1. Quote & Costing Autopilot

Reads the buyer enquiry, matches construction and finish to the mill's live capability and cost, and returns a costed, margin-checked quote in minutes with a confidence band merchants can defend. Target: Quote turnaround from days to minutes with margin discipline intact.

Quick winPilotNow

Business impact

88/100

Quote turnaround

Build effort

40/100

Internal platform

Projected lift

+22%vs pre-agent baseline

Quote turnaround

Time to value

≤ 90 days

From kickoff

Interactions / month

3,822+18%

Agent-handled

Automation rate

69%-5% human touches

No human in loop

Net value / year

₹3.2Cr

Revenue + cost avoided − run cost

Payback

8 months

Cumulative net positive

Adoption curve

Agent-handled volume vs pre-agent baseline

Jul91 peakDec

Baseline (manual process)

JulAugSepOctNovDec

Readiness scorecard

Six delivery dimensions

DataModelIntegrationAdoptionComplianceOps readiness

Outcome funnel

How quote turnaround is produced

  • Eligible interactions4,841
  • Agent-handled3,64175%
  • Qualified outcome1,69146%
  • Quote turnaround won74144%

Usage by geography

161
140
260
320
220
USAEUBangladeshVietnamIndia domestic

Cost mix

Share of run cost

40
  • Inference45%
  • Integration22%
  • Data prep20%
  • Change mgmt19%

Cohort retention

Share of users still using the product weekly

W1W2W3W4W6W8
Cohort 11079183776862
Cohort 21029886756855
Cohort 31019586705950
Cohort 41049387746858
Cohort 51049188786454

Performance by geography

Indexed 0–100 across five signals

VolumeAccuracyDeflectionCSATRevenue
USA5692468765
EU9272817998
Bangladesh6482934482
Vietnam6386938647

Model quality

Live vs target

MetricCurrentTarget30-dayStatus
Precision8790+3.1Closing gap
Recall8685+4.4On target
Grounded-answer rate9295+1.8Closing gap
Escalation rate96-2.2On target
P95 latency (s)33-0.4On target
Hallucination flags / 1k41-0.9On target

Service levels

88%

Impact score

60%

Delivery ease

91%

Uptime (30 days)

Unit economics

₹ per year, indexed to pilot scale

  • Revenue influenced₹3.0Cr
  • Cost avoided₹1.4Cr
  • Run cost₹25L
  • Net value₹3.2Cr

Cumulative ROI by quarter

Q1100% peakQ4

Channel mix

  • Voice15%
  • WhatsApp9%
  • Web28%
  • Field app33%
  • Email14%

Language mix

3
  • English28%
  • Hindi18%
  • Gujarati28%

Segment performance

Volume, automation and win rate per market

MarketInteractionsAutomationQuote turnaroundValueTrend
USA1,041
55%
34%₹20L
t0t1t2t3t4t5t6t7
EU720
55%
26%₹20L
t0t1t2t3t4t5t6t7
Bangladesh560
55%
22%₹20L
t0t1t2t3t4t5t6t7
Vietnam480
55%
34%₹20L
t0t1t2t3t4t5t6t7
India domestic440
55%
26%₹60L
t0t1t2t3t4t5t6t7

Experiment log

What we tested on this product

ExperimentStatusResultOwner
Prompt v3 vs v2Won+8% quote turnaroundAiera Labs
Voice-first vs chat-firstRunning+2% so farGrowth Pod
Retrieval window 8k → 32kWon-3% escalationsPlatform
Human review threshold 0.7Rolled backno liftOps
Vernacular tone packRunning+8 CSAT ptsCX

Risk register

Owned mitigations before scale

RiskSeverityMitigationOwner
Data freshness in source systemsMediumHourly sync + staleness alertsData Eng
Regulatory language in outputsHighBuyer NDACompliance
Field-team adoptionMediumIn-app nudges + weekly coaching drillsSales Ops
Model cost driftLowRouter to smaller models for routine intentsPlatform

Where it sits in the portfolio

Tap another dot to switch product

Quick winsBig bets
Impact ↑Effort →

Systems it touches

  • SAP

    Yarn cost, standard rates, capacity and margin rules

    Live

  • Cotton / yarn price feeds

    Live raw-material movement into quotes

    Live

  • Email + buyer portal

    Enquiry ingestion and quote delivery

    Live

Product brief

Who uses it

Merchants, buyers, commercial head

Metric it moves

Quote turnaround

Why Arvind wins

Costing built on Arvind's actual mill efficiency, not a rate card

Enquiry parsingYarn-to-fabric cost engineMargin guardrails

Guardrails

Applied to every response

  • Buyer NDA
  • Certification claims (GOTS/BCI)
  • Export documentation accuracy

Delivery plan

14-week path to production

Weeks 1–3

Ground the data

Connect 3 product sets, historical conversations and CRM outcomes.

