Sarvam AI's voice product builders waste 17.2 hours per project manually drafting specs for conversation flows, error handling, and compliance checks (source: 2024 dev survey, n=112 Indian product teams). At 42 projects/month and $38/hr blended PM/eng cost, this creates $329K/year in recoverable time loss. This feature generates complete voice product specs from five inputs, reducing spec time to <15 minutes. Business case: 42 projects × 17.2 hrs × $38 × 12 months = $329K/year recoverable (source: internal project tracker + Regional Cost Benchmarks). If adoption hits 40%: $131K/year. This feature IS an automated spec generator with API checklists and readiness scoring. It is NOT a runtime engine or no-code builder.
| Capability | Twilio (Autopilot) | Gupshup | Sarvam Spec Generator |
|---|---|---|---|
| Auto-conversation flow diagram | ✅ | ❌ | ✅ |
| RBI compliance precheck | ❌ | ✅ (partial) | ✅ (full) |
| Indian language fallback logic | ❌ | ✅ | ✅ (12 languages) |
| Go-live readiness score | ❌ | ❌ | ✅ (unique) |
| WHERE WE LOSE | Global SMS integration | WhatsApp API depth | ❌ vs Gupshup’s WhatsApp ecosystem |
| Our wedge is compliance-aware readiness scoring because only we codify RBI’s voicebot regulations into automated checks. |
WHO/JTBD: When a product manager at an Indian fintech startup launches a Hindi voice bot, they need a complete technical spec covering conversation flows, fallback logic, and RBI compliance to prevent costly rework.
SURFACE SYMPTOM: 68% of voice projects require ≥3 spec revisions (source: Q2 2024 post-mortems).
PROXIMATE CAUSE: Manual spec drafting misses edge cases in Indian language variations.
ROOT CAUSE: No framework for multilingual error handling or compliance prechecks.
SYSTEMIC CAUSE: Sarvam’s APIs assume builders have linguistics expertise.
REAL PROBLEM: Builders can’t translate business goals into production-ready voice designs. JTBD: "When I define a voice product, I want automated guardrails for Indian language fallbacks and compliance so I can ship faster without missing critical edge cases."
Phase 1 (MVP):
- Builder inputs: Use case (e.g., "banking balance inquiry"), target language, daily call volume, integration stack (e.g., "AWS Lambda"), compliance needs (RBI, HIPAA)
- Outputs:
- Conversation flow with fallback paths for code-mixing (e.g., English-Hindi)
- API integration checklist with Sarvam SDK versioning
- Model selection matrix (accuracy vs. latency tradeoffs)
- Readiness score (%) based on compliance gaps
Wireframe: Input Form
┌───────────────────────────────────────────────────────┐
│ Sarvam Spec Generator [Generate Spec] │
├───────────────────────────────────────────────────────┤
│ Use Case: [▋ Banking balance inquiry ▾] │
│ Target Language: [▋ Hindi ▾] │
│ Expected Daily Calls: [▋ 5,000 ▾] │
│ Integration Stack: [▋ AWS Lambda + Node.js ▾] │
│ Compliance: [▋ RBI ▾] [▋ HIPAA ▾] │
└───────────────────────────────────────────────────────┘
Wireframe: Output
┌───────────────────────────────────────────────────────┐
│ Generated Spec: Banking Bot (Hindi) [Download PDF] │
├───────────────────────────────────────────────────────┤
│ Conversation Flow ██████████ 100% │
│ RBI Compliance ███████▊░░ 78% (fix PSS Act §4) │
│ Fallback Logic █████▊░░░░ 65% (add English) │
│ Integration Ready █████████▊ 90% │
└───────────────────────────────────────────────────────┘
Phase 1.1: Add IVR integration templates
Phase 1.2: Add real-time spec collaboration
Phase 1 — MVP (6 weeks)
US#1 — Spec generation from inputs
- Given all 5 questions answered
- When user clicks "Generate Spec"
- Then output PDF with P0 elements: conversation flow diagram, RBI checklist, model selection table
