IndiaHealthcare — hospital networkScale · $100K
Fortis Healthcare

The hospital that answers: every appointment, insurance, and report conversation handled before the front desk queue forms

Give Fortis an agentic patient-access layer — appointment booking and reminders, cashless-insurance guidance, diagnostics report and follow-up conversations — raising utilization and patient experience across its network without expanding call-center headcount.

Entry use case
Appointment booking, reminders & no-show reduction
Expected outcome
Reduced no-shows and abandoned booking calls; higher OPD utilization; insurance-desk queries deflected to guided self-service.
Recommended next step
Cluster pilot: conversational booking, reminders, and insurance guidance at two NCR hospitals for 90 days, measured on no-show rate, booking abandonment, and desk-query deflection.
What we understand

Fortis Healthcare's operating reality

Among India's largest private hospital networks (~28 hospitals, ~4,500+ beds) with majority ownership by Malaysia's IHH Healthcare; also operates Agilus (formerly SRL) diagnostics at national scale.

Public fact

Metro-market competition (Apollo, Max, Manipal) is fought on patient experience and specialist access as much as clinical outcomes.

Public fact

Appointment lines at large hospitals queue at peak hours; abandoned booking calls are lost OPD revenue and leaked patients.

Reasoned inference

Cashless-insurance and TPA pre-authorization questions likely dominate front-desk and phone volume around admissions — anxious, repetitive, and guidance-hungry conversations.

Reasoned inference

Diagnostics (Agilus) generates enormous report-status and preparation-instruction volume that is operationally separable and automation-friendly.

Reasoned inference

Validate with the account team before outreach: HIS/scheduling system landscape and API readiness across hospitals · Where insurance-desk query volume actually concentrates and TPA-system integrability · IHH group technology governance and whether a network standard is being set regionally

Build vs buy

Why we have a right to win here

Buy-led target

Limited internal ability or appetite to build the core platform — strong candidate for the packaged solution

Evidence: Hospital chains buy clinical and operational technology; Fortis's digital estate is vendor-delivered, and IHH group practice is standardizing bought platforms across markets rather than building software.

Why they won't build the full stack: No hospital network builds conversational AI stacks; clinical-governance overhead alone dictates a packaged, auditable platform with enforced clinical-escalation boundaries.

What management is signalling

Management commentary emphasizes occupancy improvement, payor-mix optimization, and Agilus turnaround as value drivers

Reported factFY25 earnings commentary · mid 2025

GTM implication: OPD funnel efficiency and diagnostics experience automation land directly on the occupancy and Agilus narratives

Continued brownfield bed additions and digital-experience investment discussed in investor material

Inferencerecent investor communications (validate) · late 2025

GTM implication: New capacity needs demand-side conversion machinery — the patient-access layer is that machinery

What already exists (don't pitch this)
  • MyFortis app and web booking
  • Call-center appointment lines
  • WhatsApp presence
  • Agilus digital report delivery
What customers still can't do end-to-end (pitch this)
  • →Phone booking queues at peak; abandonment unmeasured
  • →No-show management thin
  • →Insurance guidance desk-dependent and inconsistent
  • →No vernacular conversational layer across hospitals and diagnostics
Opportunity map

Where agentic communications pays off first

WorkflowWhy it matters hereValueComplexitySpeedChannels
Appointment booking, reminders & reschedule
Any-hour booking in the patient's language with smart reminders and one-tap reschedule; no-show rates measured per specialty.
OPD is the network's demand engine; every abandoned call or no-show is lost utilization across expensive specialist capacity.
Friction today: Peak-hour phone queues; manual slot lookup; no-shows unmanaged; reschedules restart the whole process.
VoiceWhatsAppWeb chat
Cashless-insurance & admission guidance
Guided insurance conversations: empanelment checks, document checklists, and proactive pre-auth status; desks handle exceptions.
Insurance confusion at admission is the worst-moment experience and a discharge-delay driver.
Friction today: Patients call and queue to ask TPA, coverage, and document questions; answers vary by desk staff; pre-auth status is opaque.
WhatsAppVoice
Diagnostics reports & follow-up (Agilus)
Proactive report-ready notifications, guided prep instructions, and follow-up appointment booking in one thread.
Report-status calls and collection-prep questions form high-frequency, low-complexity volume across the diagnostics network.
Friction today: Patients call labs for status; prep instructions are miscommunicated causing repeat visits.
WhatsAppVoiceSMS
Watch the change

Appointment booking, reminders & no-show reduction: today vs the agentic model

Scenario: A daughter in Gurugram books her father's cardiology follow-up at 10 pm in Hindi, gets the fasting instructions, and reschedules by one tap when his plans change
Today
same interaction, two worlds
Agentic layer
No-show reduction
—
measured in pilot
Assumption
Cost per contact
$13.50 median assisted
$1.84 median self-service
Benchmark
QA coverage
1–2% sampled
100% scored
Platform capability
Sources & assumptions
  • · No-show reduction: Reminder-driven reductions vary by specialty; baseline first
  • · Cost per contact: Gartner customer service cost benchmarks, 2024
  • · QA coverage: Platform capability: every interaction logged and evaluated
  • · Gartner, customer service cost benchmarks (2024): $13.50 median assisted vs $1.84 self-service per contact
  • · McKinsey, digital-first collections research: 20–25% NPL reduction among leaders; up to 40% opex reduction with gen AI
  • · Baymard Institute: ~70% average cart abandonment (meta-analysis)
  • · IAMAI–Kantar via IBEF (2025): 900M+ Indian internet users; 98% consume Indic-language content
  • · LeadSquared and vendor funnel studies: 78% of students choose the first institution to respond (directional, vendor data)
  • · HDI / ITSM operator benchmarks: $15–25 per L1 ticket; 40–60% of L1 volume is resets/status (validate per customer)
  • · Conventional-flow wait times and volumes are typical operator patterns — assumptions to replace with the customer's own baseline
  • · Agentic-flow behaviors (context retention, 100% logging, in-line policy checks) are platform capabilities, not projections
Recommended solution

One integrated stack, opinionated for this account

Channels · Tilicho Labs
VoiceWhatsAppWeb chatSMS

Voice & channel orchestration, telephony, conversational execution, session/state, routing, integration build. Capability coverage validated during implementation.

