AI Engineering, Automation & Intelligent Systems

Production-grade AI systems, intelligent automation, and scalable cloud infrastructure. Built by senior engineers with deep expertise in generative AI, MLOps, and industrial IoT.

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AI Engineering & Generative AI Solutions

Design and deployment of production AI systems

Implementation of LLM-based systems (OpenAI, Claude, AWS Bedrock), RAG architectures, multi-agent systems, enterprise chatbots, and AI copilots for operations, support, and analytics.

Key Benefits

  • • Cognitive task automation
  • • Operational cost reduction
  • • Data-driven decision making

Tech Stack

AWS Bedrock, OpenAI, Claude, LangChain, LangGraph, Langfuse, PostgreSQL + pgvector

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Intelligent Process Automation (IPA)

Complex process automation with AI + business rules

Automation of operational workflows (back-office, reporting, validations), AI integration with existing systems (ERP, CRM, APIs), human-in-the-loop systems for critical processes, autonomous agents with control and traceability.

Key Benefits

  • • End-to-end workflow automation
  • • Legacy system integration
  • • Compliance and auditability

Tech Stack

Python, FastAPI, Celery, Redis, PostgreSQL, Docker

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Machine Learning & Predictive Analytics

Predictive models applied to business and industry

Predictive maintenance models, anomaly detection, time series forecasting, ML applied to IoT and industrial data, lightweight models for edge computing.

Key Benefits

  • • Failure prevention
  • • Real-time insights
  • • Edge deployment

Tech Stack

Python, PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy

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Full Stack AI Applications

AI-first digital products ready for production

Development of web platforms with integrated AI, intelligent dashboards and advanced analytics, high-performance internal systems, AI-driven SaaS products.

Key Benefits

  • • Modern UX/UI
  • • Real-time analytics
  • • Production-grade code

Tech Stack

Next.js, React, TypeScript, Tailwind, NestJS, FastAPI, Django, Node.js

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Cloud Architecture & DevOps (AWS)

Scalable and secure infrastructure for critical systems

Cloud-native architecture design, serverless (AWS Lambda) and containers (ECS, Docker), CI/CD pipelines, infrastructure as code (Terraform), observability and monitoring.

Key Benefits

  • • Auto-scaling
  • • Cost optimization
  • • 99.9% uptime

Tech Stack

AWS (Lambda, ECS, S3, RDS), Terraform, GitHub Actions, CloudWatch, Datadog

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IoT, Edge AI & Intelligent Devices

Hardware + software + AI integration

End-to-end IoT systems, edge AI for real-time processing, sensor → cloud → dashboard integration, firmware and embedded control.

Key Benefits

  • • Real-time processing
  • • Low latency
  • • Offline capability

Tech Stack

ESP32, Arduino, Raspberry Pi, MQTT, BLE, C/C++, Python

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AI Observability, Governance & Reliability

Responsible and operable AI in production

LLM observability, prompt and model evaluation, cost control and optimization, security and hallucination mitigation, audit and traceability.

Key Benefits

  • • Cost transparency
  • • Quality assurance
  • • Risk mitigation

Tech Stack

Langfuse, Weights & Biases, MLflow, Prometheus, Grafana

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AI Strategy & Technical Advisory

Strategic guidance for AI adoption

AI maturity assessment, adoption roadmaps, high-impact prototypes, architecture and cost review, technical mentoring for internal teams.

Key Benefits

  • • Clear AI roadmap
  • • Risk assessment
  • • Team enablement

Tech Stack

Strategic consulting, technical workshops, POC development

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Security, Reliability & Quality Engineering

Robust and reliable systems

API and system security, authentication and authorization, automated testing, fault-tolerant system design.

Key Benefits

  • • Secure by design
  • • High availability
  • • Quality gates

Tech Stack

OAuth2, JWT, Pytest, Playwright, Kubernetes, Load Balancers

Service Packages

Engagement models designed for rapid value delivery

AI Proof of Value

4–6 weeks

Real customer use case, functional MVP, clear impact metrics. Validate AI feasibility before full commitment.

Deliverables

  • • Technical feasibility assessment
  • • Working MVP with real data
  • • ROI projection and success metrics
  • • Production roadmap

AI Production Upgrade

6–10 weeks

Take prototypes to production with observability, security, and cost optimization.

Deliverables

  • • Production infrastructure setup
  • • Observability and monitoring
  • • Security hardening
  • • Cost optimization strategy

AI Automation Sprint

8–12 weeks

Complete automation of one business process with measurable ROI.

Deliverables

  • • End-to-end process automation
  • • Integration with existing systems
  • • Measurable ROI report
  • • Documentation and handover

Ready to transform your business with AI?

Book a 30-minute technical discovery call. No sales pitch—just an honest conversation about your challenges and how we can help.

Scale Track

Companies with product-market fit who need to scale infrastructure or rebuild legacy systems.

Typical Deliverables

  • • Performance optimization & database tuning
  • • Microservices architecture migration
  • • Real-time data pipelines
  • • Advanced integrations (payments, EHR, APIs)
  • • Security & compliance (HIPAA, SOC2)
  • • Monitoring, observability, CI/CD

Timeline & Success Metrics

Timeline: 3-6 months

  • • 10x improvement in latency/throughput
  • • Zero-downtime deployments
  • • Compliance audit readiness
  • • Reduced infrastructure costs

AI & R&D Track

Teams building ML-powered products or data-intensive platforms in sports science, health, or biomechanics.

Typical Deliverables

  • • Custom ML model development & training
  • • Computer vision & sensor data pipelines
  • • Real-time inference engines
  • • Data labeling & annotation workflows
  • • Model deployment & monitoring
  • • Explainability & compliance tooling

Timeline & Success Metrics

Timeline: 4-8 months

  • • Model accuracy targets met
  • • Real-time inference latency < target SLA
  • • System integrated into production
  • • Continuous retraining pipeline operational