Concrete processes
We start from a task repeated every week, not from an abstract transformation program.
RITSL_
AI processes - SMEs and B2B services
AI Automation for Swiss SMEs
RITSL automates repetitive steps with AI: extraction, classification, synthesis, reporting, CRM, prospecting, support and deliverable preparation, with human control and gain measurement.
Gain measurement
Time saved, volume processed, output quality and errors are tracked from the pilot.
Human supervision
Exceptions, validations and sensitive decisions stay visible to the team.
SME workflows
What this changes in day-to-day work
Data extraction
- Before
- Information copied from PDFs, emails or forms into a spreadsheet.
- With RITSL
- AI extracts fields, flags uncertainty and prepares the import.
- Controls
- Validation of sensitive fields, quality sampling, error correction.
Reporting
- Before
- Data exported, cleaned and commented manually every week.
- With RITSL
- The workflow consolidates data and prepares structured commentary.
- Controls
- Sources traced, figures checked, publication validated by the owner.
Support and triage
- Before
- Incoming requests are read one by one before assignment or prioritization.
- With RITSL
- AI classifies, summarizes, suggests a response or routes to the right person.
- Controls
- Confidence thresholds, human escalation, no automatic sending without approval.
Comparison
Classic automation vs AI automation
The goal is not to replace your existing tools. The goal is to choose a first useful, governed and measurable workflow.
| Criterion | Classic automation | AI automation |
|---|---|---|
| Data | Very effective on stable fields. | Useful when texts, formats or requests vary. |
| Rules | Deterministic logic. | Business rules plus supervised interpretation. |
| Risks | Mostly technical errors. | Understanding errors to control explicitly. |
| Best use | Structured repetitive tasks. | Semi-structured documents, messages, summaries and classification. |
Deliverables
What RITSL delivers
- Process audit and volume estimate.
- Map of inputs, outputs, validations and exceptions.
- Automated prototype on a limited scope.
- Quality measurement and control rules.
- Operating documentation for the team.
- Extension plan or stop decision if the pilot is not profitable.
Path
A short but controlled deployment
Diagnostic
Map recurring tasks, tools, sensitive data and the teams involved.
Pilot
Choose a limited workflow and build usage rules, prompts, connectors or deliverable templates.
Training
Practical workshop with the teams, based on their own use cases and confidentiality constraints.
Production launch
Deployment, follow-up on first usage, corrections and quality measurement of incoming requests.
FAQ
Frequently asked questions
Which process should we automate first?
Choose a frequent text or document task with a clear output and someone able to validate quality.
Does the automation need to replace existing tools?
No. Most often, it connects your current tools and adds an AI step between input and output.
How do we avoid AI errors?
We limit the scope, define confidence thresholds, trace sources and keep sensitive decisions under human validation.
Sources
Related pages
Identify the right first use case
The meeting is used to qualify the workflow, data, human validations and business urgency. You do not need a complete specification to start.
Book a diagnostic