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We Build software
faster with AI.

We leverage AI, and proven frameworks to Overcome time and budget constraints while safeguarding your intellectual property.

Design Illustration

Generative
Design

Defining feature and UX flows - 60% Faster
Concepts and prototypes - 40% Faster
Converting UI concepts to code - 50% Faster
Development Illustration

Generative
Development

Writing foundational code - 60% Faster
Code reviews - 35% Faster
Infrastructure set-up - 200% Faster
QA Illustration

Generative
QA & Testing

Bug Detection - 60% Faster
Unit Test Generations - 70% Faster
Regression Testing - 70% Faster

Traditional ways of building an MVP take 12 weeks—but our AI-powered development cuts it to just 5 weeks.

"Our approach offers resource-constrained teams a low-risk, high-value path to validate AI on a small scale before full deployment."
AI Innovation Workshop icon

AI Innovation Workshop

Our collaborative sessions help identify your startup's unique value proposition and the AI capabilities.

Technology & Model Selection icon

Technology & Model Selection

We recommend cost-effective frameworks and models that balance performance with your startup's resource constraints.

Data Preparation icon

Data Preparation

We develop strategies for acquiring, generating, or leveraging open-source datasets to build your initial AI application without extensive data infrastructure.

Prototype Development icon

Prototype Development

We rapidly create minimum viable AI products that demonstrate your core concept to potential investors and early customers while minimizing development costs.

How We Do It? Without the right team, AI tools can be a bottleneck—complex, generic, and time-consuming.

We don’t just use AI—we work with it. Our process combines the speed and automation of AI tools with the precision, creativity, and judgment of experienced professionals.

Design & Prototyping

Step 01

Design & Prototyping

Rapid Code Generation

Step 02

Rapid Code Generation

Code Review & Human Refinement

Step 03

Code Review & Human Refinement

Code Review & Human Refinement

Step 04

Quality Assurance & Automated Testing

Security Analysis & Hardening

Step 05

Security Analysis & Hardening

Stepper

AI helps visualise.
Humans bring it to life.

01
  • Concept Generation: We use tools like Lovable to spin up fast design concepts and interactive prototypes. But the real value? Our designers shape those ideas into interfaces that users actually want to use.
  • Collaborative Iteration: Clients are involved early and often. Together, we refine layouts, flows, and aesthetics until everything clicks.
  • Prototype Validation: Every design is checked not just for looks—but for usability, brand alignment, and feasibility. The AI draws it, but our team ensures it works.
Stepper

AI writes code fast. We make it production-grade.

02
  • AI-Driven Development: Tools like Cursor AI help turn clear requirements into working code in record time.
  • First Build Foundation: We produce a solid base product—fast enough to test, flexible enough to scale.
  • Documentation & Structure: Initial docs and comments are auto-generated—but reviewed, edited, and organized by our engineers for real-world use and onboarding
Stepper

AI can’t read between the lines. We can.

03
  • Expert Review: Our AI-certified engineers review every line of code. Not just for bugs—but for architecture, readability, and intent.
  • Performance Optimization: We tune code for speed, security, and scalability—things AI can’t fully understand without context.
  • Custom Logic Integration: Business logic, edge cases, and real-world exceptions get manually coded in. No generic solutions here.
Stepper

Speed without stability is useless. We ensure both.

04
  • Automated Testing Suite: We build in unit tests, integration tests, and regression testing from day one.
  • CI Pipelines: Continuous Integration runs tests with every update—keeping quality high, always.
  • Human QA: Automation helps, but real testers go deeper—validating UX flows, catching edge-case bugs, and flagging inconsistencies AI can’t see.
Stepper

AI helps detect threats. Our experts neutralise them.

05
  • Static Analysis: Tools like SonarQube identify risks like SQL injection or cross-site scripting.
  • Dynamic & Manual Testing: We go beyond scanning—simulating real-world hacks and penetration tests to test system resilience.
  • Final Review by Security Engineers: AI finds red flags. Our experts investigate and resolve them thoroughly, protecting your IP and data.

