Jio Haptik debuts WhatsApp and voice AI agents for India’s SMBs
Reliance Jio’s Haptik has launched WhatsApp and voice-based AI agents for small and midsize businesses (SMBs) starting at 10,000, signaling a step-change in how Indian firms automate customer engagement at scale.
Pricing, packaging, and what’s included in Jio Haptik WhatsApp AI agents
Haptik is extending its SMB platform, Interakta WhatsApp-first CRM and support suite used by over 50,000 businesses, to include autonomous AI agents for chat and voice. The entry pack is priced at 10,000 and covers roughly 2,000 AI-driven conversations, putting the effective cost per interaction in the 35 range. That is materially below human-assisted support and includes 24/7 availability without staffing constraints.
Jio Haptik WhatsApp, voice features, and 22-language support
The agents run on WhatsApp and voice, replacing rigid IVR flows with context-aware, goal-seeking conversations. They can qualify leads, book appointments, resolve routine queries, trigger follow-ups, and integrate with back-end systems for actions. Crucially, they support 22 Indian languages, which is essential for Tier-2 and Tier-3 markets where vernacular engagement directly affects conversion and trust.
Results, case studies, and reference customers
Haptik reports that early adopters are automating up to 80% of repetitive support queries and seeing a 2025% lift in lead-to-sale conversions. Live use cases include Reequil for post-purchase notifications and feedback, Pantheon Development for lead pre-qualification, and Aster Hospitals (UAE) for multilingual patient reminders. Haptik continues to serve enterprises such as Jio, Cred, Ola, PVR, Adani, Zepto, Unilever, HP, and Axis Max Life Insurance, indicating platform maturity.
Market context and timing
The launch aligns with the mainstreaming of WhatsApp Business in India, rising labor costs, and the need for round-the-clock service without expanding headcount.
Why WhatsApp-first matters for SMBs
For SMBs, WhatsApp has become the everyday sales and service channel. Making AI agents native to WhatsApp compresses onboarding time, reduces training, and meets customers where they already communicate. This is especially relevant outside metros, where language localization is often the difference between inquiry and conversion.
Moving from IVR menus to intent-driven voice AI
Voice agents that understand intent and take action are beginning to displace menu-driven IVRs. For telecom and CPaaS stakeholders, this represents a migration from call-centric to conversation-centric architectures, with lower handle times, fewer drops, and better data capture across channels.
24/7 coverage and cost efficiencies for SMBs
Indian SMBs battle tight margins and high lead leakage after hours. A per-conversation cost model with 24/7 coverage can unlock immediate savings versus human agents while maintaining responsiveness during peaks, holidays, and promotions.
Architecture and integrations
Haptiks agentic AI runs across messaging and telephony while integrating with CRM and operational systems to complete tasks, not just answer questions.
CRM, telephony, and workflow automation
The platform connects to popular CRMs and order or booking systems through APIs, enabling actions like ticket creation, inventory checks, payment links, or appointment scheduling. On WhatsApp, it leverages the WhatsApp Business Platform; for voice, it interfaces with telephony and contact center stacks to enable inbound and outbound use cases.
Security controls, compliance, and data governance
Haptik positions the agents as enterprise-grade in security and compliance. Buyers should validate controls such as encryption, role-based access, audit logs, and data residency. In India, alignment with the Digital Personal Data Protection (DPDP) Act is key, along with consent capture and minimization of personally identifiable information. For healthcare and BFSI use cases, assess certifications (for example, ISO 27001, SOC 2) and sector-specific policies, and ensure fraud prevention, authentication, and safe actioning are in place.
NLU, analytics, and model improvement
The agents use multilingual natural language understanding to maintain context across turns and languages. Automation rates typically improve over time as models learn from resolved interactions, new intents, and clarified business rules, provided feedback loops and analytics are actively managed.
ROI, metrics, and buyer checklist
SMBs can use a few simple metrics to test whether AI agents deliver predictable gains before scaling.
Cost model and success metrics
At 35 per AI-led conversation and an entry plan at 10,000, many SMBs can cut support costs by around 50% versus fully human teams while expanding coverage hours. Early deployments cite up to 80% automation on repetitive queries and 2025% uplift in lead-to-sale conversion when agents own qualification and follow-ups. Track hard metrics: cost per conversation, first-contact resolution, CSAT, lead conversion, and time-to-first-response.
Governance, escalation, and policy guardrails
Set clear boundaries for escalation to humans, especially for high-value or sensitive flows. Define tone, language, and disallowed actions. Use verification steps before transactions, sentiment detection to route unhappy customers, and periodic conversation reviews. Ensure opt-ins on WhatsApp templates and compliance with Meta’s messaging policies to avoid quality penalties.
Phased rollout and measurement plan
Start with two or three automatable journeysFAQs, appointment booking, order statusthen layer in proactive notifications, re-engagement, and payments. Integrate CRM first to keep data consistent. Test bilingually if applicable. Calibrate analytics dashboards to surface containment rates, deflection, and revenue impact in real time.
Known challenges and mitigations
AI agents can underperform without governance, high-quality data, and realistic expectations about conversational nuance.
Conversation quality and escalation strategy
Some SMBs worry about robotic interactions. Address this by authoring domain-specific knowledge, adding guardrails, and enabling quick human takeover. For regulated or high-empathy situations, use AI to triage and prepare context for agents rather than to resolve end-to-end.
Identity, fraud, and data protection
Secure identity verification, abuse detection, and template governance are critical on WhatsApp and voice. Implement OTP flows, masked PII, and rate limits. Align retention policies with DPDP and sector guidance. Monitor for social engineering risks when agents trigger actions.
Alternatives and avoiding vendor lock-in
Alternatives in India include players like Gupshup, Yellow.ai, and global CPaaS or CCaaS providers such as Twilio or MessageBird, alongside cloud AI stacks from hyperscalers. Avoid lock-in by insisting on exportable conversation data, bring-your-own-LLM options where possible, and standards-based integrations.
Jio Haptik Best-fit segments and telco/ISV plays
The model is most compelling where WhatsApp and phone are the primary sales and service touchpoints and where 24/7 responsiveness matters.
Priority industries and quick-win use cases
D2C brands, clinics, diagnostics, salons, real estate, education, and local services can realize quick wins in lead capture, appointment scheduling, order status, and loyalty re-engagement. Examples like Reequil, Pantheon Development, and Aster Hospitals show how post-purchase care, lead pre-qualification, and patient outreach can be automated without large teams.
Bundling opportunities for operators and partners
Operators and channel partners can bundle WhatsApp Business connectivity, voice, and agentic AI as a managed service for MSMEs. This pairs network reach with ready-to-use automation, creating new ARPU streams while helping SMBs scale without headcount. Watching Haptiks plan to onboard 300,000500,000 SMBs over the next two years, ecosystem players should prioritize co-selling, vertical templates, and outcome-based pricing.
