Presetify · AI workflows
Your team's repeatable AI tasks, turned into reliable workflows
Package what your team does in ChatGPT or Claude into structured presets and API-callable workflows — consistent, quality-controlled, ready to plug into your tools.
What it is
Presetify isn't just prompt engineering
The value is repeatability, context management, output structure, integration and quality control — turning one-off prompts into reliable systems.
- Email reply drafting
- Report summarisation
- CV screening
- Customer-support answers
- Product research
- Compliance-style checks
- Constrained content generation
How it works
From prompt to workflow in 6 steps
Define the objective
Pin down the repeatable task and what a good output actually looks like.
Create the preset
Capture the prompt, context and expected output structure as a reusable unit.
Add context & questions
Wire in the inputs and knowledge the workflow needs to run consistently.
Test the output
Validate against examples and test sets until quality is reliable.
Expose via form / API
Make it callable by people through a form, or by systems through an API.
Monitor quality
Track output, add review loops and keep improving the workflow over time.
Packages
How to engage Presetify
Clear packages matched to different AI maturity levels.
AI Workflow Audit
Teams already using ChatGPT / Claude manually
- Workflow mapping
- Automation opportunities
- Prompt quality review
- ROI estimate
Preset Library Build
Teams with repeated writing / analysis / support tasks
- Reusable prompt presets
- Context templates
- Output schemas
- QA checklist
API / Form Integration
Teams needing operational integration
- Web forms
- API endpoints
- Webhook integration
- Storage / logging strategy
AI Operations Retainer
Teams needing continuous improvement
- Monthly optimisation
- New presets
- Monitoring
- Team enablement
FAQ
Common questions
Is this just prompt engineering?
No. The value is repeatability, context management, output structure, integration and quality control — turning one-off prompts into reliable systems.
Can it connect to our tools?
Yes, depending on your tools and security constraints: forms, APIs, webhooks, CRM, Notion, Google Drive and more.
Can we use our own model?
Potentially yes. The architecture can route between OpenAI, Anthropic or open-source models depending on your needs and constraints.
What are good first use cases?
Email replies, report summaries, CV screening, customer support, product research, content generation and compliance-style checks.
How do you control quality?
Output schemas, examples, testing sets, human review loops, monitoring and continuous iteration.
Ready to make your AI workflows reliable?
Tell me about your repeatable tasks and I'll show you how to turn them into structured, reliable systems.
Aurélien Gekiere · Belgium · aurelien@biosai.io