5. Trend-to-Tech-Pack Engine

Turns runway, search and marketplace trend signals into a costed line plan and a tech pack draft, so a concept reaches the vendor in days rather than weeks. Target: Development calendar shortened by three weeks per season.

Core buildConceptNext

Business impact

78/100

Concept-to-tech-pack days

Build effort

52/100

Internal platform

Projected lift

+20%vs pre-agent baseline

Concept-to-tech-pack days

Time to value

2 quarters

From kickoff

Interactions / month

4,116+14%

Agent-handled

Automation rate

61%-7% human touches

No human in loop

Net value / year

₹2.2Cr

Revenue + cost avoided − run cost

Payback

11 months

Cumulative net positive

Adoption curve

Agent-handled volume vs pre-agent baseline

Jul98 peakDec

Baseline (manual process)

JulAugSepOctNovDec

Readiness scorecard

Six delivery dimensions

DataModelIntegrationAdoptionComplianceOps readiness

Outcome funnel

How concept-to-tech-pack days is produced

  • Eligible interactions4,233
  • Agent-handled3,13374%
  • Qualified outcome1,68354%
  • Concept-to-tech-pack days won81348%

Usage by geography

193
156
138
259
319
Metro NCRMumbaiBengaluruHyderabadTier-2 cluster

Cost mix

Share of run cost

52
  • Inference49%
  • Integration37%
  • Data prep21%
  • Change mgmt18%

Cohort retention

Share of users still using the product weekly

W1W2W3W4W6W8
Cohort 11059883776856
Cohort 21079683726055
Cohort 31059079685851
Cohort 41039489757258
Cohort 51059083706757

Performance by geography

Indexed 0–100 across five signals

VolumeAccuracyDeflectionCSATRevenue
Metro NCR6478547775
Mumbai9037773868
Bengaluru7093573645
Hyderabad8196706569

Model quality

Live vs target

MetricCurrentTarget30-dayStatus
Precision9190+3.1On target
Recall8485+4.4Closing gap
Grounded-answer rate9495+1.8Closing gap
Escalation rate116-2.2On target
P95 latency (s)23-0.4Closing gap
Hallucination flags / 1k31-0.9On target

Service levels

78%

Impact score

48%

Delivery ease

95%

Uptime (30 days)

Unit economics

₹ per year, indexed to pilot scale

  • Revenue influenced₹3.7Cr
  • Cost avoided₹1.1Cr
  • Run cost₹44L
  • Net value₹2.2Cr

Cumulative ROI by quarter

Q1134% peakQ4

Channel mix

  • Voice20%
  • WhatsApp36%
  • Web23%
  • Field app12%
  • Email9%

Language mix

5
  • English27%
  • Hindi17%
  • Tamil27%
  • Telugu17%
  • Bengali27%

Segment performance

Volume, automation and win rate per market

MarketInteractionsAutomationConcept-to-tech-pack daysValueTrend
Metro NCR433
91%
40%₹99L
t0t1t2t3t4t5t6t7
Mumbai416
93%
29%₹99L
t0t1t2t3t4t5t6t7
Bengaluru858
94%
37%₹59L
t0t1t2t3t4t5t6t7
Hyderabad1,079
94%
41%₹39L
t0t1t2t3t4t5t6t7
Tier-2 cluster739
94%
29%₹69L
t0t1t2t3t4t5t6t7

Experiment log

What we tested on this product

ExperimentStatusResultOwner
Prompt v3 vs v2Won+11% concept-to-tech-pack daysAiera Labs
Voice-first vs chat-firstRunning+5% so farGrowth Pod
Retrieval window 8k → 32kWon-7% escalationsPlatform
Human review threshold 0.7Rolled backno liftOps
Vernacular tone packRunning+7 CSAT ptsCX

Risk register

Owned mitigations before scale

RiskSeverityMitigationOwner
Data freshness in source systemsMediumHourly sync + staleness alertsData Eng
Regulatory language in outputsHighMarketing consentCompliance
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

  • PLM

    Tech pack, BOM and approval workflow

    In build

  • Fabric library (Arvind mills)

    In-house fabric options, lead times and prices

    Live

  • Marketplace trend APIs

    Search, bestseller and price-band signals

    Live

Product brief

Who uses it

Design, sourcing, merchandising

Metric it moves

Concept-to-tech-pack days

Why Arvind wins

Design speed backed by Arvind's own fabric and vendor base

Trend signal miningGenerative design boardsCosting + tech-pack drafting

Guardrails

Applied to every response

  • Marketing consent
  • Return-policy accuracy
  • No unverified discount claims

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 Metro NCR with human review on every output.

Weeks 7–10

Automate the loop

Hand concept-to-tech-pack days decisions to the agent with escalation thresholds.

Weeks 11–14

Scale across lines

Roll out to 5 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, Menswear and geography.

02

Ground the context

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

03

Reason and decide

Generative design boards scores the situation and picks the next best action — answer, quote, schedule, escalate — with a confidence threshold behind it.

04

Act in the workflow

Costing + tech-pack drafting 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 concept-to-tech-pack days 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, Store CRM, Marketplace, D2C site transcripts with intent, objection and sentiment labels.

    Streaming

  • Catalogue & pricing

    Menswear · Womenswear · Accessories & footwear 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

    Design, sourcing, merchandising hits the moment this product exists for — development calendar shortened by three weeks per season

  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 Marketing consent, 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 concept-to-tech-pack days is attributed to this product.

Metric tree

What we steer and what we protect

North star

Concept-to-tech-pack days

Drivers

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

Guardrail metrics

  • Grounded-answer rate above 95%
  • Escalation rate inside agreed band
  • Marketing consent
  • 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

    0.5 FTE

  • Conversation designer

    Prompts, tone and 5-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 market licence + usage
Break-even
8 months at pilot volume
Scale unit
One geography × one Menswear

Rollout waves

Scope and the exit test for each wave

Wave 1 — Prove

Metro NCR, Menswear, human review on every output.

Exit test: Concept-to-tech-pack days beats manual baseline on 200+ conversations.

Wave 2 — Automate

Add Mumbai 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 5 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 Fashions
  • Approved language pack for English, Hindi, Tamil, Telugu, Bengali
  • Telephony numbers and consent records for outbound
  • Sign-off on Marketing consent
  • Named market champions for floor adoption

Open questions for the business

Answer these to lock the scope

  • Which Metro NCR team runs the pilot and who signs off on outcomes?
  • How far back does usable conversation history go for Menswear?
  • What confidence threshold is acceptable before the agent acts unattended?
  • Which existing report does concept-to-tech-pack days get compared against?
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