2. Tender Intent Watcher

Crawls tender portals, pollution-board notices and consent orders daily, scores fit against Envisol's ZLD and STP capability, and opens a qualified pursuit with a drafted response outline. Target: Twice the qualified pursuits with the same bid team.

Quick winPilotNow

Business impact

87/100

Qualified tenders per month

Build effort

40/100

Internal platform

Projected lift

+22%vs pre-agent baseline

Qualified tenders per month

Time to value

≤ 90 days

From kickoff

Interactions / month

4,242+12%

Agent-handled

Automation rate

71%-7% human touches

No human in loop

Net value / year

₹3.1Cr

Revenue + cost avoided − run cost

Payback

8 months

Cumulative net positive

Adoption curve

Agent-handled volume vs pre-agent baseline

Jul101 peakDec

Baseline (manual process)

JulAugSepOctNovDec

Readiness scorecard

Six delivery dimensions

DataModelIntegrationAdoptionComplianceOps readiness

Outcome funnel

How qualified tenders per month is produced

  • Eligible interactions4,423
  • Agent-handled3,52380%
  • Qualified outcome1,57345%
  • Qualified tenders per month won64341%

Usage by geography

163
141
130
255
187
GujaratMaharashtraTamil NaduMiddle EastAfrica

Cost mix

Share of run cost

40
  • Inference41%
  • Integration37%
  • Data prep19%
  • Change mgmt19%

Cohort retention

Share of users still using the product weekly

W1W2W3W4W6W8
Cohort 11049990746959
Cohort 21019681726257
Cohort 31079782695849
Cohort 41049285806756
Cohort 51059685736151

Performance by geography

Indexed 0–100 across five signals

VolumeAccuracyDeflectionCSATRevenue
Gujarat9896626673
Maharashtra5437747754
Tamil Nadu4363446270
Middle East3794798789

Model quality

Live vs target

MetricCurrentTarget30-dayStatus
Precision8990+3.1Closing gap
Recall8685+4.4On target
Grounded-answer rate9095+1.8Closing gap
Escalation rate106-2.2On target
P95 latency (s)43-0.4On target
Hallucination flags / 1k41-0.9On target

Service levels

87%

Impact score

60%

Delivery ease

93%

Uptime (30 days)

Unit economics

₹ per year, indexed to pilot scale

  • Revenue influenced₹2.0Cr
  • Cost avoided₹65L
  • Run cost₹56L
  • Net value₹3.1Cr

Cumulative ROI by quarter

Q1141% peakQ4

Channel mix

  • Voice21%
  • WhatsApp17%
  • Web16%
  • Field app22%
  • Email24%

Language mix

4
  • English13%
  • Hindi25%
  • Gujarati31%
  • Tamil19%

Segment performance

Volume, automation and win rate per market

MarketInteractionsAutomationQualified tenders per monthValueTrend
Gujarat623
76%
32%₹35L
t0t1t2t3t4t5t6t7
Maharashtra961
85%
25%₹67L
t0t1t2t3t4t5t6t7
Tamil Nadu1,130
70%
21%₹83L
t0t1t2t3t4t5t6t7
Middle East1,215
62%
33%₹91L
t0t1t2t3t4t5t6t7
Africa807
78%
25%₹95L
t0t1t2t3t4t5t6t7

Experiment log

What we tested on this product

ExperimentStatusResultOwner
Prompt v3 vs v2Won+9% qualified tenders per monthAiera Labs
Voice-first vs chat-firstRunning+2% so farGrowth Pod
Retrieval window 8k → 32kWon-5% escalationsPlatform
Human review threshold 0.7Rolled backno liftOps
Vernacular tone packRunning+9 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

  • GeM / CPPP / state portals

    Tender discovery, amendments and deadlines

    Live

  • Pollution control board notices

    Consent conditions and closure orders as demand signal

    Live

  • DeployOneSense

    Industrial expansion and capex announcements

    Live

Product brief

Who uses it

Bid team, sales heads

Metric it moves

Qualified tenders per month

Why Arvind wins

Bids started days earlier than competitors even see them

Portal crawlersRelevance classificationDraft bid generation

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 qualified tenders per month 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

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

03

Reason and decide

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

04

Act in the workflow

Draft bid generation 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 qualified tenders per month 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

    Bid team, sales heads hits the moment this product exists for — twice the qualified pursuits with the same bid team

  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 qualified tenders per month is attributed to this product.

Metric tree

What we steer and what we protect

North star

Qualified tenders per month

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

    0.3 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
Internal platform
Cost drivers
Inference volume, telephony minutes, integration upkeep
Charge basis
Per handled conversation
Break-even
5 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: Qualified tenders per month 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 qualified tenders per month get compared against?
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