AI systems

Systems that run.

Agents, automations, internal tools and decision-support systems — scoped, built and deployed with a human checkpoint where it matters.

Discuss an AI system

What gets built

Multi-agent research system

An orchestrated set of agents that research, synthesize and draft with source tracking.

Problem: Teams lose days to manual research that is never reusable.
System: LLM orchestration · RAG · vector store · scheduled runs
Built for: Founders, strategy and research teams
Result: Repeatable research output with a reviewable human checkpoint.

Workflow automation layer

Event-driven automations connecting the tools a team already uses.

Problem: Coordination work quietly consumes the highest-paid hours.
System: n8n / Make · APIs · webhooks · queues
Built for: Operations and delivery teams
Result: Manual handoffs replaced by monitored automated paths.

AI assessment & placement tooling

Systems that evaluate, score and route candidate or student capability.

Problem: Assessment at scale is slow and inconsistent.
System: Structured LLM evaluation · rubrics · dashboards
Built for: Institutions and placement teams
Result: Faster feedback loops with human review retained.

Startup MVPs

Deployed product surfaces built to test demand quickly.

Problem: Founders need something real before they can learn anything.
System: Modern web stack · APIs · AI-assisted build
Built for: Early-stage founders
Result: MVPs shipped in weeks, then validated with real users.

Working stack

ChatGPT
Claude
Gemini
Perplexity
n8n
Make
Cursor
Codex
Vercel
APIs
Vector databases
RAG systems

13 / Open channel

Let's build what's next.

Building AI-ready people, institutions and organizations for the AI-native economy. Tell me the audience, the timeline and the outcome you need — I'll reply with a concrete shape for the engagement.

Invite Maaz to speak Start an institutional program Build an AI system

Email: maazaivalytics@gmail.com
LinkedIn: Connect with Maaz
Based in: Bengaluru, India