Support and Lead-Gen Agents for Multi-Tenant SaaS and E-commerce
Autonomous, citation-grounded customer assistants with tenant-scoped knowledge retrieval, CRM synchronization, and Stripe metered billing.

Structured architectural snapshot optimized for enterprise review and generative search synthesis.
A multi-tenant SaaS provider and connected e-commerce stores needed an AI agent to resolve customer inquiries, capture and score sales leads, and book product demos in CRM. However, off-the-shelf chatbots suffered from catastrophic flaws: they hallucinated refund policies, leaked data between competing tenant accounts, lacked access to real-time order tracking, and racked up unsustainable LLM bills with no usage metering per customer.
Tenant-Filtered Vector Indexing & Source Citation Verification; Tiered Model Routing with Prompt Caching & Token Economics
Deflection Rate: 74% • Cost Per Resolution: $0.04 • Cross-Tenant Leakage: 0 Incidents
Enterprise Production Architecture / ISO 27001 Aligned
The Business & Architectural Challenge
A multi-tenant SaaS provider and connected e-commerce stores needed an AI agent to resolve customer inquiries, capture and score sales leads, and book product demos in CRM. However, off-the-shelf chatbots suffered from catastrophic flaws: they hallucinated refund policies, leaked data between competing tenant accounts, lacked access to real-time order tracking, and racked up unsustainable LLM bills with no usage metering per customer.
Hard Technical Constraints
Key Architectural Decisions & Trade-Offs
Every major technical decision made during the engagement, with the trade-offs documented.
Tenant-Filtered Vector Indexing & Source Citation Verification
Rationale: Metadata tags filter all vector chunks by tenant ID prior to similarity search; every generated response cites specific page and policy IDs.
Trade-Off: Strict citation validator forces fallback to "I do not have enough policy information" when confidence scores drop below 0.88.
Tiered Model Routing with Prompt Caching & Token Economics
Rationale: Routes 75% of routine FAQ classifications to lightweight sub-models with cached prompts, reserving frontier reasoning for complex negotiation and technical support.
Trade-Off: Requires maintaining routing classification trees in Redis.
Implementation Phasing & Execution
Sprint 1: Tenant-Scoped Knowledge Base & Ingestion Pipeline
Phase 1Architected pgvector database with tenant-level row isolation and automatic document chunking for FAQs, manuals, and policies.
Sprint 2: CRM & E-Commerce Tool Mesh (Shopify, CRM, Stripe)
Phase 2Implemented scoped tool calling for order lookups, lead scoring, and calendar scheduling with prompt injection guardrails.
Sprint 3: Real-Time Usage Metering & Admin Analytics Cockpit
Phase 3Built token counter middleware integrating with Stripe metered subscription billing; deployed tenant analytics portal.
Verified Production Outcomes Matrix
Before vs. after comparison across every tracked benchmark — each cell represents a production measurement.
| Benchmark Metric | Before State | After SHIVAM ITCS | Tangible Business Impact |
|---|---|---|---|
| Tier-1 Ticket Deflection | 0% (All inquiries landed in human inbox) | 74% resolved with verified citations | Enabled 24/7 instant customer resolution across 14 international time zones. |
| Inquiry-to-Lead Conversion | 8.5% web visitor capture rate | 23.8% capture with instant CRM booking | Generated 340+ pre-qualified sales demos monthly with zero sales rep intervention. |
| Support Resolution Cost | $3.80 / ticket (Human offshore agent) | $0.04 / resolved inquiry (AI agent + token cost) | Cut monthly customer support operations expenditure by 91%. |
"Our merchants were blown away. The agent answers order and inventory questions with exact citations, books qualified sales leads directly into our CRM, and Stripe metering handles billing effortlessly."
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Support and Lead-Gen Agents for Multi-Tenant SaaS and E-commerce - FAQ
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