1. Plant Performance & Remote Diagnosis

Reads SCADA telemetry across the installed base to catch chemistry drift, membrane fouling and pump faults early, resolves what it can remotely and dispatches with the right spare already picked. Target: Site visits down 40% and uptime commitments met on evidence.

Core buildPrototypeNow

Business impact

92/100

Plant uptime

Build effort

54/100

Customer-facing

Projected lift

+23%vs pre-agent baseline

Plant uptime

Time to value

≤ 90 days

From kickoff

Interactions / month

3,444+22%

Agent-handled

Automation rate

83%-4% human touches

No human in loop

Net value / year

₹19L

Revenue + cost avoided − run cost

Payback

4 months

Cumulative net positive

Adoption curve

Agent-handled volume vs pre-agent baseline

Jul82 peakDec

Baseline (manual process)

JulAugSepOctNovDec

Readiness scorecard

Six delivery dimensions

DataModelIntegrationAdoptionComplianceOps readiness

Outcome funnel

How plant uptime is produced

  • Eligible interactions4,405
  • Agent-handled3,50580%
  • Qualified outcome1,75550%
  • Plant uptime won74542%

Usage by geography

-71
24
72
-34
43
GujaratMaharashtraTamil NaduMiddle EastAfrica

Cost mix

Share of run cost

54
  • Inference41%
  • Integration21%
  • Data prep13%
  • Change mgmt12%

Cohort retention

Share of users still using the product weekly

W1W2W3W4W6W8
Cohort 11029288777058
Cohort 21079587736557
Cohort 31069682695652
Cohort 41039382756559
Cohort 51029687736750

Performance by geography

Indexed 0–100 across five signals

VolumeAccuracyDeflectionCSATRevenue
Gujarat7390969868
Maharashtra4886759946
Tamil Nadu4462579384
Middle East8277366936

Model quality

Live vs target

MetricCurrentTarget30-dayStatus
Precision8390+3.1Closing gap
Recall6385+4.4Closing gap
Grounded-answer rate8795+1.8Closing gap
Escalation rate76-2.2On target
P95 latency (s)13-0.4Closing gap
Hallucination flags / 1k11-0.9On target

Service levels

92%

Impact score

46%

Delivery ease

87%

Uptime (30 days)

Unit economics

₹ per year, indexed to pilot scale

  • Revenue influenced₹3.0Cr
  • Cost avoided₹-14L
  • Run cost₹20L
  • Net value₹19L

Cumulative ROI by quarter

Q1138% peakQ4

Channel mix

  • Voice22%
  • WhatsApp33%
  • Web22%
  • Field app-4%
  • Email27%

Language mix

4
  • English-6%
  • Hindi1%
  • Gujarati-11%
  • Tamil-17%

Segment performance

Volume, automation and win rate per market

MarketInteractionsAutomationPlant uptimeValueTrend
Gujarat-191
39%
6%₹-14L
t0t1t2t3t4t5t6t7
Maharashtra104
27%
12%₹3L
t0t1t2t3t4t5t6t7
Tamil Nadu252
21%
1%₹11L
t0t1t2t3t4t5t6t7
Middle East326
38%
9%₹15L
t0t1t2t3t4t5t6t7
Africa363
46%
13%₹-23L
t0t1t2t3t4t5t6t7

Experiment log

What we tested on this product

ExperimentStatusResultOwner
Prompt v3 vs v2Won+12% plant uptimeAiera Labs
Voice-first vs chat-firstRunning+-1% so farGrowth Pod
Retrieval window 8k → 32kWon-1% escalationsPlatform
Human review threshold 0.7Rolled backno liftOps
Vernacular tone packRunning+3 CSAT ptsCX

Risk register

Owned mitigations before scale

RiskSeverityMitigationOwner
Data freshness in source systemsMediumHourly sync + staleness alertsData Eng
Regulatory language in outputsHighPollution-board normsCompliance
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

  • SCADA / PLC gateways

    Flow, TDS, pressure and dosing telemetry per plant

    Live

  • Field service management

    Ticket creation, dispatch and engineer routing

    Live

  • SAP spares inventory

    Part availability and auto-reservation

    In build

Product brief

Who uses it

Service heads, plant operators, AMC customers

Metric it moves

Plant uptime

Why Arvind wins

Every alarm no longer becomes a site visit

SCADA / IoT ingestionAnomaly + diagnostic reasoningSpare-parts recommendation

Guardrails

Applied to every response

  • Pollution-board norms
  • Tender confidentiality
  • Performance-guarantee wording

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 Gujarat with human review on every output.

Weeks 7–10

Automate the loop

Hand plant uptime decisions to the agent with escalation thresholds.

Weeks 11–14

Scale across lines

Roll out to 4 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, Treatment and geography.

02

Ground the context

SCADA / IoT ingestion indexes the 3 Arvind product sets, pricing rules and policy language so nothing is answered from memory alone.

03

Reason and decide

Anomaly + diagnostic reasoning scores the situation and picks the next best action — answer, quote, schedule, escalate — with a confidence threshold behind it.

04

Act in the workflow

Spare-parts recommendation 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 plant uptime 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, Tender portals, Consultants transcripts with intent, objection and sentiment labels.

    Streaming

  • Catalogue & pricing

    Treatment · Services · Retrofits 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

    Service heads, plant operators, AMC customers hits the moment this product exists for — site visits down 40% and uptime commitments met on evidence

  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 Pollution-board norms, 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 plant uptime is attributed to this product.

Metric tree

What we steer and what we protect

North star

Plant uptime

Drivers

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

Guardrail metrics

  • Grounded-answer rate above 95%
  • Escalation rate inside agreed band
  • Pollution-board norms
  • 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 4-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
Customer-facing
Cost drivers
Inference volume, telephony minutes, integration upkeep
Charge basis
Per market licence + usage
Break-even
9 months at pilot volume
Scale unit
One geography × one Treatment

Rollout waves

Scope and the exit test for each wave

Wave 1 — Prove

Gujarat, Treatment, human review on every output.

Exit test: Plant uptime beats manual baseline on 200+ conversations.

Wave 2 — Automate

Add Maharashtra 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 Envisol
  • Approved language pack for English, Hindi, Gujarati, Tamil
  • Telephony numbers and consent records for outbound
  • Sign-off on Pollution-board norms
  • Named market champions for floor adoption

Open questions for the business

Answer these to lock the scope

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