Production AI/ML systems including LLMs, RAG pipelines, computer vision, and intelligent automation.
Building ai/ml software requires navigating complex technical and regulatory requirements. Here's what we help you solve:
We've shipped production ai/ml systems that scale. Our engineers bring hands-on experience with:
From fractional CTO leadership to embedded engineering teams, we scale with your needs.
Technical leadership for ai/ml startups. Architecture, compliance, hiring, and investor storytelling.
Learn more →⚡Senior engineers with ai/ml expertise who embed in your team and ship production code.
Learn more →🤖Add AI capabilities to your ai/ml product. Copilots, automation, and intelligent features.
Learn more →“Aravind is in the top 1% of engineers I've hired. He supported us from $100K to $5M ARR, keeping us shipping through crazy growth and investor scrutiny.”
Building ai/ml software requires a unique blend of technical excellence and domain expertise. Production AI/ML systems including LLMs, RAG pipelines, computer vision, and intelligent automation. At HyperNest Labs, we bring engineers who have shipped production ai/ml systems and understand the specific challenges you face.
Generic agencies often struggle with ai/ml projects because they lack domain knowledge. They might be great React developers, but do they understand llm integration and prompt engineering? Can they navigate rag system architecture?
Our approach is different. We pair senior full-stack engineers with fractional CTO leadership who have built ai/ml products before. This means faster onboarding, fewer mistakes, and better architectural decisions from day one.
Every engagement starts with understanding your product, your users, and your technical constraints. For ai/ml specifically, we focus on:
Whether you're building a new ai/ml product from scratch or scaling an existing platform, we can help. Our typical engagement starts with a 30-minute call to understand your roadmap, followed by a scoping discussion to define the right engagement model—fractional CTO, founding engineers, or both.
Aravind has been a fractional CTO and founding engineer for 15+ startups across healthcare, fintech, sports betting, and AI. He has personally shipped production systems in ai/ml and helps founders navigate the technical challenges of scaling.
Connect on LinkedIn →We've built production systems for ai/ml companies from Seed to Series B. Our engineers have deep domain expertise in llm integration and prompt engineering and rag system architecture.
LLM application development (GPT, Claude, Llama) is core to our ai/ml practice. We bring engineers who've implemented these systems at scale and can help you avoid common pitfalls while maintaining development velocity.
Absolutely. Most of our engagements involve embedding with existing teams. We augment your capacity with senior engineers and fractional CTO leadership, transferring knowledge as we build.
We offer fractional CTO partnerships (10-25 hrs/week) for technical leadership, and founding engineer pods (1-3 engineers) for execution. Many ai/ml startups start with a fractional CTO to set technical direction, then add engineers as needed.
We can typically begin within 1-2 weeks of signing. We start with a technical discovery session to understand your stack, challenges, and roadmap before integrating with your team.
HIPAA-compliant engineering for digital health platforms, telehealth, EHR integr...
Secure, compliant engineering for payments, lending, banking, and investment pla...
Scalable multi-tenant architecture for subscription software companies from MVP ...
High-performance commerce platforms and two-sided marketplaces built for convers...
Real-time data systems and scalable platforms for gaming, sports analytics, and ...
Learning platforms, assessment systems, and educational tools that scale to mill...
Let's discuss your ai/ml engineering challenges and how we can help.