Innovation Lab

Agent experiments for Arvind Advanced Materials — 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

3

Building, piloting or shipped

Shipped

2

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

  • Idea50%
  • Building17%
  • Piloting0%
  • Shipped33%

Technology building blocks

Most reused across lab ideas

1
1
1
1
1
1
1
1
DocumentSpecScoringClaimsTest-reportGuardrailRAGFailure-mode

AI product concepts

5 platform bets for Arvind Advanced Materials

RFQ-to-Spec Engineering Copilot

Prototype

Parses a spec-heavy RFQ, extracts standard, GSM, width and volume, matches it to qualified constructions and past project evidence, and hands the engineer a drafted technical response to approve.

For Application engineers, technical sales

Document parsingSpec matching over product libraryRAG on project archive

Edge: A handful of senior engineers stop being the global bottleneck

Standards & Claims Guardrail

Pilot

Every outbound technical claim is validated against live test reports and certification scope before it leaves the building — uncertified sentences are blocked, not corrected later.

For Compliance, technical sales, marketing

Claims validation rulesCertification knowledge baseGuardrail layer on all channels

Edge: In defence and protective fabrics a wrong claim is a legal event

Sample-to-Order Conversion Tracker

Pilot

Tracks every sample through trial, testing and homologation with automated multilingual check-ins at each gate, and escalates the moment a trial goes quiet.

For Sales, technical service, plant trials

Stage-gate trackingScheduled outreachEscalation rules

Edge: The pipeline stage where this business silently loses the most revenue

Distributor Demand Sensing

Concept

Ingests distributor sell-through and regional project pipelines to forecast pull, flag stock-outs before reorders stop, and prompt the replenishment conversation with the numbers attached.

For Channel managers, supply planning, distributors

Demand forecastingDistributor data ingestionAutomated nudges

Edge: Visibility past the first sale, which most industrial suppliers never get

Export Control & End-Use Screening

Concept

Screens every new enquiry for end-use, denied parties and sanctions before any technical data leaves the building, and keeps the audit trail regulators ask for.

For Compliance, legal, export desk

Denied-party screeningEnd-use classificationData-access gating

Edge: Defence-grade materials cannot be sold without this discipline

Idea catalogue

6 plays designed for Arvind Advanced Materials

RFQ auto-qualification

Now

Spec-heavy RFQs sit for days before an application engineer decides whether they're worth quoting.

What we build: Parse the RFQ, extract standard, GSM, width and volume, score fit against the product library and route only qualified enquiries to engineering.

Document parsingSpec matchingScoring + routing
Aiera ContextAiera Predict
Impact
Effort

Tracks RFQ response time · payback 6 weeks

Standards-compliance checker

Now

EN and NFPA claims must be exact; a wrong sentence is a legal problem, not a sales problem.

What we build: Every outbound answer passes a standards checker that validates claims against test reports and blocks anything uncertified.

Claims validation rulesTest-report knowledge baseGuardrail layer
Aiera BrainAiera Context
Impact
Effort

Tracks Non-compliant claims · payback 5 weeks

Application-engineer co-pilot

Next

A handful of senior engineers are the bottleneck for every technical conversation worldwide.

What we build: Co-pilot that drafts application recommendations from past projects, test data and failure modes, with the engineer approving in one click.

RAG over project archiveFailure-mode reasoningApproval workflow
Aiera ConverseAiera Brain
Impact
Effort

Tracks Engineer hours per RFQ · payback 10 weeks

Sample-to-order conversion tracker

Now

Samples ship and then vanish; nobody knows which trial is stuck at which stage.

What we build: Track every sample through trial, testing and approval with automated check-ins at each stage and escalation on silence.

Stage-gate trackingScheduled outreachEscalation rules
Aiera EngageAiera Dash
Impact
Effort

Tracks Sample-to-order rate · payback 5 weeks

Distributor demand sensing

Next

Distributor stock and pull-through are invisible until reorders stop.

What we build: Ingest distributor sell-through, forecast regional demand and prompt replenishment conversations before stock-outs.

Demand forecastingDistributor data ingestionAutomated nudges
Aiera PredictAiera Engage
Impact
Effort

Tracks Distributor stock-outs · payback 9 weeks

Defence & export-control screening

Later

Export-controlled enquiries need screening before any technical data leaves the building.

What we build: Automatic end-use and denied-party screening on every new enquiry, with technical data locked until clearance.

Denied-party list screeningEnd-use classificationData-access gating
Aiera BrainAiera Connect
Impact
Effort

Tracks Screening coverage · payback 12 weeks

Idea

3 experiments

  • Spec-sheet answer engine

    If we deploy spec-sheet answer engine, cost per qualified lead improves measurably within 30 days.

    +11%Rohit Shah

  • Standards-compliance checker

    If we deploy standards-compliance checker, cost per qualified lead improves measurably within 30 days.

    +33%Meera Gupta

  • Application-engineer co-pilot

    If we deploy application-engineer co-pilot, response time improves measurably within 30 days.

    +26%Pooja Reddy

Building

1 experiments

  • RFQ auto-qualification

    If we deploy rfq auto-qualification, cost per qualified lead improves measurably within 30 days.

    +33%Neha Reddy

Piloting

0 experiments

    Shipped

    2 experiments

    • Distributor demand sensing

      If we deploy distributor demand sensing, response time improves measurably within 30 days.

      +15%Vikram Joshi

    • Sample-to-order conversion tracker

      If we deploy sample-to-order conversion tracker, retention improves measurably within 30 days.

      +21%Priya Patel