Silicon Prime · Outsourcing
Enterprise AI Development: Strategy, Build, and Operational Support
From strategy to production — the full AI capability, under one accountable lead.
A Stanford-rooted Responsible AI lab that scopes, builds, and supports enterprise AI. Most AI projects stall before production — GARTNER ↗ puts the abandonment rate at 30% after proof of concept. Find where you are — strategy, build, infrastructure, or staffing — every engagement runs on our patent-pending Aegis AI methodology — Silicon Prime's own proprietary contribution, drawing on our published research at Research & Insight: fixed-scope, shipped in your own cloud, with one lead who answers for it. Led by founder Kelvin Tran (Stanford-rooted; 12+ years building and shipping production AI systems for the enterprise) and co-founder Suhail Abidi (Stanford GSB).
One capability, four ways in
The same lead answers for it however you start.
One capability, four ways in — and the same lead answers for it however you start. As of June 2026 · reviewed quarterly.
AI services
Sixteen ways we put Responsible AI into production for the enterprise — the same discipline behind our four-plus years shipping to production for BJ's Restaurants across 200+ locations, twice weekly, with zero critical defects.
Conversational AI →
Chat and voice assistants grounded in your data, wired to your systems, and built to hand off to a human.
Agentic AI →
Autonomous, multi-step agents with governed tool use, staged autonomy, and human approval gates.
AI Automation →
Runs document, approval, and data-entry workflows end to end, with humans on the exceptions.
Enterprise AI →
Systems built to integrate with legacy stacks, govern at scale, and survive a multi-team rollout.
Machine Learning →
Custom predictive models — forecasting, fraud, classification, recommendation, vision — trained on your data.
AI Infrastructure & MLOps →
The operational layer that keeps your models alive in production — deploy, monitor, detect drift.
Data Analytics & Engineering →
One trustworthy, owned data layer — pipelines, warehouse, quality, and BI — built in your own cloud.
Natural Language Processing →
NLP that reads the text your business generates and makes it usable — validated against your domain.
LLM Development →
Copilots, RAG, and AI agents built on OpenAI, Claude, and Gemini — deployed in your own cloud.
AI Center of Excellence →
A CoE your team runs, not one you rent: we design it, stand it up, operate alongside you, then hand it over.
Physical AI →
The software intelligence layer for physical AI: agent planning over machine fleets, telemetry, oversight.
AI Development →
Custom AI and ML scoped, built, evaluated, and shipped to production in your own cloud — fixed scope.
Generative AI →
Generative AI that produces the output your business runs on — documents, content, code, and images.
AI Consulting →
A prioritized, ROI-backed AI roadmap you can actually fund — where AI pays, what to build versus buy.
AI Staff Augmentation →
Vetted senior AI and ML engineers embedded in your team in 1–2 weeks — productive from the first sprint.
AI Readiness Assessment →
A fixed-scope diagnostic that grades your data, use cases, tech, team, governance and ROI.
Staff augmentation vs. outcome-based delivery
There are two honest ways to buy outsourced AI work, and they suit different situations. We'll tell you which one your problem actually calls for — and we do both.
You own the plan; we supply the hands.
Vetted senior AI and ML engineers embed in your team and take direction from your leads. You keep the roadmap, the estimates, and the day-to-day priorities; we add capacity and specialist skills.
Pick this when your requirements are clear, you have a technical lead to steer the work, and the constraint is bandwidth or a missing skill — not direction.
We own the outcome; one lead answers for it.
A fixed-scope engagement with one accountable lead who scopes, builds, and ships to production in your own cloud. We carry the estimate and the risk, and you buy a result rather than hours.
Pick this when the goal is defined but the path isn't, you don't have the internal bandwidth to manage the build, and you want one throat to choke for reaching production.
Thirty minutes · No pitch deck
Not sure which AI service you need?
Bring the problem. We'll tell you honestly what fits — strategy, a build, or a team — and what it takes to reach production.