Agentic AI for Martech Operations
Turns data into actions: alerts, recommendations, and automated execution.
Moved from static dashboards and manual querying to AI agents that monitor signals, reason across systems, and trigger actions with human oversight.
Agentic AI reduced time-to-answer, increased adoption among non-technical users, and laid the foundation for scalable, action-driven AI across GTM workflows.
Agentic AI
Autonomous Systems with Human-in-the-Loop
Turn system
THE CHALLENGE (TILES)Siloed
Tools & Data
Multiple SaaS systems (CRM, marketing automation, sales enablement) and enterprise data repositories created fragmented decision-making.
Static
Dashboards
Pre-built reports were rigid, slow, and often outdated—limiting real-time action.
Low
Adoption
Non-technical users struggled with complex tools; leaders wanted a conversational, ChatGPT-like experience grounded in enterprise context.
Business Impact
40% ↓
Query response time vs legacy dashboards
65% Adoption
Of eligible users within 3 weeks of launch
Executive Buy-In
Approval secured for Phase 2 expansion
Enterprise-Grade Trust
Enterprise-Grade Trust
Execution Timeline
-
8 weeks (2 months) from architecture design to production deployment.
Team Structure
-
AI Architect · MLOps Engineer · 3 Senior Engineers · QA/Test Specialist
(6-person squad delivering end-to-end functionality)
Conversational Agent Interface
Built a chat-based interface where users ask questions in natural language and receive context-aware answers across systems.
MCP-Based Orchestration
Implemented a Model Context Protocol (MCP) layer to securely orchestrate multiple SaaS APIs and client-owned data sources.
Reasoning & Action Layer
Used an LLM reasoning engine to route queries, synthesize insights, recommend next steps, and trigger workflows when approved.
Guardrails & Human Oversight
Applied PII tagging, guardrail prompts, and human-in-the-loop validation for critical actions—ensuring trust and compliance.
