BharatPe launches AI merchant assistant and credit coach at Global Fintech Fest 2026

Built on Google Cloud’s Gemini platform, BharatPe’s new tools aim to help Indian merchants manage operations, access multilingual support, build credit awareness and run personalised advertising through My Shop My Ad.

— Source publishedWed, 9 Sept, 2026, 15:50 IST·First seen Wed, 9 Sept, 2026, 16:00 IST·Source YourStory

What happened

BharatPe launched an Agentic AI merchant assistant and Credit Coach, built on Google Cloud’s Gemini platform, to support Indian merchants with operations,

Key facts

  • Two AI tools launched
  • More than 60 live systems

Why this matters

BharatPe’s move highlights partnership or acquisition opportunities in vernacular AI, SMB credit education, merchant CRM and local advertising technology for firms seeking deeper merchant engagement.

What to watch

  • Monthly active merchant usage and repeat-query rates for the AI assistant.
  • Reduction in support contacts, onboarding time and merchant churn.
  • Conversion from credit-coach interactions to loan applications, approvals and repayment quality.
  • Ad-campaign adoption, merchant ad spend and attributable sales/payment-volume lift from My Shop My Ad.
  • Disclosure of Google Cloud/Gemini data handling, model-governance controls and any regulatory feedback.
  • Comparable AI merchant-tool launches from PhonePe, Paytm, Razorpay, Pine Labs and banks.
  • Bundle the assistant into BharatPe for Business workflows including settlements, GST-adjacent reporting, QR/payment troubleshooting and loan eligibility explanations.
  • Use consented transaction data to segment merchants for My Shop My Ad campaigns and measure whether ads lift payment volume and repeat customer visits.
  • Convert credit coaching into pre-qualification funnels for working-capital loans, with clear disclosures to avoid mis-selling risk.
  • Expand Gemini-powered support across Indian languages and voice interfaces, especially for non-metro kirana and micro-merchant cohorts.
  • Establish human review, audit trails and escalation for lending-related AI outputs before scaling personalized credit recommendations.