation use cases
Start with a workflow where repeated inputs, decisions, handoffs, or reviews slow the team down.
Proposal and client intake workflow
Extract requirements from calls, forms, and emails, identify missing information, prepare scope notes, and draft proposal structure.
- Requirements extraction
- Missing-information questions
- Proposal outline and internal scope notes
Support triage and knowledge assistant
Classify tickets, prepare sourced replies, and escalate issues that need human attention.
- Ticket classification and routing
- Suggested replies with sources
- Escalation rules for risky cases
Document processing and approval
Extract and validate document data, then route exceptions and approvals to the right person.
- Structured extraction with validation
- Exception queues for human review
- Approval status and audit trail
Reporting and operations summaries
Pull data from tools, summarize changes, identify anomalies, and prepare weekly updates for leadership and teams.
- Recurring summaries from live tools
- Anomaly and change highlights
- Status updates with source links
Decide what software, AI, and people should handle.
The build separates predictable rules from AI judgment and human decisions, then defines the data, tests, and failure behavior around each.
Human decisions
Customer commitments, sensitive changes, and uncertain outputs stay behind clear approval steps.
Deterministic rules
Validation, permissions, routing, and fixed business logic stay in ordinary software where predictable behavior matters.
Evaluation cases
Representative inputs define acceptable output, failure categories, and escalation behavior before launch.
AI tasks and limits
Extraction, classification, summaries, and drafts operate within clear instructions, model choices, and usage limits.
Data boundaries
Data exposure is minimized. Sensitive fields, permissions, and tool access are designed around the actual workflow.
Failure behavior
The workflow can pause, retry, or escalate when outputs are uncertain, tools fail, or rules change.
From approved scope to controlled production
Build one defined workflow, test it against representative cases, and increase responsibility only after the system behaves reliably.
Confirm the build boundary
Turn the audit or agreed brief into a defined first release: inputs, systems, owners, exceptions, and acceptance criteria.
- AI action
- Identify where AI adds useful judgment.
- Human checkpoint
- Approve scope, ownership, and review criteria.
- Output
- Build boundary and acceptance criteria.
Controls you can see in production
Once live, permissions, run history, alerts, and cost limits show what the system is doing and where the team needs to intervene.
- Data minimization and redaction
- Retention rules and cleanup
- Model and provider review when needed
Production control layer
Visible by default
Access control
Roles and permissions
Limit who can view data, review outputs, or trigger actions.
Audit trail
Every action logged
Trace inputs, outputs, approvals, and overrides.
Alerts and monitoring
Real-time visibility
Spot failed steps, unusual costs, or quality drops.
Cost controls
Usage caps and limits
Keep spend predictable with model and workflow limits.
Ready to build the first controlled workflow?
Share the tools, inputs, handoffs, and decisions involved. I will review the fit and tell you whether the next step is the paid audit or a scoped build.