Intelligence · Google Cloud
Gemini reasoningEnterprise groundingWorkflow agentsMulti-agent orchestrationGoverned actionsEvaluation & analytics
Systems · Fortis Healthcare
HIS schedulingDoctor rostersTPA/insurance desk systemsAdmission workflowLIS/RISReport delivery system

API access to these systems is the critical-path dependency.

Trust & languages
HindiEnglishPunjabiBengaliMarathiKannada

Identity-bound sessions, policy-bounded actions, 100% audit logging, human approvals at defined points, in-tenant intelligence.

Business case

The economics, with your numbers

Addressable monthly interactions900K
Seller assumption — replace in discovery
Current cost per interaction ($)$1.5
Industry benchmark scale — validate
Automation / assistance rate (%)55%
Seller assumption — pilot proves this
$1.4M
Current operating cost / mo
$6.8M
Modelled gross benefit / yr
0.2 mo
Payback on Scale
322%
3-yr ROI (modelled)
Automated/assisted interactions per month495K
Modelled AI run-cost per month (usage + cloud, system estimate)$173K
New monthly operating cost$781K

All figures are modelling estimates from the labeled inputs above — nothing here is customer-provided yet. The pilot's first job is replacing these assumptions with Fortis Healthcare's measured baseline. Package price covers implementation only; recurring usage billed separately.

Recommended package

Scale — $100K implementation

Scale · $100K · A multi-channel production deployment10–14 weeks to production across priority workflows

Why this package for Fortis Healthcare: Two-three workflows (appointments, insurance guidance, diagnostics follow-up) with HIS/RIS integration across voice and WhatsApp — scale scope deployable hospital-cluster by cluster.

Included
  • 4–6 channels
  • 2–3 priority workflows
  • Multiple enterprise integrations
  • API credential & security setup
  • Advanced orchestration
  • Multilingual support
  • Agent Assist / human escalation
  • Production analytics
  • Expansion roadmap
Not included
  • ✕Usage & consumption (billed separately)
  • ✕Enterprise-wide governance build-out
  • ✕Multi-BU rollout
Recurring costs (separate from the package)

Packages cover implementation and integration only. Recurring costs are billed separately: Tilicho Labs platform usage (~$0.15/call-min indicative, usage only), Google Cloud consumption, telephony/carrier charges, managed operations, and support & optimization. No package includes unlimited usage.

Customer resources required
  • · API access + credentials for: HIS scheduling, Doctor rosters, TPA/insurance desk systems
  • · A named business owner for appointment booking, reminders & no-show reduction
  • · Security review counterpart and policy sign-off (HIS scheduling scope)
  • · Baseline metrics for the pilot's success thresholds
Executive messages

What to say to whom

CEO

“Fortis competes on being easy to reach and easy to trust; an agent that answers every appointment and insurance question instantly is patient experience made structural.”

CIO / CTO

“HIS-grounded conversations replace phone queues without another portal — and Agilus diagnostics can adopt the same layer with a separate, faster integration.”

COO

“No-show reduction and confirmed bookings smooth OPD load; front desks stop answering the same insurance questions and start resolving exceptions.”

Head of Patient Experience / OPD Operations

“Booking abandonment, no-shows, and insurance-query resolution become measured funnels per hospital — experience managed with numbers.”

Chief Risk / Compliance Officer

“DPDP-conformant consent and data handling with full logging; clinical questions always route to qualified staff — the boundary is enforced by design.”

CFO / Procurement

“Recovered no-show slots and deflected calls are directly monetizable; pilot on one hospital cluster proves the utilization math before network rollout.”

Outreach

Pre-built offer emails for Fortis Healthcare

Written from this account's own research — the strategic signal, the capability gap, the entry workflow, and the modelled economics — not a mail-merge template. Pick the moment and the persona, edit anything, then copy or open in your mail client.

Moment in the deal
Cold outreach — no prior conversation
Who it's addressed to
Cares about: The workflow itself and its daily failure modes
Register
Length
Draft — edit freely before sending
Open in mail client

Customer-safe by construction: drafts are composed only from customer-facing fields. Account tier, build-vs-buy classification, priority score, internal routing, and partner-commercial detail are not inputs to the composer, so they cannot appear in a draft. Money figures are always framed as modelled from the customer's own volumes. Read before sending — you own what goes out.

The pursuit

Tier 2 — high-potential incubation

Why this tier

IHH-backed national hospital chain (~28 hospitals, plus Agilus diagnostics) competing on service experience in metro markets — appointment, insurance-desk, and diagnostics conversations at volume, with international-patient and multi-city coordination layered on top.

Recommended next step

Cluster pilot: conversational booking, reminders, and insurance guidance at two NCR hospitals for 90 days, measured on no-show rate, booking abandonment, and desk-query deflection.

Entry: Appointment booking, reminders & no-show reduction · Scale package · 10–14 weeks to production across priority workflows. Human fallback throughout; success thresholds agreed before build.

Start the pursuit

Research-based priority-account universe assembled from public information, market scale, communication volume, and solution fit. This is NOT an authoritative list of top Google Cloud customers; existing Google Cloud relationships are noted only where publicly reported. Validate every account with the account team before outreach.