Innovation Lab

Agent experiments for Arvind Garmenting — from idea to shipped, measured against pilot baselines.

Lab ideas

6

Tailored to this business

Avg impact

79/100

Weighted on revenue lift

Experiments running

5

Building, piloting or shipped

Shipped

3

Live in production

Impact vs effort

Where to spend the next sprint

Quick winsBig bets
Impact ↑Effort →

Horizon split

6
  • Now3
  • Next2
  • Later1

Experiment pipeline

  • Idea17%
  • Building17%
  • Piloting17%
  • Shipped50%

Technology building blocks

Most reused across lab ideas

1
1
1
1
1
1
1
1
ProductionRiskBottleneckOutboundAmharic/Hindi/EnglishERPVisionClustering

AI product concepts

5 platform bets for Arvind Garmenting

OTIF Early-Warning Engine

Prototype

Models fabric-in, cutting, sewing and finishing telemetry against the buyer's ship date to flag PO risk two weeks out — with the specific line, operation and bottleneck named.

For Plant heads, merchandising, buyers

Production telemetryDelay risk modelBottleneck attribution

Edge: Risk surfaced while it can still be fixed, not at the shipping week

Vendor Follow-up Autopilot

Pilot

A multilingual voice agent that calls fabric and trim vendors on schedule, captures committed dates and writes them straight into the PO tracker — 40 chase calls a day off the merchant's desk.

For Merchants, sourcing, vendors

Outbound voice agentHindi / English / Amharic ASRERP write-back

Edge: Supplier commitments become data instead of WhatsApp memory

Vision QA & Defect Intelligence

Prototype

Vision models classify defects at end-of-line and in the finishing audit, cluster them by line, operator and operation, and escalate the repeat cause before the buyer claim arrives.

For Quality heads, industrial engineering, buyers

Vision defect classificationClustering + root causeEscalation workflow

Edge: Patterns visible in hours instead of after the claim lands

Capacity & Costing Desk

Concept

Answers a buyer's capacity and price question in the meeting: SAM-based feasibility against live line plans, duty and freight modelled, and a slot held on the spot.

For Buyers, merchandising, industrial engineering

SAM / efficiency modelLine-plan optimiserCosting engine with confidence band

Edge: Bookings won on speed while competitors are still costing

Buyer Status Broadcast

Pilot

Each buyer receives their weekly status pack on their cadence, in their template, exceptions first — generated automatically from live production data.

For Buyer merchandisers, account teams

Report generationPer-buyer templatingException ranking

Edge: The reporting burden that consumes merchant weeks disappears

Idea catalogue

6 plays designed for Arvind Garmenting

Delay early-warning agent

Now

Delivery risk surfaces at the shipping week, when nothing can be fixed.

What we build: Model fabric-in, cutting, sewing and finishing telemetry to flag PO risk two weeks out with the specific bottleneck named.

Production telemetryRisk modelBottleneck attribution
Aiera PredictAiera Sense
Impact
Effort

Tracks OTIF · payback 8 weeks

Vendor follow-up autopilot

Now

Merchants make 40+ chase calls a day to fabric and trim vendors.

What we build: Multilingual voice agent that calls vendors on schedule, captures committed dates and writes them straight into the PO tracker.

Outbound voice agentAmharic/Hindi/English ASRERP write-back
Aiera ConverseAiera Connect
Impact
Effort

Tracks Merchant hours saved · payback 5 weeks

QA escalation triage

Next

Rejections are logged as photos and free text; patterns only emerge after the claim lands.

What we build: Vision model classifies defect type from line photos, clusters by line and operator, and escalates repeat causes automatically.

Vision defect classificationClusteringEscalation workflow
Aiera SenseAiera Brain
Impact
Effort

Tracks Rejection rate · payback 11 weeks

Line-capacity booking assistant

Next

Buyer capacity requests are answered from memory, and lines end up over- or under-booked.

What we build: Conversational capacity booking against live line plans with SAM-based feasibility and an instant hold on the slot.

SAM/efficiency modelLine-plan optimiserSlot holds
Aiera ContextAiera Predict
Impact
Effort

Tracks Line utilisation · payback 12 weeks

Buyer status broadcast

Now

Every buyer merchandiser asks for the same weekly status in a different template.

What we build: Auto-generated per-buyer status pack pushed on their cadence, in their format, with exceptions highlighted first.

Report generationPer-buyer templatingException ranking
Aiera DashAiera Engage
Impact
Effort

Tracks Status emails avoided · payback 4 weeks

Costing enquiry responder

Later

Costing requests bounce between merchandising and IE for days.

What we build: Instant indicative costing from tech pack inputs — fabric, trims, SAM, duty — with a confidence band and one-click IE review.

Tech-pack parsingCosting engineConfidence scoring
Aiera ContextAiera Brain
Impact
Effort

Tracks Costing turnaround · payback 10 weeks

Idea

1 experiments

  • Line-capacity booking assistant

    If we deploy line-capacity booking assistant, response time improves measurably within 30 days.

    +25%Rohit Patel

Building

1 experiments

  • Costing enquiry responder

    If we deploy costing enquiry responder, response time improves measurably within 30 days.

    +31%Sneha Kulkarni

Piloting

1 experiments

  • Buyer status broadcast agent

    If we deploy buyer status broadcast agent, retention improves measurably within 30 days.

    +19%Neha Reddy

Shipped

3 experiments

  • Delay early-warning agent

    If we deploy delay early-warning agent, response time improves measurably within 30 days.

    +13%Priya Gupta

  • Vendor follow-up autopilot

    If we deploy vendor follow-up autopilot, conversion improves measurably within 30 days.

    +24%Sanjay Iyer

  • QA escalation triage

    If we deploy qa escalation triage, response time improves measurably within 30 days.

    +24%Imran Menon