3. Tenant Demand Radar

Watches hiring, funding, GST registrations and expansion signals to name which corporates will need space next quarter, and opens the conversation before the RFP is written. Target: One in three leases sourced before a formal RFP exists.

Core buildPrototypeNext

Business impact

82/100

Pre-RFP meetings

Build effort

46/100

Internal platform

Projected lift

+21%vs pre-agent baseline

Pre-RFP meetings

Time to value

2 quarters

From kickoff

Interactions / month

3,948+13%

Agent-handled

Automation rate

70%-6% human touches

No human in loop

Net value / year

₹2.9Cr

Revenue + cost avoided − run cost

Payback

5 months

Cumulative net positive

Adoption curve

Agent-handled volume vs pre-agent baseline

Jul94 peakDec

Baseline (manual process)

JulAugSepOctNovDec

Readiness scorecard

Six delivery dimensions

DataModelIntegrationAdoptionComplianceOps readiness

Outcome funnel

How pre-rfp meetings is produced

  • Eligible interactions4,572
  • Agent-handled3,27272%
  • Qualified outcome1,52247%
  • Pre-RFP meetings won77251%

Usage by geography

212
296
338
359
369
AhmedabadGandhinagarBengaluruPuneNRI - USA/GCC

Cost mix

Share of run cost

46
  • Inference46%
  • Integration31%
  • Data prep27%
  • Change mgmt16%

Cohort retention

Share of users still using the product weekly

W1W2W3W4W6W8
Cohort 11079490736760
Cohort 21049385746154
Cohort 31018984685949
Cohort 41079785767058
Cohort 51019184716656

Performance by geography

Indexed 0–100 across five signals

VolumeAccuracyDeflectionCSATRevenue
Ahmedabad5046659470
Gandhinagar4398677369
Bengaluru7872559169
Pune4166579091

Model quality

Live vs target

MetricCurrentTarget30-dayStatus
Precision8290+3.1Closing gap
Recall7985+4.4Closing gap
Grounded-answer rate9595+1.8On target
Escalation rate146-2.2On target
P95 latency (s)33-0.4On target
Hallucination flags / 1k11-0.9On target

Service levels

82%

Impact score

54%

Delivery ease

86%

Uptime (30 days)

Unit economics

₹ per year, indexed to pilot scale

  • Revenue influenced₹3.3Cr
  • Cost avoided₹1.3Cr
  • Run cost₹27L
  • Net value₹2.9Cr

Cumulative ROI by quarter

Q1115% peakQ4

Channel mix

  • Voice25%
  • WhatsApp16%
  • Web24%
  • Field app21%
  • Email15%

Language mix

5
  • English17%
  • Hindi27%
  • Gujarati32%
  • Kannada20%
  • Marathi29%

Segment performance

Volume, automation and win rate per market

MarketInteractionsAutomationPre-RFP meetingsValueTrend
Ahmedabad772
91%
40%₹39L
t0t1t2t3t4t5t6t7
Gandhinagar1,036
93%
29%₹29L
t0t1t2t3t4t5t6t7
Bengaluru718
74%
23%₹24L
t0t1t2t3t4t5t6t7
Pune559
64%
34%₹22L
t0t1t2t3t4t5t6t7
NRI - USA/GCC929
59%
40%₹21L
t0t1t2t3t4t5t6t7

Experiment log

What we tested on this product

ExperimentStatusResultOwner
Prompt v3 vs v2Won+10% pre-rfp meetingsAiera Labs
Voice-first vs chat-firstRunning+5% so farGrowth Pod
Retrieval window 8k → 32kWon-7% escalationsPlatform
Human review threshold 0.7Rolled backno liftOps
Vernacular tone packRunning+4 CSAT ptsCX

Risk register

Owned mitigations before scale

RiskSeverityMitigationOwner
Data freshness in source systemsMediumHourly sync + staleness alertsData Eng
Regulatory language in outputsHighRERA registration numbersCompliance
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

  • DeployOneSense signal crawl

    Hiring, funding, expansion and office-move notices

    Live

  • LinkedIn / firmographic data

    Headcount trajectory and decision-maker mapping

    Live

  • DeployOne Connect

    Multilingual outbound and meeting booking

    Live

Product brief

Who uses it

Leasing team, business development

Metric it moves

Pre-RFP meetings

Why Arvind wins

Pipeline created ahead of the market, not bid for inside it

Signal miningFirmographic enrichmentOutbound orchestration

Guardrails

Applied to every response

  • RERA registration numbers
  • No assured-return claims
  • Broker attribution rules
  • Call recording consent

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 Ahmedabad with human review on every output.

Weeks 7–10

Automate the loop

Hand pre-rfp meetings decisions to the agent with escalation thresholds.

Weeks 11–14

Scale across lines

Roll out to 5 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, Residential and geography.

02

Ground the context

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

03

Reason and decide

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

04

Act in the workflow

Outbound orchestration 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 pre-rfp meetings 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, Broker network, Portals, Site walk-in transcripts with intent, objection and sentiment labels.

    Streaming

  • Catalogue & pricing

    Residential · Commercial · Services 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

    Leasing team, business development hits the moment this product exists for — one in three leases sourced before a formal rfp exists

  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 RERA registration numbers, 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 pre-rfp meetings is attributed to this product.

Metric tree

What we steer and what we protect

North star

Pre-RFP meetings

Drivers

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

Guardrail metrics

  • Grounded-answer rate above 95%
  • Escalation rate inside agreed band
  • RERA registration numbers
  • 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 5-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 market licence + usage
Break-even
9 months at pilot volume
Scale unit
One geography × one Residential

Rollout waves

Scope and the exit test for each wave

Wave 1 — Prove

Ahmedabad, Residential, human review on every output.

Exit test: Pre-RFP meetings beats manual baseline on 200+ conversations.

Wave 2 — Automate

Add Gandhinagar 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 5 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 Real Estate
  • Approved language pack for English, Hindi, Gujarati, Kannada, Marathi
  • Telephony numbers and consent records for outbound
  • Sign-off on RERA registration numbers
  • Named market champions for floor adoption

Open questions for the business

Answer these to lock the scope

  • Which Ahmedabad team runs the pilot and who signs off on outcomes?
  • How far back does usable conversation history go for Residential?
  • What confidence threshold is acceptable before the agent acts unattended?
  • Which existing report does pre-rfp meetings get compared against?
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