Who We Are

  • AI-powered product engineering and IT staffing partner for tech startups in the USA
  • 10+ years specializing in startup product development
  • Expert team of 150+ engineers, including certified AI specialists and Silicon Valley-vetted, A+ talent
  • Trusted by 70+ startups from preseed to Series A
  • IT staff augmentation with 100% guaranteed Silicon Valley vetted, A+ developers
  • Software engineering where AI is a core part of the solution, delivering intelligent, adaptive, and impactful user experiences.
AI Certified Engineering team →
Engineering Professional

Bay Area

Startup Challenges vs. ATeams Solutions

Challenge Bay Area Startup Landscape ATeams Solutions
Technical Leadership 68% of non-technical founders struggle to find technical partners Full-cycle development from concept to production-ready applications
Time-to-Market 7-9 months average time from concept to MVP MVP acceleration reducing time-to-market by 40%
Development Efficiency 35% of development budget wasted on rework Agile methodology with 2-week sprints and tangible deliverables
Technology Decisions Wrong tech stack choices lead to scaling issues and technical debt Technology consultation with stack selection optimized for unique needs
Engineering Resources In-house teams stretched across too many priorities Dedicated engineering teams that work as an extension of your team
Talent Acquisition 86% of startups report difficulty hiring qualified engineers Pre-vetted talent pool ready to deploy with zero recruitment overhead
Engineering Costs Average Bay Area engineer costs $175K+ annually Full-time resources at $3,200/month per engineer (~$38K annually)
Hiring Timeline 3-6 months to fill specialized roles Skill-matched resources with precise alignment to technical requirements
Team Stability 25% annual engineer turnover in competitive markets Flexible scaling with ability to adjust team size as needs evolve
Budget Constraints Early-stage startups can't compete with tech giants Scalable architecture built on foundations that grow with your business

AI Certified Engineering
Teams

Finding skilled AI experts is hard—costs are rising and there's a shortage of top technical talent. We solve this by providing immediate access to seasoned AI professionals who start delivering results from day one, saving you time and money.

Top Rated Gen AI Engineers by Startups in America
TOP AI & DATA TALENT

Access India's best minds in AI and data, all working in your local time zone.

FASTER TIME TO ROI

Our engineers master our Generative-Driven Development approach, harnessing AI to consistently produce higher-quality code in less time.

SELECTIVELY CURATED & VETTED

Only elite developers pass our rigorous vetting, ensuring you get talent your project demands.

OUR GEN AI CERTIFIED ENGINEERING TEAM

Machine Learning Engineers
Machine Learning Engineers
Data Scientists
Data Scientists
MLOps Architects
MLOps Architects
AI-Powered Engineers
AI-Powered Engineers
Databricks Experts
Databricks Experts
Machine Learning Engineers
Machine Learning Engineers
AI Strategists
AI Strategists
Data Engineers & Architects
Data Engineers & Architects
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GUARANTEE

30-DAY PERFORMANCE PROMISE

If you don’t see measurable progress in 30 days, you don’t pay — no questions asked.

Become a client

Case Study 1

(AMWI) AI-Driven Talent Acquisition Platform

Autonomous Recruitment AI Agent From Sourcing to Interviews

case study illustration 1

Executive Summary

Client:AMWI.AI (Artificial Intelligence Workforce Innovators)

Industry : HR Tech / Future of Work

Challenge : 72% of hiring managers struggle to identify qualified passive candidates; 68% face interview scheduling bottlenecks.

Solution : End-to-end AI recruiting platform with Alexa-level automation for candidate sourcing, ranking, and video interviewing.

Result : 65% reduction in time-to-hire, 40% cost savings per hire, and 92% candidate-match accuracy.

Client Profile

Founder : Abhi Verma (ex-AWS AI/ML architect)

HQ : San Francisco Bay Area

Stage : Series A startup targeting enterprise clients

AI Focus :

  • Transformer-based NLP for candidate profiling
  • Computer vision for video interview analysis
  • Predictive analytics for candidate success forecasting

Our Solution

Rapid Development
  • We built an end-to-end AI recruiting platform in just 5 weeks—far faster than traditional MVP timelines.
AI-Powered Features
  • The platform automates candidate sourcing, ranking, and video interviewing using advanced NLP, computer vision, and predictive analytics.
Efficient Engineering
  • ur experienced, vetted engineering team delivered a robust solution that integrates seamlessly with existing workflows.

