AI & Automation

From Intelligent Automation to Production ML - AI That Ships

Not just prototypes. We build AI systems that run in production, at scale, with monitoring and guardrails. ML pipelines, GenAI integration, AI agents, and computer vision - deployed with enterprise reliability.

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Trusted by

Seneca ESG Cygon InfraSignal Amatrium

Production-Grade AI

Not slide decks. AI systems with monitoring, guardrails, retraining, and SLAs.

4-Week AI Pilot

Validate any AI use case with your real data in 4-8 weeks. $15-25K fixed price.

Enterprise Security

ISO 27001 certified. SOC 2 aligned. AI with guardrails and human-in-the-loop.

Full MLOps Pipeline

Training, serving, monitoring, retraining - end-to-end ML infrastructure.

Eastgate Software's AI & Automation practice builds production-grade AI systems - not slide decks. Our engineers deploy ML pipelines, GenAI/RAG integrations, AI agents, computer vision, and intelligent document processing for enterprise clients across FinTech, ITS, manufacturing, and retail. From a 4-week AI pilot with your real data to full-scale production ML with automated retraining and monitoring, we deliver AI that works in the real world. 200+ engineers, ISO 27001 certified, with 12+ years of engineering mission-critical systems. AI-augmented development tooling built into every engagement.

200+ Engineers
500+ Projects Delivered
93% Client Retention
4-8 wk AI Pilot to Production
12+ Years Experience
ISO 27001 · ISO 9001 · IAS Accredited · SOC 2 Aligned · Clutch Top Developers

What AI & Automation Capabilities Does Eastgate Provide?

End-to-end AI engineering - from pilot to production ML at enterprise scale.

AI Agent & Agentic Workflows

Autonomous AI agents for document processing, decision support, and multi-step task execution with human-in-the-loop oversight.

LangChainCrewAIOpenAIAnthropicAutoGen

ML Pipeline & Model Deployment

End-to-end ML infrastructure: data preparation, model training, serving, monitoring, and automated retraining.

PyTorchTensorFlowMLflowKubeflowSageMaker

GenAI Integration

Embed LLMs into existing products: RAG pipelines, prompt engineering, fine-tuning, output guardrails, and cost optimization.

OpenAIAnthropicHuggingFaceLangChainPinecone

Computer Vision & Image Analysis

Object detection, OCR, quality inspection, and visual analytics for manufacturing, retail, and infrastructure monitoring.

YOLOOpenCVTesseractAWS RekognitionCustom CNNs

Intelligent Document Processing

AI-powered extraction, classification, and routing for invoices, contracts, compliance documents, and tender files.

spaCyTextractDocument AICustom NLP Models

Process Mining & Automation

Discover bottlenecks, model workflows, and automate with RPA + AI. From manual processes to intelligent automation.

CelonisUiPathPythonPower AutomateKafka
Parent Practice

Product Engineering & AI

Full-stack product development, AI integration, and our AI-augmented development methodology.

Explore Product Engineering → Sibling Practice

Enterprise Platforms

Cloud migration, ERP integration, workflow automation, and legacy modernization.

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How Does Eastgate Use AI to Accelerate Engineering Delivery?

AI isn't just what we build - it's how we build. Every engagement includes AI-augmented tooling across the full development lifecycle.

AI Code Generation

Specification-first workflows where AI agents build from precise specs - not ambiguous prompts.

AI Test Generation

LLM-assisted edge-case tests, integration suites, and data validation scenarios - increasing coverage automatically.

Automated Code Review

Security scanning, architecture compliance, and performance checks on every commit - AI-powered.

Anomaly Detection

ML-powered monitoring for production AI systems - drift detection, performance degradation, and automated alerts.

"The team built an AI-powered platform that significantly improved our product. Their expertise in ML and full-stack development was exactly what we needed for production-grade AI."
AL

Amy Loukus

Product Lead, EdTech

How Can You Engage Eastgate for AI Projects?

All models support outcome-based pricing - you pay for results, not hours.

Ongoing AI product development

Embedded AI Team

AI/ML engineers embedded in your team. Managed by EGS Team Lead. Outcome-based pricing available.

Min: 4 people, 6+ months
Defined AI/ML use case

AI Project

Fixed scope, milestone-based delivery. EGS owns PM + QA. Production-grade AI with monitoring and guardrails.

Min: $50K per SoW
Validate an AI use case

AI Pilot

4-8 week pilot with your real data. Working prototype + go/no-go decision. Fixed price.

Min: $15-25K
See our full engineering process and delivery model →

Frequently Asked Questions About AI & Automation Engineering

What is the difference between an AI pilot and a full AI project?
A Pilot ($15-25K, 4-8 weeks) validates a single AI use case with your real data - you get a working prototype and a clear go/no-go decision. A full AI Project ($50K+ per SoW) builds production-grade AI systems with monitoring, retraining pipelines, guardrails, and integration into your existing workflows.
Can you integrate AI into our existing products?
Yes. Most of our AI work is integration, not greenfield. We embed LLMs, ML models, and AI agents into existing SaaS platforms, enterprise systems, and workflows. RAG pipelines for knowledge retrieval, AI-powered search, automated document processing - all integrated with your current tech stack.
How do you ensure AI systems are reliable in production?
We build AI systems with monitoring dashboards, automated drift detection, output guardrails, and human-in-the-loop oversight where needed. Model performance is tracked continuously, and automated retraining pipelines kick in when accuracy degrades. We treat AI like any other production system - with SLAs, incident response, and observability.
What AI/ML frameworks and tools do you use?
Our core AI stack includes PyTorch, TensorFlow, LangChain, OpenAI, Anthropic, and HuggingFace for model development. For MLOps we use MLflow, Kubeflow, and AWS SageMaker. Vector databases like Pinecone and Weaviate for RAG. Computer vision with YOLO, OpenCV, and custom CNNs. We match the tooling to the use case.
Do you build custom AI models or use pre-trained ones?
Both. For many use cases - document processing, code review, content generation - fine-tuned pre-trained models (GPT-4, Claude, open-source LLMs) are the right choice. For specialized tasks like industrial quality inspection, anomaly detection, or domain-specific NLP, we train custom models on your data.
How long does it take to deploy an AI system to production?
An AI pilot runs 4-8 weeks. A production ML pipeline typically takes 8-16 weeks depending on complexity, data readiness, and integration requirements. GenAI features (RAG, chatbots, document processing) can ship faster - often 4-8 weeks to production - because they build on pre-trained foundation models.
Regional Solutions

Serving Gulf Industrial Enterprises

AI modernization and zero-downtime legacy migration for UAE, KSA, and Qatar enterprises. Start with a 4-week paid PoC.

Explore Middle East Solutions
Get Started

Ready to Put AI to Work?

Start with a 30-min discovery call. We'll identify the highest-impact AI use case for your business.

000 +

Engineers

Full-stack + AI/ML specialists

00 %

Client Retention

Partners, not vendors

0 -8 wk

AI Pilot

To production prototype