Interactive cost analysis: Rent vs Build postures | Confidential — May 2026
Stress-test the baseline model assumptions shown in the Reference section below. Changes here are scenario overrides only and do not alter the underlying source definitions.
Total cost per year across Rent vs dynamic Build ($M)
Running total spend — crossover points highlighted ($M)
Unit economics: $/member/year by posture
Investment structure by year — Rent vs Build grouped stacked view ($M)
Shows data generated by member activity. Not priced as an asset — shown to illustrate the compounding data flywheel that underpins the Build thesis.
Raw data exhaust vs training-usable corpus — cumulative tokens across all members
Annual token volume by source — scaled by member count and engagement
These panels describe the baseline assumptions behind the model. Controls above test alternate scenarios without changing the underlying source definitions. All figures are Y2+ steady-state unless noted.
Source documents: 1_Usage_and_Inference_Demand.md · 2_AI_Light_Rent.md · 3_AI_Full_Build.md (incl. Data Dividend for Delayed Build Starts) · 4_AI-Build-Posture_Full-Context.md — AI Cost Model, May 2026.
Every cost figure in this model traces back to a concrete set of AI engagement events per member per year. The baseline is ~496 personal agent events/member/year (Y2+ steady-state), plus clinical encounter events layered on top.
| Feature Category | Events/member/yr | LLM calls/event | Tokens/call | Routing (Frontier / Mid / Flash) | Voice & OCR per event |
|---|---|---|---|---|---|
| Passive / proactive Daily briefings, wearable alerts, weekly patterns |
247 | 1 | 500 | 0% / 10% / 90% | None |
| Admin / reminders Medication adherence, appointments |
109 | 1 | 500 | 0% / 20% / 80% | 30% voice: 1 min ASR + 700 chars TTS |
| Wellness / diet / medication coaching | 113 | 2 | 1,500 | 0% / 30% / 70% | 50% voice: 1.5 min ASR + 1K chars TTS; 20% meal photo: 1 OCR page |
| Symptom triage / care navigation | 14 | 5 | 3,000 | 20% / 60% / 20% | 50% voice: 2 min ASR + 1.2K chars TTS |
| Document / lab / prescription help | 13 | 3 | 6,000 | 20% / 70% / 10% | 2 OCR pages / event |
| Total personal agent events | 496 |
| Encounter Type | Rate/member/yr (Y5) | LLM calls/encounter | Key Workflows |
|---|---|---|---|
| CHW visits | 5.0 | 6 | Pre-visit prep, screening, escalation summary, follow-up, voice capture |
| Doctor consults Telehealth + clinic |
13.0 | 5 | Pre-consult summary, differential + safety check, care plan + documentation |
| Specialist referrals | 2.0 | 6 | Referral package, post-visit reconciliation, patient summary |
| Hospital admissions | 0.15 | 7 | Admission brief, discharge reconciliation, discharge instructions |
| Pharmacy events | 12.0 | 3 | Drug interaction, substitution, adherence plan |
| Post-encounter reconciliation | fires after CHW + doctor | 1 | Longitudinal record update |
| Modality | Annual Volume per Member |
|---|---|
| LLM calls (all tiers) | 855 |
| LLM tokens (all tiers, incl. 1.4x overhead) | 2.56M |
| — frontier tokens | 329K |
| — mid-tier tokens | 1,395K |
| — flash tokens | 834K |
| ASR minutes | 213 |
| TTS characters | 113,373 |
| OCR pages | 64 |
Not all members engage equally. The 496 events/year is a blended average across three engagement segments. This distribution is critical — it means 20% of users drive disproportionate cost, and 40% barely use the personal agent at all.
| Segment | Share | Events/year | Profile |
|---|---|---|---|
| Power users | 20% | 1,383 | Chronic disease (diabetes, cardiac, pregnancy), daily wearable, highly motivated |
| Moderate | 40% | 399 | Engaged 2–3x/week, responds to nudges, logs meals occasionally |
| Light | 40% | 150 | Enrolled via insurance, minimal self-initiated use, engages around CHW visits |
| Blended | 100% | ~496 | Weighted average across segments |
Verification: (0.20 × 1,383) + (0.40 × 399) + (0.40 × 150) = 276.6 + 159.6 + 60.0 = 496.2 ≈ 496
| Service | Unit Price | Use |
|---|---|---|
| Frontier LLM (Opus / GPT-4.5) | $10.00 / M tokens | Differential diagnosis, safety checks |
| Mid-tier LLM (GPT-4o / Sonnet) | $4.38 / M tokens | Pre-consult summaries, care plans |
| Flash LLM (Gemini Flash) | $0.26 / M tokens | Reminders, admin, low-risk follow-ups |
| ASR (Indic + English) | $0.006 / minute | Voice input |
| TTS (Indic + English) | $0.015 / 1K chars | Voice responses |
| OCR / document extraction | $0.03 / page | Prescriptions, lab reports |
| Model | $ / M tokens | What It Serves |
|---|---|---|
| Phase 1 (8B active, MoE 30B) | $0.30 | First proprietary model |
| Phase 2 (60B active, MoE 300B) | $0.50 | Mid-scale clinical workloads |
| Phase 3 / GP-level (100B active, MoE ~900B) | $0.80 | Full GP model |
| Cloud distilled clinical | $0.12 | Mid-tier equivalent |
| Cloud distilled flash | $0.02 | Routine / admin |
| Local / JORO / on-device | $0.00 | Eligible workloads on user hardware |
API prices are as of May 2026 list rates. The "API Price Decline Rate" slider above models year-over-year compression of these rates. Self-hosted inference cost assumes amortized GPU cluster (768× H100/H200) over 5 years.
