Quote & Tender Assistant
Draft quotes and tender documents faster, backed by past deals and price lists.
Quote and tender creation is time-consuming because many text blocks, prices and references are compiled manually. The assistant pulls matching passages from previous quotes, checks requirements from specification sheets and produces a structured draft, with final approval remaining with the sales team.
- Significantly shorter quote cycles.
- More consistent pricing and wording logic.
- More capacity for consultation instead of drafting.
Drafting time per quote
Time to value
More quotes per salesperson
Draft acceptance rate
Calculated from average drafting time per quote multiplied by annual quote volume.
- 01
Quote analysis
Analyze structure and recurring patterns in past quotes.
- 02
Text module library
Bundle approved wording and pricing logic.
- 03
CRM integration
Integrate customer and project data for context.
- 04
Draft review
Test runs with the sales team and adjustment of guardrails.
- 05
Rollout
Deployment in daily operations with a clear approval loop.
Steps
Data sources
Stakeholders
From first data access to production – every step delivers a tangible interim result.
CRM
Customer history, contacts and project status.
Past quotes
Proven text modules and pricing structures.
Price lists
Current terms for products and services.
Requirement specs
Customer requirements from tender documents.
Reference projects
Matching case examples to support quotes.
Approval workflow
Internal sales rules for final review.
Sales
Faster, consistent quote creation.
Tender management
Structured responses to specification sheets.
Sales management
Higher quote throughput per employee.
Controlling
More consistent pricing baselines.
Significantly shorter quote cycles.
More consistent pricing and wording logic.
More capacity for consultation instead of drafting.
Higher hit rate on tenders.
Top performers' know-how becomes available to all.
With a solid data foundation this use case gets faster, cheaper and far more stable.
Clean CRM data provide relevant customer context.
Central pricing logic prevents contradictory quotes.
Versioned text modules ensure traceability.
The existing document platform speeds up integration.
Document chat (RAG)
Past tender documents can be searched specifically.
Content & product data generation
Product descriptions flow directly into quotes.
Business intelligence
Quote data feed win-rate metrics.
Internal Enterprise GPT
A company-owned chat assistant that reliably answers questions on processes, policies and expertise.
Document Chat (RAG)
Search large document sets via chat instead of manually digging through contracts and reports.
Service & Repair Assistant
Technicians get precise repair guidance on-site, drawn from manuals and ticket history.