From 5-Day Backlog to 4-Hour Quotes: AI Automation at Tempsens
92% Faster Quote Turnaround
Tempsens processed 100+ daily RFQs by hand — interpreting specs from PDFs, building BOMs, checking SAP pricing, drafting quotes. Each quote took 5 days and cost ₹22L/month in labour. 9AI's CableQuote AI engine automated the entire workflow: RFQ-to-signed-PDF in 4 hours, ₹15L/month saved, SAP data errors eliminated, 3-year ROI projected at 585%.
92%
Quote Turnaround
faster
₹15L
Monthly Savings
0%
SAP Data Errors
585%
3-Year ROI
Tempsens manufactures industrial cables and temperature measurement equipment for process industries across India and the GCC. Sales begins with an RFQ — a spec document that arrives as a PDF, Excel file, scanned image, or free-text email. An engineer must interpret it, draft a cable architecture compliant with IEC 60794, build a BOM, pull pricing from SAP, and produce a branded quote PDF — often for multiple variants of the same specification.
At 100+ RFQs per day, the team carried a 5-day queue. 480 engineer-hours per week were spent on structured data entry rather than engineering. An 8% SAP master-data error rate sent incorrect quotes to customers. Faster competitors were winning deals that Tempsens should have closed.
Why the manual process couldn't keep up:
- RFQs arrive in unstructured formats — PDFs, scanned drawings, free-text emails
- Cable architecture generation requires IEC 60794 domain knowledge
- SAP BAPI pricing was a manual copy-paste step between systems
- Quote PDF formatting required a separate design step
- 8% SAP master-data errors caused incorrect pricing on live quotes
The engineers weren't inefficient — the workflow was broken at every stage.
Daily RFQ volume
Quote turnaround time
Engineer hours/week on quotes
Monthly labour cost
SAP master-data errors
#CableQuote AI — End-to-End Automation
#Five-Stage Pipeline
Multi-Format Ingestion
Email listener, PDF OCR, and Excel parser extract RFQ data regardless of format. Structured spec JSON generated automatically — no human reads the incoming document.
GPT-4o Requirement Parser
Fine-tuned on 21,000 historical Tempsens RFQs. Extracts cable type, length, temperature range, environment class, shielding requirements, and special conditions from unstructured text with 99.4% field accuracy.
IEC-Compliant Architecture Generator
Constraint-based engine produces cable BOM from parsed specs — materials, shielding, armoring, and insulation automatically selected per IEC 60794. No engineer review required for standard configurations.
SAP BAPI Live Pricing Integration
Material costs fetched in real time from SAP via BAPI calls. Zero manual SAP entry. SAP master-data errors dropped from 8% to 0% on day one.
Branded Quote PDF + Digital Signature
Fully formatted Tempsens-branded PDF generated, signed, and dispatched to the customer's inbox — total pipeline runtime: under 4 hours from RFQ receipt.
#Before vs After: Quoting Operations
| Metric | Before | After | Change |
|---|---|---|---|
| Quote turnaround | 5 days | 4 hours | 92% faster |
| Engineer hours/week on quotes | 480 hours | 40 hours | 92% reduction |
| Monthly labour cost | ₹22L | ₹7L | ₹15L saved |
| SAP master-data errors | 8% | 0% | Eliminated |
| Quote pricing accuracy | 91% | 99.4% | +8.4 percentage points |
This system freed our engineers to innovate instead of keying data. Quotes reach customers in hours, not days — and they're accurate every single time.
— VP Sales Engineering, Tempsens
#Measured Outcomes
92%
Quote Speed
faster
₹15L
Monthly Savings
labour recovered
0%
SAP Errors
fully eliminated
585%
3-Year ROI
projected