Each phase has a binary kill-gate: if the answer is "no", stop investing and revert to Rent. This is the core risk-management mechanism of the Build posture.
| Phase | Timeline | Model | Cost | Kill-Gate Question |
|---|---|---|---|---|
| 0 | Months 1–6 | Fine-tune OSS 70B | $0.3M | Does fine-tuning improve Indian clinical performance? |
| 1 | Months 6–12 | 30B MoE (8B active) | $7.4M | Beat frontier APIs on Indian clinical evals? |
| 2 | Months 12–18 | 300B MoE (60B active) | $39.7M | Achieve task-shift multipliers in pilot? |
| 3 | Months 18–24 | 800B–1T MoE (100B active) | $199M | Full production deployment |
| Component | Cost ($M) |
|---|---|
| Training compute (Phases 0–3 + retraining) | $288M |
| Corpus construction | $22M |
| Manual annotation (1,776 peak FTE) | $30M |
| Synthetic data pipeline | $13M |
| Eval & safety infrastructure | $11M |
| Distillation + local modalities | $18M |
| GPU cluster (768 H100/H200) + clinical validation | $66M |
| PII gate + orchestration | $4M |
| R&D team (45→95 headcount) | $91M |
| Total 5-yr capex | $546M |
When Build starts after Y1, the platform has already accumulated consented usage data. The model credits only the portion that survives consent, de-ID, clinical relevance, and quality filters, reducing annotation and corpus construction costs while leaving training compute, GPU cluster, synthetic data, safety, distillation, and team costs unchanged.
| Build Start | Clean Data | Clinical Annotation Pool | Annotation Discount | Annotation Cost | Corpus Discount | Corpus Cost | Data-Creation Savings |
|---|---|---|---|---|---|---|---|
| Y1 | 0.0B | 0.0B | 0.0% | $30.1M | 0.0% | $22.0M | $0.0M |
| Y2 | 6.4B | 1.2B | 2.0% | $29.5M | 1.6% | $21.6M | $1.0M |
| Y3 | 60.1B | 10.8B | 18.6% | $24.5M | 15.0% | $18.7M | $8.9M |
| Y4 | 1,824.1B | 328.3B | 55.0% | $13.5M | 25.0% | $16.5M | $22.1M |
| Y5 | 20,548.1B | 3,698.7B | 55.0% | $13.5M | 25.0% | $16.5M | $22.1M |
The per-member demand figures (855 LLM calls, 2.56M tokens) already include a 1.4x overhead multiplier applied to raw engagement volumes. This multiplier captures the production reality that every user-facing AI call triggers additional system calls.
| Overhead | What It Covers | Multiplier |
|---|---|---|
| Safety pipeline | Input guardrails, output hallucination check, clinical audit log | 1.15× |
| PII filtration model | Separate NER scrub per cloud call | +2% calls |
| Data validation model | Input quality checks on health data | +1% calls |
| Real-world overhead | Retries, cache misses, multilingual expansion, A/B testing | 1.20× |
| Combined effective multiplier | ~1.4× |
The member ramp is the single largest driver of total cost. The 500× growth from Y1 to Y5 is aggressive but assumes Jio distribution activation — the same channel that scaled JioPhone to 100M+ users.
| Year | Members | What's Happening |
|---|---|---|
| Y1 | 10,000 | Jamnagar pilot — Reliance employee families |
| Y2 | 50,000 | Expanded pilot — Gujarat / Mumbai metro |
| Y3 | 1,500,000 | National launch — first mass enrollment |
| Y4 | 15,000,000 | Rapid scale — Jio distribution activated |
| Y5 | 50,000,000 | Full national scale |
Y6–Y7 hold at 50M (steady state). The "Usage Growth Speed" slider above scales all member counts linearly — at 2.0x, Y5 = 100M members.