Sensors that fire work orders, not just dashboards.

• Meters read manually

  Watchman walks the basement on the 5th. Half the readings are typed wrong.

  Revenue leak

• Leaks caught at the bill

  Underground pipe leaks for 6 weeks. Caught when water bill triples.

  Cost shock

• Vendor SDK fragmentation

  Hikvision + CP Plus + Genus + L&T meters — five SDKs, five integrations, no single registry.

  Integration cost

• Dashboards nobody acts on

  Grafana shows the spike. Nobody creates a ticket. Bill arrives anyway.

  Action gap

• Insecure devices

  Default passwords. Open ports. One bad device, the whole network is exposed.

  Security risk

• Single device registry — meters, sensors, cameras, gates, gateways
• Multi-protocol ingestion — MQTT, Modbus, HTTP, vendor SDKs
• Real-time anomaly detection — leaks, spikes, offline, tamper
• Auto work orders to vendors on threshold breach
• Device security — cert-based auth, signed firmware, audit log
• Resident-facing meter app — consumption history, leak alerts

• Device registry

  One source of truth across vendor SDKs and protocols.

• Anomaly + action

  Detect spike, leak, offline. Fire ticket automatically.

• Resident app

  Live consumption, history, leak alerts in the SoftDocket app.

• Device registry

  Onboard, tag, locate, decommission. Multi-vendor, multi-protocol.

  • Bulk onboarding (CSV / SDK)
  • Location tree (site / block / floor / flat)
  • Vendor + model + firmware metadata
  • Health status per device
  • Decommission + replacement workflow

• Multi-protocol ingestion

  MQTT, Modbus RTU / TCP, HTTP, vendor SDKs — one normalised stream.

  • MQTT broker (managed)
  • Modbus RTU / TCP gateway
  • Hikvision + CP Plus camera SDK
  • Genus + L&T meter SDK
  • Custom HTTP webhooks

• Anomaly + work orders

  Rule-based + ML-based detection. Auto work orders to vendors.

  • Threshold rules (e.g. > 3× baseline)
  • ML anomaly detection (water / energy)
  • Offline / tamper alerts
  • Auto-ticket to vendor with photo capture request
  • SLA breach escalation

• Resident + manager app

  Real-time consumption + leak alerts for residents. Live ops view for managers.

  • Live consumption + history
  • Cost prediction this cycle
  • Leak alert push
  • Manager site overview
  • Weekly summary digest

1. 1

   Ingest

   Meter / sensor pushes reading via MQTT or vendor SDK. Normalised to common schema.

   Reading in

2. 2

   Detect

   Rule + ML engine flags spike, leak, offline, or tamper.

   Anomaly

3. 3

   Assign

   Auto work order to vendor with location, severity, photo request.

   Vendor notified

4. 4

   Resolve

   Vendor uploads photo + closure note. Resident notified. Metric monitored.

   Closed + verified

The same anomaly that fires the ticket also closes it when the metric returns to baseline.

• MQTT brokers

  Protocol

• Modbus RTU / TCP

  Protocol

• AWS IoT Core

  Cloud

• Hikvision cameras

  Surveillance

• CP Plus

  Surveillance

• Genus smart meters

  Metering

• L&T smart meters

  Metering

• Grafana

  Visualisation

• WhatsApp alerts

  Channel

• Webhooks

  Developer

• Cert-based device auth

  Every device onboards with x.509 cert. No shared passwords.

  mTLS 1.2+

• Signed firmware updates

  OTA updates signed and verified at device. Rollback on failure.

  Code-signed

• Network segmentation

  IoT subnet isolated from corporate / resident networks. Zero-trust egress.

  Mapped to NIST 800-82

• Device action audit

  Every command + reading + firmware update logged with device, actor, timestamp.

  7-year retention

Leak detection time

-94%

From 6 weeks to 4 hours

Water saved

18%

Median across 80 sites

Energy saved (common area)

12%

Anomaly + auto-shutoff

Manual meter reading

0 hrs

From 14 hrs / month

Tamper events caught

+340%

Vs random audit

Device uptime

99.4%

Cert-based + OTA

• Live consumption heatmap by site / block / flat
• Anomaly feed — leak, spike, offline, tamper
• Vendor scorecard — response time to IoT-triggered tickets
• Cost-saved dashboard — water + energy + manual labour

• “An underground leak that would have cost us ₹6.8 lakh got caught in 4 hours. ROI in one event.”

  Bharat Goyal

  Facility Head · Rohan Mithila

  ₹6.8L leak caught in 4h

• “We retired manual meter readings entirely. Watchman time goes to security now, where it actually matters.”

  Aarti Joshi

  MC President · Brigade Gardenia

• “Multi-vendor SDK headaches went away. One registry, one anomaly rule set, one ticket queue.”

  Vikram Singhania

  IT Head · Sattva Hamilton Court

  5 SDKs → 1 platform