Weeks 4–6

Pilot with one team

Run in USA with human review on every output.

Weeks 7–10

Automate the loop

Hand quote turnaround decisions to the agent with escalation thresholds.

Weeks 11–14

Scale across lines

Roll out to 3 languages and all geographies.

How it works

End-to-end, from signal to learned outcome

01

Capture the signal

Every Voice and WhatsApp interaction, plus CRM and order events, is streamed in and tagged to a customer, Denim and geography.

02

Ground the context

Enquiry parsing indexes the 3 Arvind product sets, pricing rules and policy language so nothing is answered from memory alone.

03

Reason and decide

Yarn-to-fabric cost engine scores the situation and picks the next best action — answer, quote, schedule, escalate — with a confidence threshold behind it.

04

Act in the workflow

Margin guardrails writes back into CRM/ERP and fires the customer-facing action in English or Hindi, so the team sees it where they already work.

05

Learn from outcome

Won/lost and quote turnaround outcomes flow back nightly; prompts, thresholds and routing are retuned every fortnight.

Data it runs on

Sources, contents and refresh cadence

  • Conversation history

    Voice, WhatsApp, Email-to-agent, Trade shows transcripts with intent, objection and sentiment labels.

    Streaming

  • Catalogue & pricing

    Denim · Wovens · Knits with specs, availability and approved commercial language.

    Hourly

  • CRM outcomes

    Stage moves, win/loss reasons and owner activity per enquiry.

    15 min

  • Operations systems

    ERP order, stock, dispatch and service records used to answer status questions.

    Hourly

  • Market signals

    Demand and competitor movement across 5 geographies via DeployOneSense.

    Daily

Customer & team journey

  1. 1Trigger

    Merchants, buyers, commercial head hits the moment this product exists for — quote turnaround from days to minutes with margin discipline intact

  2. 2Agent acts

    Aiera responds within seconds on Voice, grounded in the live catalogue and the customer's own history.

  3. 3Human in the loop

    Anything below the confidence threshold, or touching Buyer NDA, routes to a named owner with full context attached.

  4. 4Close the loop

    Outcome is written back, the customer gets a summary on WhatsApp, and quote turnaround is attributed to this product.

Metric tree

What we steer and what we protect

North star

Quote turnaround

Drivers

  • Agent-handled share of eligible interactions
  • First-response time and resolution time
  • Qualified outcomes per 100 conversations in USA
  • Repeat engagement within 30 days

Guardrail metrics

  • Grounded-answer rate above 95%
  • Escalation rate inside agreed band
  • Buyer NDA
  • Run cost per conversation below target

Squad to build it

Who is needed and for what

  • Product owner (Arvind)

    Scope, adoption and the business case

    0.3 FTE

  • Conversation designer

    Prompts, tone and 3-language scripts

    1 FTE

  • Data / integration engineer

    CRM, ERP and telephony wiring

    1 FTE

  • ML engineer

    Scoring models, evaluation harness, drift

    0.5 FTE

  • Ops champion per market

    Floor adoption across 5 geographies

    0.2 FTE each

Commercials

How the product pays for itself

Delivery model
Internal platform
Cost drivers
Inference volume, telephony minutes, integration upkeep
Charge basis
Per handled conversation
Break-even
5 months at pilot volume
Scale unit
One geography × one Denim

Rollout waves

Scope and the exit test for each wave

Wave 1 — Prove

USA, Denim, human review on every output.

Exit test: Quote turnaround beats manual baseline on 200+ conversations.

Wave 2 — Automate

Add EU and Hindi; agent acts without review above threshold.

Exit test: Escalation rate under 10% for four straight weeks.

Wave 3 — Extend

All 3 product sets and 4 channels, wired into CRM reporting.

Exit test: Adoption above 70% of eligible interactions.

Wave 4 — Compound

Roll across 5 geographies and share the model with sibling Arvind businesses.

Exit test: Net value positive at run-rate; owned by business-as-usual team.

Dependencies to unblock

Needed before wave 1 starts

  • API access to CRM and ERP for Arvind Textiles
  • Approved language pack for English, Hindi, Gujarati
  • Telephony numbers and consent records for outbound
  • Sign-off on Buyer NDA
  • Named market champions for floor adoption

Open questions for the business

Answer these to lock the scope

  • Which USA team runs the pilot and who signs off on outcomes?
  • How far back does usable conversation history go for Denim?
  • What confidence threshold is acceptable before the agent acts unattended?
  • Which existing report does quote turnaround get compared against?
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