WELCOME TO HYPER AI SOLUTIONS

Build Your AI Product Without the 90-Day Hiring Cycle

Dedicated AI/ML engineering teams for US startups. Embedded in your workflow, your tools, and your culture. Ready in 2 weeks.

US-Registered Company
4-6 Hour Timezone Overlap
You Own The Code
See Pricing
✦
Trusted Partner Dedicated AI/ML Teams
hyperai-embedded-team // slack + github
Dark mode team collaboration and AI model engineering workflow picture
100K+
Users Powered By Our Teams
75+
B2B Businesses Served
2
Weeks to Deploy
100%
Code Ownership
4-6
Hours US Timezone Overlap
FINTECH BIZPOP
AI SAAS BIZFRONTER
HEALTH AI MEDFLOW
LOGISTICS DATACORE
THE PROBLEM

Hiring One ML Engineer in the US Takes 90+ Days

By the time you post the job, interview candidates, negotiate offers, and wait for notice periods, your competitor has already shipped their AI feature.

Evaluation Metric US In-House Hiring HyperAI Embedded Team
Time to start ✗ 90-120 days ✓ 2 weeks
First-year cost ✗ $300,000+ ✓ $15,000 - $45,000/month
Time to productive ✗ 5 months ✓ Week 2
Risk ✗ High (bad hire = 6 months lost) ✓ Low (replace in 2 weeks)
Code ownership ✓ Yours ✓ Yours (from Day 1)
Time to Start
US Hiring: 90-120 days
HyperAI Team: 2 weeks
First-Year Cost
US Hiring: $300,000+
HyperAI Team: $15,000 - $45,000/mo
TRUST & SECURITY

Your IP Is Protected From Day One

We know trust is everything when hiring an offshore team. Here's how we protect your intellectual property, data, and competitive advantage.

🔒

NDA-First Engagement

Signed NDA before any code is written. All engineers sign individual IP assignment and confidentiality agreements under US legal frameworks.

🐙

Your Repo, Your Code

Code lives in YOUR GitHub repository from Day 1. You own 100% of the IP, models, and data pipelines. No proprietary frameworks. No lock-in.

🛡️

Data Security

No access to your production data without explicit permission. Encrypted communication. Role-based access control. SOC 2-aligned security practices.

📋

Clean Handoff Guarantee

When you're ready to bring work in-house, we provide full documentation, knowledge transfer sessions, and clean repo access transfer.

Have specific security requirements? Contact Our Security Team

OUR SERVICES

Three Ways to Build Your AI Team

Start with a free audit, ship an MVP in 10 weeks, or embed a dedicated team.

AI Readiness Audit

For Series A+ Startups

FREE
  • 60-minute strategy call
  • Technical feasibility assessment
  • Data readiness review
  • 90-day implementation roadmap
  • Recommended team composition
  • No-obligation proposal within 48 hours
Learn More & Book
MOST POPULAR

AI MVP Sprint

Fixed Fee | 8-12 Weeks

$25,000 - $50,000
  • 2 Senior ML Engineers + 1 Technical PM
  • End-to-end MVP (data pipeline, model, API, UI)
  • Weekly sprint demos
  • Cloud deployment (AWS/GCP/Azure)
  • Code in your repo from Day 1
  • Full documentation + handover
  • 30-day post-launch support
Start Your Sprint

Embedded AI Team

3-Month Minimum

$10,000 - $50,000 / month
  • Dedicated ML engineers (1-4 depending on tier)
  • Your Slack, your Jira, your GitHub
  • Daily standups in your timezone
  • Weekly business reviews
  • Code ownership transfers to you
  • Replace any engineer within 2 weeks
  • Scale up or down monthly
Pilot: $10,000/mo (1 Engineer)
Sprint: $25,000/mo (2 Engineers + PM)
Scale: $40,000/mo (4 Engineers + Lead + PM)
View Team Options
🛡️

30-Day Pilot Guarantee

Start with one engineer for 30 days. If you're not satisfied with the output, communication, or code quality, you don't pay for Month 1. No questions asked.

No long-term contracts Cancel anytime after the first month.
Replace any engineer Not a fit? New engineer within 2 weeks.
Full code handoff You own everything from Day 1.
ROI CALCULATOR

See Your Exact Savings

Compare the true cost and timeline of US in-house hiring vs. a HyperAI embedded team.

How many ML engineers do you need? 2 engineers
Average US ML engineer salary $180,000
Time to hire locally (months) 4 months
US In-House Hiring
$528,000
Total first-year cost
Time to productive team: 4 months
Risk level: High — bad hire = 6 months lost
Includes salary, benefits, overhead, and recruiter fees
HyperAI Embedded Team
$300,000
Total first-year cost
Time to productive team: 2 weeks
Risk level: Low — replace in 2 weeks, no recruiter fees
Fixed monthly fee. No hidden costs.
Save $228,000 in Year One
Productive 4 months sooner
Based on average US ML engineer total compensation of $225K-$333K including benefits, overhead, and recruiter fees. HyperAI pricing includes all engineer costs with no additional fees.

