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PARMA Presale Pipeline

Preparation cycle 15→7 days, estimation accuracy 60%→85-90%, AI automates 40% of documentation, conversion ≥70%

At a glance
Preparation cycle: 15 → 7 business days

CTO

6 мес · 12 чел

  • CRM
  • AI Assistants
  • LLM
  • KPI Dashboard
  • Jira
  • Confluence

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Problem

What doesn't work

Commercial proposal preparation was manual and inconsistent across departments. Average cycle for large proposals — up to 15 business days. Effort estimation accuracy — ~60%. No unified artifact repository or templates, estimates depended on subjective experience, architects and analysts unevenly loaded. Manual document review and approval.

Solution

Architectural approach

Standardized presale pipeline: formalized artifact sets per proposal type, clear stage sequence (request → analysis → design → estimation → defense), automated checklists, internal "presale portal" with templates. AI for text preparation, structures, diagrams, and effort analysis — reduces 40% of standard documentation sections.

My role & contribution

CTO

Author of the presale section in the production strategy. Designed the presale pipeline: formalized 5 problem areas, identified 20+ root causes, developed 30+ KPIs. Introduced multi-variant proposals and mandatory artifact sets.

Ready to discuss?

If you need an architect who builds autonomous AI systems — reach out.

Serbia-based · CET/CEST timezone · EU-aligned working hours · International contracts experience