V.Trivedy_

// WORK / CASE STUDIES

Problem, solution, outcome.

Real systems, solved for innovation, built for scale.

CryptoniumX

Bient Technologies // Head of Technology

Ruby on RailsRabbitMQSidekiqRedisWebSockets
See the architecture →

THE PROBLEM

Build a crypto exchange that holds up under load without dropping trades or mismatching ledgers. Standard schemas weren't going to hold.

WHAT I BUILT

A matching engine and schemas designed from first principles, with tuned daemon jobs, deep cache optimization, and queue management; led 20+ engineers and designers.

THE OUTCOME

Reached 4,000 trades/second with a clean ledger under load, with no dropped trades and no regulatory exposure.

SiGiL

NxtCurve // Founding Technology Partner & Fractional CTO

TypeScriptNext.jsExpressMongooseMulti-LLM
See the architecture →

THE PROBLEM

Assess and grow workforce skills adaptively without LLM latency killing every request.

WHAT I BUILT

An adaptive, IRT-based assessment engine, a multi-tenant data model with secure RBAC, AI-curated learning paths, and multi-LLM integration with background generation so the front end never waits.

THE OUTCOME

A working Workforce Decision Intelligence platform moving HR from intuition to evidence, in production with enterprise multi-tenancy.

SMAD + Video Automation Pipeline

Brahma Labs (execution arm) // Director of architectural & operational oversight

FastAPIpgvectorCelery/RedisBrowser Automation
See the architecture →

THE PROBLEM

Agencies drowning in managing many social profiles, assets, and their social team.

WHAT I BUILT

A Social Media Automation Dashboard unifying profiles, assets, and team into one workflow, plus a pipeline that generates and assembles video content programmatically. Built by a team under my architectural oversight, not a fractional-CTO engagement.

THE OUTCOME

One workflow replacing scattered manual social ops and manual video editing.

Legacy / AI-MVP Rescue Op

Rescue operations // Rescue Architect

ArchitectureSecurityCI/CDMigration

THE PROBLEM

A fragile, AI-generated MVP that demoed beautifully and broke the moment real users arrived.

WHAT I BUILT

Stabilize the architecture, secure APIs and data, cut technical debt, add CI/CD, and migrate toward production.

THE OUTCOME

Faster load times, lower server costs, and a maintainable codebase a new engineer can read on day one.

Zero-to-One AI MVP

Fractional CTO // Fractional CTO

14-step buildAI pipelineDevOps

THE PROBLEM

A founder with an idea and no app, who needs to launch.

WHAT I BUILT

The 14-step build process, beta MVP in 15 days, production launch in 45 to 90, an AI pipeline, and DevOps stood up from the start.

THE OUTCOME

A launched, demoable product with a defensible architecture.

System Archive — Secondary Deployments

// I'm open to working with founders and operators across the US, UK, Europe, Australia, and India/global. This reflects markets I'm open to — not a claimed track record in each.