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Manufacturing · Tempsens

3–4 days → < 10 minutes RFQ-to-Quote Turnaround

92% faster quote turnaround, $15,000 saved every month

9AI replaced Tempsens' manual RFQ-to-quote workflow with a five-stage, SAP-integrated pipeline running live in production.

92%

faster quote turnaround

$15,000

saved every month

0%

SAP master-data errors

585%

3-year ROI, projected

#The story in three moves

The situation

100+ RFQ line items a day, each interpreted by hand. Five days to a quote, 480 engineer-hours a week spent on structured data entry, and an 8% SAP master-data error rate putting wrong prices in front of customers.

What we deployed

A five-stage pipeline that ingests any RFQ format, parses the specification, generates an IEC 60794-compliant architecture and BOM, prices it live from SAP and issues a signed, branded quote PDF.

The outcome

Turnaround down to under 10 minutes, engineering effort down 92%, $15k saved every month, SAP data errors eliminated on day one, and a projected 585% three-year return.

RFQ received → spec parsed → cable engineered → priced from SAP → signed PDF

in under 10 mins

#The bottleneck, in numbers

100+

RFQs per day

3-4 days

quote turnaround

480 h

engineering / week

$22,000

labour cost / month

8%

SAP master-data errors

Why the manual process couldn't keep up

Unstructured inputs

RFQs arrive as PDFs, scanned drawings and free-text emails. No two look alike, so no two can be handled the same way.

Domain-heavy design

Generating a cable architecture demands IEC 60794 knowledge held by a handful of senior engineers.

Manual SAP lookup

SAP BAPI pricing was a copy-paste step between two systems, performed by hand on every single line.

Separate design step

Quote PDF formatting needed its own pass before anything could be sent to the customer.

Errors reaching customers

An 8% SAP master-data error rate meant incorrect pricing went out on live quotes.

#Every quote was a custom engineering job

Tempsens manufactures industrial cables and temperature measurement equipment for process industries across India and the GCC. Every sale begins with an RFQ — a specification that arrives as a PDF, an Excel file, a scanned image, or free text in an email body.

Before anyone could price anything, an engineer had to:

1

Interpret the incoming specification, in whatever format it arrived

2

Draft a cable architecture compliant with IEC 60794

3

Build the bill of materials, layer by layer

4

Pull current material pricing out of SAP by hand

5

Produce a branded quote PDF — often for several variants of one spec

#Implemented AI capabilities

Reads every enquiry

A mailbox agent connects to your intake inbox and ingests RFQs as PDFs, Excel files or plain-text email bodies, including prior thread context.

Qualifies RFQs

A qualification engine classifies each email and filters out non-RFQ correspondence, with a manual override always available.

Extracts line items

Cable family, conductor, cores, sizes, standards and optional layers are parsed. Anything ambiguous or missing is flagged for quick human review.

Engineers the cable

A cable-physics engine generates the cross-section, side view and build process, and calculates weights and material quantities layer by layer.

Prices in real time

Material rates are pulled live from your existing pricing source, so every quote reflects current costs.

Generates the proposal

A fully formatted quote — margins, taxes, rates and layout configurable, with separate domestic and international templates. Every field editable.

#The end-to-end workflow

1AI

Inquiry

Mailbox ingested automatically; customer, BOQ line items and QR criteria parsed into a tracked record.

2AI+H

Requirement Analysis

Engine pulls the cable-relevant specification into a structured sheet the engineer reviews rather than searches for.

3AI+H

Clarification

Conflicts and missing values flagged against the applicable IS / IEC clause, with a draft mail and tracked closure.

4AI+H

Cable Engineering

Rules engine proposes the full construction stack per size, customer TS overriding IS. Engineer approves or overrides.

5AI

BOM Generation

Layer-by-layer weights computed for every size in the BOQ at once from the approved construction.

6AI+H

Pricing & Margin

BOM flows into a rate master; landed cost computed automatically. Margin stays a human decision.

7AI

Proposal + GTP

GTP per size and the commercial quotation generated from the same approved record, on your company template.

8AI+H

Handover

One record carries the enquiry from mail to submitted quotation, with SAP integration for order handover.

Proven in production. This exact pipeline is live today — quotation turnaround fell from 3–4 days to under 10 minutes.

#Before vs after: Quoting operations

MetricBeforeAfterChange
Quote turnaround5 days10 min99.8% faster
Engineer hours / week on quotes480 hours40 hours92% reduction
Monthly labour cost$22,000$7,000$15,000 saved
SAP master-data errors8%0%Eliminated
Quote pricing accuracy91%99.4%+8.4 pts
Quote turnaround
Before5 days
After10 min
Change99.8% faster
Engineer hours / week on quotes
Before480 hours
After40 hours
Change92% reduction
Monthly labour cost
Before$22,000
After$7,000
Change$15,000 saved
SAP master-data errors
Before8%
After0%
ChangeEliminated
Quote pricing accuracy
Before91%
After99.4%
Change+8.4 pts
Start here

Start with the audit.
Keep everything. Risk nothing.

Your 4-week entry point. Even if you stop there, you keep the SOP, AI strategy, and solution mockups, all yours.

The first step is always a conversation.

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into an AI Native Organisation.

Starting with an Enterprise AI Audit, we map your business, implement our AI Operating System tailored to your workflows, and work alongside your teams to customize, deploy, and drive adoption across the organization.

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“The next big thing in AI was always going to be human”

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9AI Logo

We turn your company
into an AI Native Organisation.

Starting with an Enterprise AI Audit, we map your business, implement our AI Operating System tailored to your workflows, and work alongside your teams to customize, deploy, and drive adoption across the organization.

Company

AboutCase StudiesContactAudit

Resources

Media & NewsCareersCrunchbaseBlog
ISO Certified

“The next big thing in AI was always going to be human”

team [at] 9ai [dot] in
TwitterInstagramLinkedInWhatsAppFacebookYouTube

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