Production-Grade AI Engineering: From MVP to Scalable Platform.
Turn your validated AI model into a reliable, revenue-generating application. We are your end-to-end partner for building, deploying, and scaling production-grade AI that delivers continuous value, backed by dedicated MLOps and engineering support.
Your Path to a Production-Ready AI Platform
Whether starting from a strategic plan or an existing model, we follow a robust, agile process to develop your AI application and provide continuous engineering support.
- 1
Architecting for Scale & Success
- Detailed Scope & Requirements: Solidify features, user stories, and acceptance criteria.
- System Architecture & Tech Stack: Design a scalable, cloud-native architecture and select optimal technologies.
- UX/UI Design & Prototyping: Craft intuitive interfaces and user experiences for the application.
Output: Comprehensive design docs, detailed architecture, and a clear development backlog.
- 2
Building for Reliability & Velocity
- Iterative Development Sprints: Build features (backend APIs, frontend UI, data pipelines) in agile cycles.
- ML Model Integration: Seamlessly integrate your AI models into the application workflow.
- CI/CD & Automated Testing: Implement robust MLOps pipelines for continuous integration and quality assurance.
Output: Working software increments, deployed models, and automated DevOps pipelines.
- 3
Deploying & Evolving with MLOps
- Cloud Deployment & Launch: Deploy your application to a scalable cloud environment.
- Monitoring & Observability: Proactive system monitoring, performance tuning, and model health checks.
- Continuous Improvement: Iteratively add new features and update models based on user feedback and business needs.
Output: A live, supported AI application with a clear path for continuous growth.
Your Partner for AI Operational Excellence
We combine rapid application development with robust MLOps and dedicated support to ensure your AI solutions deliver continuous, long-term value.
Speed to Market
Rapid MVP Launch
Launch your Minimum Viable Product in just 6-8 weeks to gather user feedback and validate concepts in the real world.
End-to-End Ownership
Full-Stack AI Expertise
We handle the entire lifecycle—from data pipelines and MLOps to cloud infrastructure and user-facing applications.
Continuous Evolution
Dedicated Engineering Pods
Our retainer-based Pods provide a dedicated expert team to continuously improve, scale, and support your live AI systems.
Ready to Build, Launch, or Scale Your AI Solution?
Our engineering services are designed for organizations ready to transform AI concepts into robust applications and ensure their ongoing success with expert support.
This is the Right Partnership If You:
- Have a Validated AI Concept or Model: You're ready to build a full-stack application or integrate AI into existing products.
- Need to Deploy, Monitor & Scale AI Reliably: You require MLOps expertise and robust cloud infrastructure.
- Have an Existing MVP Needing Enhancement: Your current AI solution needs expert engineering to be fully productionized.
- Seek Dedicated, Ongoing Engineering Support: You're looking for flexible “Pods” to augment your team and drive continuous improvement.
This Might Not Be Your First Stop If You:
- Are Still in the Early Idea Stage: Our AI Strategy & Roadmap is designed to validate feasibility and ROI first.
- Are Looking Purely for Off-the-Shelf Software: Our strength lies in custom development, integration, and tailoring AI solutions to your specific needs.
- Need a Simple, Standalone Model: For projects without application or MLOps needs, a Data-to-Value Sprint would be more suitable.
Prototype & Eng. Pods in Action
Rescuing & Rebuilding: From Stalled MVP to Scalable AI Platform
Many promising AI initiatives stall due to engineering gaps or misaligned talent. Our Prototype & Engineering Pods step in to provide the full-stack ML expertise needed to get projects back on track and build for the future.
Challenge:
A client had an existing MVP with potential but faced significant engineering hurdles. Their Redis service needed review, data pipelines were inefficient, and they lacked the expertise to integrate ML/LLM capabilities effectively or build a robust front-end and dashboarding system.
Our Solution & Impact:
Maximum Labs deployed an Engineering Pod that first conducted a thorough technical review and scoping exercise. We then refactored their social media data monitoring scripts to Python, designed a scalable data architecture (moving parts to relational systems), and identified key ML/LLM integration points. Our team built an entire scheduling pipeline for fetching and scoring new video content (using ML and ChatGPT), developed a new full-stack MVP (React/FastAPI), and created accompanying dashboards for actionable insights.