Ready to start saving? Book a free strategy call.

HOW IT WORKS

From Roadmap to Production in 4 Steps

No long procurement cycles. No hiring committees. Just a team that ships.

01
📅

Book Your AI Audit

30-minute call where we map your AI use case, assess data readiness, and recommend team composition.

Week 0
02
👥

We Assemble Your Team

We match ML engineers to your tech stack and culture. You interview them. We onboard them to your tools.

Week 1
03
💻

Embedded Execution

Your team joins your daily standups, Slack channels, and code reviews. They ship code to your repo from Day 1.

Week 2
04
📈

Scale or Hand Off

Add engineers as you grow, pivot focus as priorities change, or bring everything in-house with clean knowledge transfer.

Ongoing
WHY HYPERAI

The Smarter Way to Build Your AI Team

See how embedding a dedicated AI team compares to the alternatives.

Metric Freelancers In-House Hiring Big Agency HyperAI
Speed to Start 1-2 weeks 90-120 days 30-60 days 2 weeks
Cost Predictability Hourly, variable $300K+ with overhead Project-based, scope creep Fixed monthly fee
AI Specialization Generalist Perfect (if you find one) Generalist devs AI/ML only ✓
Code Ownership Vague Yours Often theirs Yours from Day 1 ✓
Timezone Overlap Inconsistent Perfect Minimal 4-6 hours guaranteed ✓
See Our Pricing
CASE STUDIES

Real AI Products Built By Our Embedded Teams

We don't just write code. We embed into your team and ship products that scale.

Bizpop AI Fintech recommendation platform UI dashboard
FINTECH

How Our Embedded ML Team Built an AI Fintech Platform for 100K Users

100,000
Active Users
0 -> 1
Product Build
AI Engine
Recommendation System
Challenge: Startup needed AI-driven credit recommendations and automated support but had zero ML talent in-house.
Solution: We embedded 2 ML engineers + 1 PM who built the AI recommendation engine, BizBot AI support, and personalized loan matching system.
Results: Platform scaled to 100,000 users with iOS and Android apps. Client raised next funding round within 6 months of launch.
Python TensorFlow AWS React Native
Read Full Story →
B2B SAAS / AI AUTOMATION

How Our Embedded AI Team Deployed 5 AI Agent Types for 75+ B2B Clients

Note: We embedded our AI engineering team into Bizfronter's product division to build their multi-agent platform.
75+
B2B Businesses
5
AI Agent Types
82+
Projects Delivered
Challenge: Needed to build and deploy multiple AI agents (support, lead qualification, scheduling, cold calling, marketing) at scale.
Solution: We embedded 3 AI engineers + 1 Architect who built a multi-agent AI system handling 5 business functions simultaneously.
Results: 75+ B2B businesses onboarded. Platform handles customer support, lead qualification, appointment scheduling, cold calling, and marketing automation.
Python LLM APIs Workflow Automation Cloud Infrastructure
Read Full Story →
Bizfronter B2B SaaS multi-agent AI workflow dashboard screenshot
OUR EXPERTISE

We Build With Your Stack

Our engineers are fluent in the tools and frameworks your team already uses.

ML / AI
TensorFlow PyTorch Scikit-learn Hugging Face OpenAI API LangChain LlamaIndex spaCy
Data & Backend
Python SQL PostgreSQL MongoDB Redis Apache Kafka FastAPI Django Node.js
Cloud & MLOps
AWS SageMaker GCP Vertex AI Azure ML Docker Kubernetes MLflow Kubeflow CI/CD Terraform
Integration
REST APIs GraphQL gRPC WebSockets OAuth JWT
Frontend
React Next.js React Native TypeScript Tailwind CSS

Don't see your stack? We adapt. Our engineers ramp on new tools in 48 hours.

FAQ

Questions? We've Got Answers.

You do. 100%. From Day 1. We work in your GitHub repo, commit to your branch structure, and follow your coding standards. When the engagement ends, we transfer all access.

We replace them within 2 weeks at no cost. No questions asked.

We guarantee 4-6 hours of US timezone overlap every day. Daily standups at your preferred time. Async handoffs via Slack.

We're not a marketplace. We're your dedicated team. The same engineers work with you every day, embedded in your workflow and tools.

Yes. The Pilot tier is exactly that — one senior ML engineer for 30 days. If it's a fit, we scale.

3 months for Sprint and Scale tiers. 30 days for Pilot.

Yes. HyperAI is a US-registered company with a US business address.

Yes. Slack, Jira, GitHub, Notion, Asana, Linear — whatever your team uses, we use.

Ready to Ship AI Features This Quarter?

Book a free 30-minute AI Strategy Call. Walk away with a 90-day roadmap — even if you don't hire us.

Submit Direct Inquiry Form
Or email us: info@hyperaisolution.com