About Plavaga
We've Seen Production AI Break. Same Pattern, Every Time.
Senior engineers who've shipped AI across three industries and run AWS infrastructure for over a decade. We diagnose what breaks after AI goes live.
Our journey
How We Got Here
From infrastructure shop to AI diagnostic practice.
Production Software
Full-stack platforms for business networking, real estate, e-commerce, ed-tech, enterprise software. Clients that stayed 5–6 years.
Deep into AWS
Cloud Architecture, DevOps, Legacy Modernization, Security. The infrastructure foundation for everything that followed.
IoT Platform & Predictive Analytics
Built an IoT PaaS with predictive maintenance analytics and event-driven data ingestion pipelines. ML in production before the LLM wave.
Health Tech Partnership
Became outsourced CTO at aarca Research — infrastructure, security architecture, and now AI tool integrations into their product roadmap.
Production AI Startup
Architected and then led as CTO. Shipped conversational commerce (hospitality), medical AI (health tech), content moderation (consumer wellness). Real users, real production incidents.
Diagnostic Practice
Launched this year. Same pattern across every industry: the model ships, the operational layer doesn’t follow. Built a practice around diagnosing that gap.
AI-native isn’t a marketing claim. It’s how we build.
Our Team
Over a decade on AWS — infrastructure, security architecture, DevOps. Certified Solutions Architect. Outsourced CTO at aarca Research since 2019, now spanning infrastructure, security, and AI tool integrations into their product roadmap. He brings both the infrastructure depth that keeps AI systems running in production and hands-on experience integrating AI into a real health tech product. When we diagnose margin bleed or security gaps, Azmi is the reason the fix actually deploys.
Shipped AI across hospitality (conversational commerce over WhatsApp), health tech (FHIR-based medical AI), and consumer wellness (AI content moderation). Some made it to production users. Some didn’t survive the startup. All taught him where AI breaks — and why. Advises QuietGrowth (fintech robo-advisory) on AI architecture in a regulated context. 20+ years across Infosys, EMC, and HP before focusing on AI implementation. When we diagnose RAG failures or monetization gaps, Rishi has usually seen the pattern before.
When projects need more hands, we scale with vetted domain specialists — AI/ML engineers, security architects, frontend developers. The diagnostic scopes the work; scaling happens at the build phase.
Client voices
From people we’ve worked with
“Plavaga understood the business requirements and made excellent suggestions for improving the customer experience.”
Christina Ravaglia
Senior Director of Product Management, Satmetrix
“Plavaga has taken the initiative of meticulously understanding what we wanted and delivered beyond par.”
Prakash Sethuraman
Managing Partner, Enterprise Blueprints
“We have been working with Plavaga for over 5 years. They displayed tremendous maturity in understanding the problem we were attempting to solve.”
Ravi Shankar
Founder Director, eMyPA
“Your experience and guidance has been the perfect match for our enthusiasm. Working with you all has been a pleasure.”
Nia
Founder, Taglr
What We Believe
Diagnose, don’t pitch.
Every call starts with your problem. We ask what’s hurting, show something relevant, and give honest feedback. Half our calls end with ‘you don’t need us for this.’
Senior engineers. No layers.
The people who diagnose are the people who build. No project managers, no handoffs, no ‘let me check with the team.’ Architecture decisions happen in the room.
AI-native, not AI-adjacent.
Cursor, Claude Code, LLM agents — in our daily workflow, not on our website for show. We understand AI in production because we build with it every day.
Start bounded, not open-ended.
Every engagement begins with a scoped diagnostic — fixed timeline, fixed cost, written deliverable. You see what we find before you decide what to build.
Technology Stack
Our experience spans AI, cloud architecture, IoT, and full-stack product development — from sensor data pipelines to LLM-powered systems.
AI & Intelligence
AI & ML
AI Billing & Metering
AI Dev Tools
Cloud & Infrastructure
AWS Compute
AWS Storage & Data
AWS Security
AWS Networking
Infrastructure as Code
Containers & Orchestration
CI/CD
Development
Languages
Frontend
Observability
Edge
Hardware/IoT
Now You Know Who Does the Work.
Tell us what you're dealing with. We'll tell you which diagnostic fits — or whether you need one at all. 30 minutes, straight feedback.