Key Outcome: Transformed a struggling MVP into a scalable, AI-enhanced platform with automated data pipelines and rich user-facing features, empowering the client to move forward with confidence.
What You Get
Your Production-Ready Engineering Assets
Whether an MVP Sprint or ongoing Pod support, we deliver concrete, valuable assets that form the foundation of your live, scalable AI application.
Deployed AI Application
A working MVP or full application deployed to your cloud environment, ready for user testing or a full launch.
Complete Source Code & IP
Full ownership of all custom code, configurations, and intellectual property, delivered via your private repository.
CI/CD & MLOps Pipelines
Automated pipelines for testing, deploying, and monitoring your models and application, ensuring robust and repeatable operations.
Technical Documentation
Comprehensive documentation covering system architecture, setup guides, API specifications, and operational procedures.
Monitoring & Observability
Dashboards and alerting systems to track model performance, data drift, and system health in real-time.
Dedicated Pod Support
For retainer engagements, you get a dedicated team providing proactive maintenance, continuous improvements, and expert support.
Investment Options
Engineering for Every Stage of Growth
From fixed-scope sprints to build your MVP to dedicated monthly retainers for long-term evolution, we offer clear, value-driven pricing.
Project-Based Builds
MVP Launchpad Sprint
From $35,000
A 6-8 week fixed-scope engagement.
Includes core feature development (backend & UI), ML model integration, and deployment to a staging environment.
Custom AI Application Build
Custom Quote
Typically $75,000+
A custom-scoped project for complex, production-grade applications requiring advanced MLOps, deep integrations, and polished UX.
Ongoing Support Retainers
Support & Optimization Pod
$8,000/month
Up to 40 hours/month.
Provides ongoing monitoring, maintenance, performance tuning, bug fixes, and expert advisory for your live application.
Growth & Evolution Pod
$20,000/month
Dedicated FTE resource.
A dedicated senior engineer focused on building new features, updating models, and continuously evolving your AI platform.
FAQ
Your Engineering & MLOps Questions, Answered
Have questions? Below are answers to some common questions. If you don’t see yours, use the button below to ask.
We are proficient in a wide range of modern technologies including Python for ML/AI, FastAPI & React for full-stack development, Docker & Kubernetes for containerization, and major cloud platforms (AWS, GCP). We select the best stack based on project requirements for scalability and performance.
We implement MLOps best practices from the start, including version control for data & models, automated training pipelines, CI/CD for continuous testing and deployment, and robust monitoring for model performance and system health in production.
Our Engineering Pods are engaged on a monthly retainer. We offer two tiers: a 'Support & Optimization Pod' for maintenance, and a 'Growth & Evolution Pod' for continuous development with a dedicated resource.
Yes, absolutely. We have extensive experience stepping into existing projects. We typically start with a technical audit and code review to understand the current state, then propose a plan for refactoring, enhancement, or ongoing support.
You, the client, retain 100% ownership of all custom code, models, and intellectual property developed specifically for your project. We provide all source code and documentation.
We design for scalability from day one, utilizing cloud-native architectures, containerization with Docker, and efficient data processing techniques. Clean code and comprehensive documentation contribute to long-term maintainability.
Every MVP launch includes comprehensive documentation and a knowledge transfer session. For ongoing support, maintenance, and further development, we highly recommend engaging one of our Engineering Pods.
We're flexible. Our Pods can function as a self-contained project team or integrate seamlessly with your existing engineers and tools (e.g., Slack, Jira, Git). We prioritize clear communication and collaborative workflows.
Powered by a Modern, Flexible Tech Stack
While our builds focus on your business outcome, they are delivered on a foundation of deep expertise across the AI and engineering ecosystem. We select the right tools for your specific challenge.
Ready to Bring Your AI Vision to Life & Keep It Thriving?
From rapid MVPs to production-grade platforms and dedicated ongoing support, we are your trusted partner for building and scaling successful AI-powered solutions.