Case Studies

The Challenge

The sales team was overwhelmed with 800+ inbound leads per month. SDRs spent most of their time on unqualified leads, manually researching companies on LinkedIn, checking CRM history, and writing personalized follow-ups. By the time they reached qualified prospects, competitors had already responded.

What We Built

• An autonomous lead qualification agent that enriches inbound leads with company data, funding stage, tech stack, and intent signals
• Automated lead scoring using a custom rubric aligned with the client's ICP (Ideal Customer Profile)
• Personalized outreach drafts generated for high-scoring leads, ready for SDR review and send
• CRM integration (HubSpot): qualified leads auto-tagged and routed to the right SDR with full context
• Slack notifications for hot leads so the team can respond within minutes

Results (After 60 Days)

Client Impact

The client reassigned 2 SDRs from lead research to closing, saving approximately $8,000/month in operational costs. The agent now processes every inbound lead within 2 minutes, 24/7, and the sales pipeline conversion rate improved by 40% in the first quarter.

The Challenge

Each loan application required extracting data from 8-12 documents (ID proofs, bank statements, salary slips, property papers), cross-verifying information across documents, and flagging discrepancies. The manual process took 45 minutes per application and was prone to human error, leading to compliance risks and processing delays.

What We Built

• A multi-agent document processing pipeline: one agent per document type, orchestrated by a coordinator agent
• OCR + LLM extraction that handles scanned documents, handwritten forms, and multi-language inputs
• Automated cross-verification: the agent checks name, address, and income consistency across all documents and flags mismatches
• Structured output with confidence scores, so operations staff only review flagged items instead of entire applications
• Audit trail with full traceability for every extraction and decision, meeting regulatory requirements

Results (After 90 Days)

Client Impact

The firm reduced their document processing team from 6 to 2, reassigning 4 staff to higher-value client advisory roles. Application processing time dropped from 45 minutes to under 12 minutes. Error rates on data extraction fell by 90%, significantly reducing compliance flags and rework cycles.

The Challenge

The support team was drowning in repetitive tickets. Agents spent most of their day answering the same questions: "Where is my order?", "How do I return this?", "When will I get my refund?". Meanwhile, complex issues (damaged goods, payment disputes, escalations) waited in queue. Customer satisfaction was dropping and hiring more agents wasn't sustainable.

What We Built

• An AI support agent integrated with Zendesk that handles Tier-1 queries autonomously, including order tracking, return initiation, refund status, and FAQs
• Real-time order lookup by connecting to the client's OMS (Order Management System) and shipping APIs
• Smart escalation: the agent detects sentiment, urgency, and complexity, routing difficult cases to human agents with full context attached
• RAG-powered knowledge base: the agent pulls answers from the company's help center, policies, and past resolutions
• Continuous learning loop: unresolved queries are flagged for review and fed back to improve the agent weekly

Results (After 90 Days)

Client Impact

The company reduced their support team from 10 to 6 agents without any drop in customer satisfaction. In fact, CSAT scores improved by 15% due to faster response times. The remaining human agents now focus exclusively on complex issues and VIP customers, leading to higher resolution quality and better retention.