{"id":1301,"date":"2026-05-05T09:23:02","date_gmt":"2026-05-05T09:23:02","guid":{"rendered":"https:\/\/srini.ee\/?post_type=case&p=1301"},"modified":"2026-05-27T08:39:02","modified_gmt":"2026-05-27T08:39:02","slug":"ai-native-customer-support-without-the-ai-startup-budget","status":"publish","type":"case","link":"https:\/\/srini.ee\/en\/case-studies\/ai-native-customer-support-without-the-ai-startup-budget\/","title":{"rendered":"AI-native customer support without the AI-startup budget"},"content":{"rendered":"
\r\n

Modena’s support team handles inbound emails in three languages and serves two distinct audiences \u2014 borrowers and investors \u2014 under licensed-financial-institution audit requirements.<\/span>\u00a0<\/span><\/h3>\n<\/div>\r\n\r\n\n\n
\r\n
\r\n \r\n
\n\r\n
\r\n
\r\n
Annual direct financial gain (5 agents)<\/dt>\r\n
27 420 \u20ac<\/dd>\r\n <\/dl>\r\n
\r\n
Time saved by AI features<\/dt>\r\n
27.5h \/ week<\/dd>\r\n <\/dl>\r\n <\/div>\n<\/div>\r\n <\/div>\r\n \r\n<\/div>\r\n\n\n
\r\n
\r\n \r\n
\n
\r\n

Challenge\u00a0<\/strong><\/p>\n

Every\u00a0customer\u00a0reply at a licensed credit institution must be auditable and\u00a0regulation-compliant. The support team was juggling three languages, two portals (modena.ee for lending and\u00a0modena.capital\u00a0for investors), and the constant pressure of fast, consistent quality across a small team.<\/span><\/p>\n

Solution\u00a0<\/strong><\/p>\n

    \n
  • 11 AI workflows, one platform.\u00a0<\/span><\/b>AI is integrated into 11 distinct support workflows rather than\u00a0bolted on\u00a0as a side chatbot; every AI output goes through human review before reaching a customer.<\/span>\u00a0<\/span><\/li>\n<\/ul>\n
      \n
    • Cost-aware three-model strategy.\u00a0<\/span><\/b>Triage runs on Haiku, reply drafting on Sonnet, complex reasoning on Opus \u2014 admins can see and override the choice per scenario.<\/span>\u00a0<\/span><\/li>\n<\/ul>\n
        \n
      • RAG on the Zendesk archive.\u00a0<\/span><\/b>Every new ticket surfaces the three most similar resolved tickets as context, so the AI learns from how humans\u00a0actually handled\u00a0the same question.<\/span>\u00a0<\/span><\/li>\n<\/ul>\n
          \n
        • Portal-aware knowledge base.\u00a0<\/span><\/b>Every KB article is tagged with a portal \u2014 investor tickets never see lending FAQs and vice versa.<\/span>\u00a0<\/span><\/li>\n<\/ul>\n
            \n
          • Self-extending KB.\u00a0<\/span><\/b>Every Sunday, Claude reviews\u00a0resolved\u00a0tickets and drafts the three most-recurring FAQs; admins click ‘publish’ after review.<\/span>\u00a0<\/span><\/li>\n<\/ul>\n
              \n
            • Graceful degradation.\u00a0<\/span><\/b>If the Claude API is down, the platform keeps running \u2014 AI is an enhancement, never a critical path.<\/span>\u00a0<\/span><\/li>\n<\/ul>\n<\/div>\r\n\r\n\n<\/div>\r\n <\/div>\r\n \r\n<\/div>\r\n\n\n\n
              \n
              \n\t
                \n\t\t\t\t\t\t\t\t
              • \n\t\t\t\t\n\t\t\t\t\tAI<\/span>\n\t\t\t\t<\/span>\n\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
              • \n\t\t\t\t\n\t\t\t\t\tBackend<\/span>\n\t\t\t\t<\/span>\n\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
              • \n\t\t\t\t\n\t\t\t\t\tPHP<\/span>\n\t\t\t\t<\/span>\n\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
              • \n\t\t\t\t\n\t\t\t\t\tSelf-Service<\/span>\n\t\t\t\t<\/span>\n\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
              • \n\t\t\t\t\n\t\t\t\t\tUX<\/span>\n\t\t\t\t<\/span>\n\t\t\t<\/li>\n\t\t\t<\/ul>\n\t<\/div>\n<\/div>\n\n\n\n
                \"\"<\/figure>\n\n\n
                \r\n

                Result\u00a0<\/strong><\/p>\n

                  \n
                • Response time dropped from 5\u201310 minutes to 1\u20132 minutes per reply.<\/span>\u00a0<\/span><\/li>\n<\/ul>\n
                    \n
                  • Escalations now reach the right\u00a0person\u00a0the same day, not from the back of the queue.<\/span>\u00a0<\/span><\/li>\n<\/ul>\n
                      \n
                    • Reply quality is more consistent across agents \u2014 same KB, same prior resolutions.<\/span>\u00a0<\/span><\/li>\n<\/ul>\n
                        \n
                      • New hires use the platform on day one \u2014 no ‘prompt engineering’ training needed.<\/span>\u00a0<\/span><\/li>\n<\/ul>\n
                          \n
                        • Direct software savings of ~7 140\u20ac\/year versus Zendesk Suite + Advanced AI.<\/span>\u00a0<\/span><\/li>\n<\/ul>\n

                          Key takeaway\u00a0<\/strong><\/p>\n

                          An AI-native support operation\u00a0doesn’t\u00a0need an AI-startup budget \u2014 it needs careful workflow integration, a cost-conscious model strategy, and humans in the loop on every decision.<\/span>\u00a0<\/span><\/p>\n<\/div>\r\n\r\n\n\n","protected":false},"excerpt":{"rendered":"","protected":false},"featured_media":1261,"template":"","case_category":[9,33,37,32,15],"industry":[14],"class_list":["post-1301","case","type-case","status-publish","has-post-thumbnail","hentry","case_category-ai","case_category-backend","case_category-php","case_category-self-service","case_category-ux","industry-fintech"],"acf":[],"yoast_head":"\nAI-native customer support without the AI-startup budget \u2013 SRINI Case Study<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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