Vikram Purohit
Software engineer and AI practitioner with a track record of building reliable, scalable systems, and increasingly, AI-powered products that behave in production the way they were designed to.
vprism works with companies at every stage, from early-stage startups finding product-market fit to growth-stage businesses navigating their first major AI integration. The practice builds AI assistant apps using Claude and the Vercel AI SDK, with deep Claude Code expertise, and is currently applying for the Anthropic Claude Partner Network. The common thread: smart decisions made early, on architecture, on AI strategy, on what to build, save enormous time and cost later.
The approach is direct and pragmatic. No presentation decks that gather dust. The process starts with understanding your goals, identifying the real constraints, and finding solutions your team can actually implement this week, not this quarter.
Expertise
What vprism brings
Deep hands-on experience across AI and the full technology stack. Not advisory at arm's length, but the kind of expertise that comes from having shipped production systems, built LLM-powered applications, and made the hard calls firsthand.
AI & LLM Implementation
Building AI-powered applications using Claude and the Vercel AI SDK. Agent architectures, prompt engineering, retrieval-augmented generation, and production LLM pipelines. Deep Claude Code expertise.
Technical Strategy
Roadmap planning, architecture decisions, build-vs-buy analysis, and technology selection. Including where AI fits and where it doesn't.
Engineering Leadership
Team structure, hiring, engineering culture, process design, and organizational scaling.
System Architecture
Cloud infrastructure, distributed systems, API design, data modeling, and microservices.
Product Engineering
Full-stack development, performance optimization, and shipping production-quality software.
Philosophy
How to think about technology
Most technology problems are not actually technology problems. They're prioritization problems, communication problems, or organizational problems wearing technology clothing. Recognizing that distinction is the first step to solving the right thing.
This applies to AI too. The question isn't whether to use LLMs. It's which problems they actually solve well, and how to build around their failure modes. Teams need to answer that question before committing to an architecture they can't unwind.
Complexity is worth being skeptical of. Every piece of technology added to a system is a liability as much as an asset. The best architectures are boring in exactly the right ways: reliable, maintainable, and understood by the team that has to live with them.
Momentum matters. A good decision made and shipped beats a perfect decision still in planning. The goal is always to help your team move forward with confidence, not to produce an impressive-looking strategy document.
Clients
Who vprism works with
Founders
You have a product vision and need a technical co-pilot who can help make smart decisions, including whether and how to integrate AI, without the overhead of a full-time CTO.
Engineering Leaders
You're scaling a team, dealing with technical debt, or navigating a major architecture decision, including AI adoption. You want a peer who's been there.
Product Teams
You want to ship AI features but aren't sure how to build them reliably. Architecture reviews and targeted guidance keep you on track.
Engagements
How engagements work
Every engagement starts with understanding your specific situation, not fitting you into a predetermined framework. Some clients need a focused architecture review over a few days. Others need an ongoing strategic partner for months.
Engagements are flexible by design: one-time advisory sessions, targeted project support, or ongoing partnerships structured around what actually moves the needle for you.
Let's talk about what you're building
Whether you have a specific challenge in mind or just want to explore how vprism might help, get in touch.
Start a conversation