What happened
Chief Product Officer Amarinder S Dhaliwal told Reuters that IndiaMART plans to double its spending on artificial intelligence tools every six months as part of stepped-up efforts to curb fake listings and improve content checks. Reuters reports that IndiaMART is using AI to identify proxy accounts through pattern matching across seller profiles and has introduced real-time voice-to-text tools to speed processing of buyer requests, functions previously handled by call centre employees. According to Reuters, the company is developing some AI tools in-house and is also working with external AI firms, though it did not name partners. Reuters records the company's technology and content expenses in fiscal 2026 at about 2.26 billion rupees. Per Reuters, IndiaMART matches around 600 buyers with suppliers every minute, draws roughly 90 million visitors a month, and has about 220,000 sellers; Dhaliwal said the company aims to eventually host 1 million sellers.
Technical details
Reporting by Reuters describes the platform-level approaches IndiaMART is deploying: pattern-matching across seller profiles to detect proxy or linked accounts, and automated voice-to-text conversion to process inbound buyer requests in real time. Reuters frames these moves as shifting tasks that had been handled by call centre staff into AI-driven pipelines. The company did not disclose specific vendor names or detailed technical architectures in the Reuters piece.
Editorial analysis
Marketplaces of comparable scale increasingly combine behavioural pattern analysis and automated transcription to reduce manual moderation load and accelerate buyer-seller matching. These techniques can scale detection of linked accounts and repetitive fraud signals, but industry practitioners note they also raise trade-offs around false positives, appeal workflows, and the need for human-in-the-loop review for high-risk categories.
Context and significance
Reporting flags that IndiaMART was included in the U.S. Trade Representative's 2022 "Notorious Markets" list for counterfeit goods, a reputational pressure point that contextualises investment in content controls. For platforms with high transaction volume and large seller pools, improvements in automated detection and request handling materially change operational cost profiles and buyer experience metrics, even if specifics of model selection, thresholds, and vendor integration determine outcomes.
What to watch / For practitioners
Watch for concrete signals of effectiveness: industry disclosure of false-positive rates, appeal or remediation timelines, vendor names or open-source components, and measurements linking moderation changes to buyer conversion or fraud incidence. Observers should also track how platform moderation policies are updated alongside AI deployments, since policy and model tuning interact closely in live moderation systems.
Scoring Rationale #
IndiaMART's plan to double AI spending every six months is a concrete operational signal from one of India's largest B2B marketplaces, with specifics on pattern-matching for fake account detection and voice-to-text automation. Relevance is primarily for practitioners working on marketplace trust and AI-driven content moderation at scale; the story is niche outside the South Asia e-commerce context and relies on company-stated forward plans rather than audited outcomes.
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