Pravesh Jain
I build AI-powered workflows that connect business processes, data, models, browser automation and agents — turning manual operations into connected systems that run, track and evolve through iteration.
From business problems to working systems
The business problems came first. The systems were built because they were necessary.
I started by working around GTM, growth, lead generation and operational processes. Over time, I began building the systems needed to automate that work — moving from workflow automation into AI models, browser automation, agents, data systems and deployment.
Today I design end-to-end systems where orchestration, research, enrichment, AI models, browser automation, databases and outreach infrastructure work together as one pipeline.
I'm not a traditional code-first engineer. I use AI as a technical multiplier: I understand the problem, design the system, build the workflow, debug the gaps and keep iterating until the system actually works.
The combination that matters
No single tool defines the profile — the intersection does.
One orchestrator, everything connected
n8n sits at the center. Hover any category or tool to see its connection; click a tool to jump into the full ecosystem.
Lines show orchestration relationships — how each category connects through n8n, not isolated tool usage.
Eight areas of practical capability
Each card opens to show what it means, the tools involved, how it fits into my systems, and an honest current level.
Problem-first. AI-multiplied. Iterated until it works.
AI as a technical multiplier. I'm not a traditional code-first engineer — I use AI to understand unfamiliar technologies, write and modify code, generate SQL, design API requests and troubleshoot deployments, while I own the problem, the architecture and the outcome. I learn technologies in the context of real problems, not before them.
Representative architectures I build
Interactive diagrams based on real workflow work. Click any stage to see its purpose, tools, input and output.
From manual business processes to automated systems
Every earlier phase became the foundation for the current work — the automation is grounded in having done the job manually first.
Full record
Systems, not tool lists
Representative systems built from real work. No invented metrics — each entry shows the problem, the architecture, the tools and what the work taught me.
Evidence of actual work
Real captures from the systems — n8n workflow canvases, AI qualification runs, outreach and CRM pipelines, and agent executions.
Honest labels, no inflated bars
CORE · STRONG PRACTICAL · PRACTICAL · WORKING KNOWLEDGE · DEVELOPING · EXPLORING — levels describe hands-on ability, not theory.
Developing areas are shown on purpose — they mark the active edge of the profile, not weaknesses to hide.
Every tool, its role and its relationships
Select any tool to see category, experience level, what it's used for and the systems it connects to.
A tool appearing here means practical, working exposure — not equal expertise in everything.
The profile is still evolving
Clearly separated from completed skills — presented as building / learning / exploring, never as mastered.
Let's connect
Open to conversations around AI workflows, automation, GTM systems and cross-border payments.
© Pravesh Jain
New Delhi, India