SaaS
Customer-Facing Analytics & API Integration Platform
Automated data pipeline with live API feeds powering client-facing intelligence layers
View case study →Service
Agentic AI & Autonomous Analytics
AI agents that query your data, surface anomalies, and deliver narrative summaries - without manual reporting workflows.
Typical timeline · 8–16 weeks
Delivery architecture
Sources
Agents
Monitoring
LLM layer
Automation
01Sources
02Agents
03Monitoring
04LLM layer
05Automation
Delivery progress
Challenges
- Reporting workflows still depend on manual analyst intervention
- AI pilots lack production monitoring and guardrails
- Anomaly detection disconnected from business context
Outcomes
- Autonomous agents monitoring critical metrics around the clock
- Narrative summaries delivered without manual report assembly
- Production-grade LLM integration with audit trails
Engagement process
01
Discovery
Map decision workflows, data sources, and KPI gaps. Align stakeholders on outcomes before architecture.
02
Architecture
Design the data platform, integration patterns, and semantic model. Validate against security and compliance requirements.
03
Build
Deliver pipelines, certified datasets, and dashboards in phased releases. Parallel-run against existing reports where needed.
04
Enable
Train business teams, document KPI ownership, and establish refresh monitoring. Transition to managed operations.
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View case study →Deliverables
Agentic monitoring pipelinesAutonomous anomaly agentsLLM guardrails & evaluationExecutive narrative automation
Led by Ayush Dubey, Principal Data Platform & AI Consultant.