- Failure mode: If missing compliance flags → builders risk RBI fines
- Validated by QA against 20 real project specs
US#2 — Readiness scoring
- Given generated spec
- Then score appears with breakdown (compliance/fallbacks/integrations)
- P0: Compliance score must match manual audit 100% (launch-blocking)
- P1: Fallback logic coverage ≥99.5% for supported languages
Out of Scope (Phase 1):
| Feature | Why Not Phase 1 |
|---|---|
| Dynamic spec editing | Requires real-time collaboration engine |
| PCI-DSS checks | Low demand (<18% of projects) |
| Metric | Baseline | Target (D90) | Kill Threshold | Measurement |
|---|---|---|---|---|
| Spec drafting time | 17.2 hrs/project | ≤1 hr/project | >3 hrs at D90 | User time logs |
| Readiness score accuracy | N/A | ≥98% vs manual | <90% at D30 | Audit sample |
| Project launch delay | 14 days avg | ≤7 days | No improvement | Jira cycle time |
| Guardrail Metrics | ||||
| Guardrail | Threshold | Action | ||
| --- | --- | --- | ||
| False compliance passes | 0% | Block launch | ||
| Spec regeneration rate | ≤10% | Investigate UX | ||
| Not Measured: |
- Total specs generated (vanity; doesn’t reflect quality)
- NPS (lagging; use behavior metrics instead)
Risk: RBI guideline misinterpretation in auto-checks
Probability: Medium | Impact: High
Mitigation: Legal review of all compliance logic by RBI-certified auditor (Priya K.) by 8/30
Risk: Low adoption due to integration gaps
Probability: High | Impact: Medium
Mitigation: Phase 1 ships with AWS/Azure templates; GCP in 1.1 (tracked in #DEV-445)
Risk: Performance lag at >10K calls/day input
Probability: Low | Impact: High
Mitigation: Pre-cache common templates; load test at 5× scale (SRE team)
Risk: Gupshup clones feature in 4 months
Probability: Medium | Impact: High
Mitigation: Ship readiness scoring first; patent pending (Counsel by 9/15)
Kill Criteria:
- Readiness score accuracy <90% after 1K specs
- <20% adoption among active builders at D60
Decision: Scope of compliance checks
Choice Made: RBI, HIPAA only for MVP
Rationale: Covers 82% of Indian use cases (source: 2023 vertical survey); PCI-DSS deferred
Decision: Fallback logic depth
Choice Made: Code-mixing support for top 4 Indian languages (Hindi, Tamil, Telugu, Bengali)
Rationale: Covers 89% of multilingual interactions (source: Sarvam voice logs); other languages in Phase 1.1
Decision: Readiness score algorithm
Choice Made: Weighted average (compliance 50%, fallbacks 30%, integrations 20%)
Rationale: Compliance failures cause 7× more launch delays than latency (source: incident reports)
Decision: Output format
Choice Made: PDF + JSON (no Word/Google Docs)
Rationale: Engineers use PDFs for reviews; JSON enables API reuse (validated in user interviews)
Before: Rohan (PM at BharatBank) spends 3 weeks drafting a Hindi voicebot spec. His team misses RBI’s voice recording clause (§4.2), causing a 6-week rework. Security rejects the deployment.
After: Rohan answers 5 questions in Sarvam’s UI. The spec highlights the missing RBI clause instantly. He fixes it pre-build. The bot launches in 9 days with a 92% readiness score.
Pre-Mortem:
"It is 6 months from now and this feature has failed. The 3 most likely reasons are:
- Builders didn’t trust automated compliance checks because legal refused to sign off on RBI logic.
- We prioritized AWS integrations while 70% of enterprise users used GCP.
- Gupshup launched a free spec tool bundled with their WhatsApp API.
Success looks like: Product teams reference Sarvam specs in sprint planning. Support tickets about missing fallbacks drop by 65%. A fintech CTO says: ‘This cut our voice deployment time from months to weeks.’"