Key AI Features

Passive Hunter Algorithm:
  • Scrapes 2M+ profiles weekly using ethical web crawlers
  • Achieves 38% higher relevance than legacy ATS filters [F1-score: 0.87]
Bias Mitigation Engine:
  • Demographic-neutral facial recognition (ArcFace)
  • Tone analysis using wav2vec 2.0 with fairness constraints
Autonomous Interviewer:
  • Demographic-neutral facial recognition (ArcFace)
  • Real-time follow-up question generator (GPT-4 fine-tuned on 10k HR transcripts)

Case Study 2

(JVOLVE) AI-Powered Coaching Platform for Personal & Professional Growth

Scaling Self-Discovery Through Digital Human Avatars & Behavioral AI

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Executive Summary

Client:Jvolve (Wharton VIP X-Suite Innovation Award Winner)

Industry : EdTech / Digital Coaching

Challenge : 89% of users find traditional coaching cost-prohibitive; lack of personalized, scalable self-reflection tools.

Solution : AI-driven coaching platform with digital human avatars + Qualtrics-powered behavioral analytics.

Result : 70% user retention rate, 2024 Wharton X-Suite Award for ethical AI innovation, and $1.2M in pre-seed funding.

Client Profile

Founder : Minlan D (Ex-McKinsey behavioral strategist)

Platform : Web/mobile AI coaching SaaS

Key Features :

  • Inner Voice: Free 30-min NLP-driven self-compassion module
  • Premium Modules: North Star (purpose discovery), Energy Optimization (AI time management)
  • Digital Avatars: User-generated AI clones reflecting coaching insights

AI Ethics :

  • GDPR/CCPA-compliant via Qualtrics integration

Our Solution

Rapid MVP Development
  • Delivered a fully functional MVP in just 5 weeks using our AI-powered development framework.
Expert Engineering Team
  • Provided vetted, AI-certified engineers to implement key features including.
  • Digital Human Avatars: Utilizing D-ID and Stable Diffusion for personalized avatar creation.
  • Adaptive Coaching Paths: Leveraging GPT-4 fine-tuned on coaching transcripts for dynamic, personalized content.
  • Seamless Analytics: Integrated Qualtrics-powered behavioral analytics for real-time personalization and feedback.
Predictive Fit Scoring
  • Ensured smooth mobile and web experiences with robust backend support.

Case Study 3

(FLOE) AI-Powered IoT Solution for Ice Dam Prevention

Accelerating Commercial Property Safety Through Predictive Analytics & Scalable Engineering

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Executive Summary

Client:US-Based Commercial Property Tech Startup

Challenge :  High costs ($9.5B/year in US damages) and inefficiency of traditional ice dam solutions; lack of IoT/AI expertise to build a predictive system1.

Solution : End-to-end development of an AI/IoT device management system with real-time weather integration and automated deicer deployment.

Result : 70% faster ice dam detection, 40% cost reduction vs. traditional methods, and scalable deployment across 500+ commercial properties1.

Client Profile

Stage : Seed-stage startup targeting municipal/commercial clients.

Founders : Non-technical (real estate/facility management background).

Objective :  Build a predictive IoT system to automate ice dam prevention.

AI Focus :

  • Needed AI/ML expertise for weather pattern analysis.
  • Struggled with IoT device-cloud integration.
  • Lacked DevOps engineers for 24/7 system monitoring.

Our AI/IoT Solutions

Product Engineering Services
  • AI Model Development:
    • Built predictive algorithms using historical weather/ice dam data1.
    • Automated deicer deployment triggers based on sensor inputs.
  • IoT Architecture:
    • Designed edge-to-cloud communication for 10,000+ devices.
  • Implemented AWS IoT Core for real-time device management1.
IT Staff Augmentation
  • Deployed 3 specialized engineers:
    • 1 AI/ML developer for algorithm optimization.
    • 1 IoT architect for device-cloud integration.
    • 1 DevOps engineer for CI/CD pipelines.
  • Cost Model: Saved 35% vs. US hires through hybrid onsite/offshore teams.

Case Study 4

IT staffing for HealthTech Startup

Dedicated HIPAA-compliant developers

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Client Profile

SeedRound digital therapeutics company preparing for FDA 510(k) clearance

Staffing Challenges

  • 47-day average time-to-hire for HIPAA-compliant developers
  • 62% candidate drop-off rate during technical screenings
  • $18K/month wasted on misaligned recruitment agencies

Our Staffing Approach

  • Created dedicated talent pipeline with 38 pre-vetted healthcare developers
  • Implemented three-stage technical validation
  • Algorithmic code challenges 
  • Domain-specific scenario testing (HIPAA breach simulations)
  • Live screening
  • Established attrition protection program with backup engineers

Contact
Information

-2 Level, Thejaswini Building,
Technopark, Trivandrum, Kerala
695582 

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