5. Discharge Compliance Copilot
Watches online effluent monitoring against consent limits in real time, warns the operator before a breach is recorded, and files the board-ready compliance report automatically. Target: Zero recorded breaches across monitored plants.
Business impact
Consent breaches
Build effort
Customer-facing
Projected lift
Consent breaches
Time to value
From kickoff
Interactions / month
Agent-handled
Automation rate
No human in loop
Net value / year
Revenue + cost avoided − run cost
Payback
Cumulative net positive
Adoption curve
Agent-handled volume vs pre-agent baseline
Baseline (manual process)
Readiness scorecard
Six delivery dimensions
Outcome funnel
How consent breaches is produced
- Eligible interactions4,226
- Agent-handled3,22676%
- Qualified outcome1,77655%
- Consent breaches won66638%
Usage by geography
Cost mix
Share of run cost
- Inference42%
- Integration33%
- Data prep17%
- Change mgmt19%
Cohort retention
Share of users still using the product weekly
| W1 | W2 | W3 | W4 | W6 | W8 | |
|---|---|---|---|---|---|---|
| Cohort 1 | 105 | 92 | 87 | 74 | 68 | 60 |
| Cohort 2 | 104 | 95 | 84 | 75 | 61 | 50 |
| Cohort 3 | 105 | 94 | 81 | 68 | 59 | 52 |
| Cohort 4 | 100 | 95 | 87 | 75 | 70 | 58 |
| Cohort 5 | 108 | 97 | 82 | 72 | 66 | 58 |
Performance by geography
Indexed 0–100 across five signals
| Volume | Accuracy | Deflection | CSAT | Revenue | |
|---|---|---|---|---|---|
| Gujarat | 79 | 85 | 60 | 95 | 80 |
| Maharashtra | 85 | 88 | 42 | 49 | 86 |
| Tamil Nadu | 63 | 56 | 57 | 44 | 66 |
| Middle East | 61 | 76 | 97 | 55 | 63 |
Model quality
Live vs target
| Metric | Current | Target | 30-day | Status |
|---|---|---|---|---|
| Precision | 84 | 90 | +3.1 | Closing gap |
| Recall | 82 | 85 | +4.4 | Closing gap |
| Grounded-answer rate | 96 | 95 | +1.8 | On target |
| Escalation rate | 16 | 6 | -2.2 | On target |
| P95 latency (s) | 2 | 3 | -0.4 | Closing gap |
| Hallucination flags / 1k | 4 | 1 | -0.9 | On target |
Service levels
85%
Impact score
52%
Delivery ease
88%
Uptime (30 days)
Unit economics
₹ per year, indexed to pilot scale
- Revenue influenced₹2.3Cr
- Cost avoided₹1.3Cr
- Run cost₹43L
- Net value₹3.0Cr
Cumulative ROI by quarter
Channel mix
- Voice22%
- WhatsApp15%
- Web23%
- Field app25%
- Email15%
Language mix
- English18%
- Hindi13%
- Gujarati25%
- Tamil16%
Segment performance
Volume, automation and win rate per market
| Market | Interactions | Automation | Consent breaches | Value | Trend |
|---|---|---|---|---|---|
| Gujarat | 426 | 58% | 35% | ₹90L | t0t1t2t3t4t5t6t7 |
| Maharashtra | 863 | 76% | 40% | ₹95L | t0t1t2t3t4t5t6t7 |
| Tamil Nadu | 1,081 | 85% | 29% | ₹57L | t0t1t2t3t4t5t6t7 |
| Middle East | 1,190 | 90% | 23% | ₹78L | t0t1t2t3t4t5t6t7 |
| Africa | 795 | 92% | 20% | ₹49L | t0t1t2t3t4t5t6t7 |
Experiment log
What we tested on this product
| Experiment | Status | Result | Owner |
|---|---|---|---|
| Prompt v3 vs v2 | Won | +6% consent breaches | Aiera Labs |
| Voice-first vs chat-first | Running | +3% so far | Growth Pod |
| Retrieval window 8k → 32k | Won | -3% escalations | Platform |
| Human review threshold 0.7 | Rolled back | no lift | Ops |
| Vernacular tone pack | Running | +6 CSAT pts | CX |
Risk register
Owned mitigations before scale
| Risk | Severity | Mitigation | Owner |
|---|---|---|---|
| Data freshness in source systems | Medium | Hourly sync + staleness alerts | Data Eng |
| Regulatory language in outputs | High | Pollution-board norms | Compliance |
| Field-team adoption | Medium | In-app nudges + weekly coaching drills | Sales Ops |
| Model cost drift | Low | Router to smaller models for routine intents | Platform |
Where it sits in the portfolio
Tap another dot to switch product
Systems it touches
- In build
CPCB OCEMS feeds
Live effluent parameters reported to the regulator
- Live
State board consent registry
Applicable limits and consent renewal dates
- Planned
Customer EHS reporting
Auto-filed monthly compliance returns
Product brief
Who uses it
Customer EHS teams, Envisol O&M, consultants
Metric it moves
Consent breaches
Why Arvind wins
Turns Envisol from an equipment vendor into the customer's compliance guarantee
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 consent breaches 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
Real-time limit monitoring indexes the 3 Arvind product sets, pricing rules and policy language so nothing is answered from memory alone.
03
Reason and decide
Breach prediction scores the situation and picks the next best action — answer, quote, schedule, escalate — with a confidence threshold behind it.
04
Act in the workflow
Automated regulatory reporting 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 consent breaches outcomes flow back nightly; prompts, thresholds and routing are retuned every fortnight.
Data it runs on
Sources, contents and refresh cadence
- Streaming
Conversation history
Voice, WhatsApp, Tender portals, Consultants transcripts with intent, objection and sentiment labels.
- Hourly
Catalogue & pricing
Treatment · Services · Retrofits with specs, availability and approved commercial language.
- 15 min
CRM outcomes
Stage moves, win/loss reasons and owner activity per enquiry.
- Hourly
Operations systems
ERP order, stock, dispatch and service records used to answer status questions.
- Daily
Market signals
Demand and competitor movement across 5 geographies via DeployOneSense.
Customer & team journey
1Trigger
Customer EHS teams, Envisol O&M, consultants hits the moment this product exists for — zero recorded breaches across monitored plants
2Agent acts
Aiera responds within seconds on Voice, grounded in the live catalogue and the customer's own history.
3Human in the loop
Anything below the confidence threshold, or touching Pollution-board norms, routes to a named owner with full context attached.
4Close the loop
Outcome is written back, the customer gets a summary on WhatsApp, and consent breaches is attributed to this product.
Metric tree
What we steer and what we protect
North star
Consent breaches
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
- 0.5 FTE
Product owner (Arvind)
Scope, adoption and the business case
- 1 FTE
Conversation designer
Prompts, tone and 4-language scripts
- 1 FTE
Data / integration engineer
CRM, ERP and telephony wiring
- 0.5 FTE
ML engineer
Scoring models, evaluation harness, drift
- 0.2 FTE each
Ops champion per market
Floor adoption across 5 geographies
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
- 8 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: Consent breaches 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 consent breaches get compared against?