2. Fabric Match & Sampling Engine
Matches a buyer's swatch, spec or reference to the closest developed quality in the archive, so sampling rounds collapse from three to one. Target: Sampling rounds per enquiry down from three to one.
Business impact
Sampling rounds per order
Build effort
Customer-facing
Projected lift
Sampling rounds per order
Time to value
From kickoff
Interactions / month
Agent-handled
Automation rate
No human in loop
Net value / year
Revenue + cost avoided − run cost
Payback
Cumulative net positive
Adoption curve
Agent-handled volume vs pre-agent baseline
Baseline (manual process)
Readiness scorecard
Six delivery dimensions
Outcome funnel
How sampling rounds per order is produced
- Eligible interactions4,810
- Agent-handled3,21067%
- Qualified outcome1,76055%
- Sampling rounds per order won83047%
Usage by geography
Cost mix
Share of run cost
- Inference50%
- Integration22%
- Data prep10%
- Change mgmt9%
Cohort retention
Share of users still using the product weekly
| W1 | W2 | W3 | W4 | W6 | W8 | |
|---|---|---|---|---|---|---|
| Cohort 1 | 105 | 99 | 90 | 79 | 64 | 62 |
| Cohort 2 | 107 | 94 | 86 | 75 | 64 | 51 |
| Cohort 3 | 107 | 96 | 84 | 72 | 60 | 50 |
| Cohort 4 | 102 | 94 | 89 | 77 | 72 | 55 |
| Cohort 5 | 105 | 93 | 83 | 78 | 65 | 58 |
Performance by geography
Indexed 0–100 across five signals
| Volume | Accuracy | Deflection | CSAT | Revenue | |
|---|---|---|---|---|---|
| USA | 96 | 95 | 65 | 63 | 95 |
| EU | 81 | 69 | 52 | 90 | 69 |
| Bangladesh | 37 | 89 | 67 | 72 | 99 |
| Vietnam | 70 | 63 | 37 | 62 | 98 |
Model quality
Live vs target
| Metric | Current | Target | 30-day | Status |
|---|---|---|---|---|
| Precision | 92 | 90 | +3.1 | On target |
| Recall | 74 | 85 | +4.4 | Closing gap |
| Grounded-answer rate | 85 | 95 | +1.8 | Closing gap |
| Escalation rate | 5 | 6 | -2.2 | Closing gap |
| P95 latency (s) | 2 | 3 | -0.4 | Closing gap |
| Hallucination flags / 1k | -2 | 1 | -0.9 | Closing gap |
Service levels
85%
Impact score
50%
Delivery ease
96%
Uptime (30 days)
Unit economics
₹ per year, indexed to pilot scale
- Revenue influenced₹3.9Cr
- Cost avoided₹36L
- Run cost₹17L
- Net value₹1.4Cr
Cumulative ROI by quarter
Channel mix
- Voice31%
- WhatsApp33%
- Web-10%
- Field app0%
- Email46%
Language mix
- English-16%
- Hindi-4%
- Gujarati2%
Segment performance
Volume, automation and win rate per market
| Market | Interactions | Automation | Sampling rounds per order | Value | Trend |
|---|---|---|---|---|---|
| USA | 214 | 42% | -5% | ₹-44L | t0t1t2t3t4t5t6t7 |
| EU | 307 | 48% | 6% | ₹-12L | t0t1t2t3t4t5t6t7 |
| Bangladesh | 353 | 31% | -2% | ₹4L | t0t1t2t3t4t5t6t7 |
| Vietnam | 376 | 23% | -6% | ₹-28L | t0t1t2t3t4t5t6t7 |
| India domestic | 388 | 39% | 6% | ₹-4L | t0t1t2t3t4t5t6t7 |
Experiment log
What we tested on this product
| Experiment | Status | Result | Owner |
|---|---|---|---|
| Prompt v3 vs v2 | Won | +11% sampling rounds per order | Aiera Labs |
| Voice-first vs chat-first | Running | +0% so far | Growth Pod |
| Retrieval window 8k → 32k | Won | -1% escalations | Platform |
| Human review threshold 0.7 | Rolled back | no lift | Ops |
| Vernacular tone pack | Running | +4 CSAT pts | CX |
Risk register
Owned mitigations before scale
| Risk | Severity | Mitigation | Owner |
|---|---|---|---|
| Data freshness in source systems | Medium | Hourly sync + staleness alerts | Data Eng |
| Regulatory language in outputs | High | Buyer NDA | Compliance |
| Field-team adoption | Medium | In-app nudges + weekly coaching drills | Sales Ops |
| Model cost drift | Low | Router to smaller models for routine intents | Platform |
Where it sits in the portfolio
Tap another dot to switch product
Systems it touches
- Live
Fabric archive / PLM
Construction, finish and test data per quality
- In build
Lab systems (Datacolor)
Colour measurement and shade approval
- Live
Sample dispatch / courier APIs
Sample status visible to the buyer
Product brief
Who uses it
Buyers, product development, merchants
Metric it moves
Sampling rounds per order
Why Arvind wins
Decades of developed qualities that competitors would have to re-develop
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 sampling rounds per order 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
Spectral + image matching indexes the 3 Arvind product sets, pricing rules and policy language so nothing is answered from memory alone.
03
Reason and decide
Fabric archive embeddings scores the situation and picks the next best action — answer, quote, schedule, escalate — with a confidence threshold behind it.
04
Act in the workflow
Sample tracking 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 sampling rounds per order outcomes flow back nightly; prompts, thresholds and routing are retuned every fortnight.
Data it runs on
Sources, contents and refresh cadence
- Streaming
Conversation history
Voice, WhatsApp, Email-to-agent, Trade shows transcripts with intent, objection and sentiment labels.
- Hourly
Catalogue & pricing
Denim · Wovens · Knits with specs, availability and approved commercial language.
- 15 min
CRM outcomes
Stage moves, win/loss reasons and owner activity per enquiry.
- Hourly
Operations systems
ERP order, stock, dispatch and service records used to answer status questions.
- Daily
Market signals
Demand and competitor movement across 5 geographies via DeployOneSense.
Customer & team journey
1Trigger
Buyers, product development, merchants hits the moment this product exists for — sampling rounds per enquiry down from three to one
2Agent acts
Aiera responds within seconds on Voice, grounded in the live catalogue and the customer's own history.
3Human in the loop
Anything below the confidence threshold, or touching Buyer NDA, routes to a named owner with full context attached.
4Close the loop
Outcome is written back, the customer gets a summary on WhatsApp, and sampling rounds per order is attributed to this product.
Metric tree
What we steer and what we protect
North star
Sampling rounds per order
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
- 0.5 FTE
Product owner (Arvind)
Scope, adoption and the business case
- 1 FTE
Conversation designer
Prompts, tone and 3-language scripts
- 1 FTE
Data / integration engineer
CRM, ERP and telephony wiring
- 0.5 FTE
ML engineer
Scoring models, evaluation harness, drift
- 0.2 FTE each
Ops champion per market
Floor adoption across 5 geographies
Commercials
How the product pays for itself
- Delivery model
- Customer-facing
- Cost drivers
- Inference volume, telephony minutes, integration upkeep
- Charge basis
- Per market licence + usage
- Break-even
- 6 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: Sampling rounds per order 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 sampling rounds per order get compared against?