AI Team Augmentation

Embed AI/ML specialists directly into your engineering team. We provide experienced engineers who work within your processes, tools, and communication cadence to deliver AI capabilities or capacity when you need them.

Available Roles & Expertise

Computer Vision Engineers

Specialists in medical imaging, biometric verification, visual inspection, and image classification. Experience with CNNs, vision transformers, hybrid architectures, and production deployment including 40,000+ face liveness verifications.

Deep Learning Specialists

Engineers with published research (Frontiers in Neuroscience) and production experience. Capable of neural architecture design, training optimization, model calibration, and federated learning implementation.

LLM Integration Engineers

Specialists in fine-tuning (LoRA/QLoRA), RAG systems, prompt engineering, evaluation frameworks, and production deployment of language models. Research experience with Llama, Mistral, and multi-agent systems.

ML Infrastructure Engineers

Build training pipelines, monitoring systems, model serving infrastructure, and MLOps workflows. Experience with distributed training, model versioning, and production deployment on cloud platforms.

AI Research Engineers

Bridge academic research and production systems. Capable of literature review, experimental design, ablation studies, paper reproduction, and translating research findings into implementable solutions.

Full-Stack AI Engineers

Handle end-to-end AI product development including frontend integration, backend APIs, model serving, database design, and user experience for AI features. Background in React Native and web platforms.

How Augmentation Works

01 / Integrate into Your Workflow

Our engineers join your sprint planning, daily standups, code reviews, and team communication channels. They work inside your existing tools (GitHub, Jira, Slack) and follow your development processes.

02 / Maintain Technical Context

Senior technical oversight remains available for architecture decisions, risk assessment, and knowledge transfer. The delivery conversation stays close to the work without account management layers.

03 / Scale Flexibly

Add engineers when starting new AI initiatives, scale down after deployment, or maintain ongoing capacity. Engagements adapt to project phases and changing requirements without rigid contracts.

Track Record

  • Published AI/ML research in Frontiers in Neuroscience (2026)
  • Production face liveness detection: 40,000+ verifications for government program
  • Medical image classification: 99.55% accuracy with calibration analysis
  • HEC-funded LoRA and multi-agent LLM research
  • Cross-platform mobile development (React Native) with backend integration
  • International delivery experience: US, UK, GCC, South Asia, Europe

Frequently Asked Questions

What roles can Kortex8Labs provide for team augmentation?
We provide AI/ML engineers, computer vision specialists, deep learning researchers, LLM integration engineers, and ML infrastructure specialists who work directly within your existing team structure.
How does AI team augmentation work?
Our specialists join your backlog, sprint planning, code reviews, and team communication. They work inside your development processes rather than creating a separate delivery system. Senior technical oversight remains available.
What is the typical engagement duration?
Engagements are flexible. We support short-term capability gaps (3-6 months) and ongoing capacity needs. Teams can scale up or down based on project phases and changing requirements.
What time zones does Kortex8Labs support?
Based in Pakistan (GMT+5), we provide overlap with US Eastern/Pacific time zones, strong alignment with UK working hours, and same-region coverage for GCC clients in Saudi Arabia, UAE, and Qatar.
How quickly can engineers start?
After initial scoping (understanding your tech stack, processes, and current challenges), engineers can typically begin within 1-2 weeks. We prioritize finding the right capability match over rapid placement.

Discuss Your Team Needs

Describe your current team structure, the capability or capacity gap, and your AI roadmap. We'll assess fit and propose a team augmentation approach.

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