At Profisea, we help engineering and product teams design, build, and operate cloud-native AI and GenAI solutions – from architecture and infrastructure to implementation, observability, security, and cost optimization.
We support:
Profisea helps companies design, build and operate cloud-native AI and GenAI solutions, from early discovery and architecture to production-ready infrastructure, integrations, governance and optimization.
We combine deep cloud, DevOps and platform engineering expertise with hands-on GenAI implementation across AWS, Google Cloud and Azure.
We help teams define the right AI use cases, technical architecture, cloud services, feasibility, cost expectations and implementation roadmap.
We integrate applications with leading model providers and cloud-native AI services, including Amazon Bedrock, SageMaker, Azure OpenAI, Google Vertex AI, Gemini, Claude and other LLM providers.
We design retrieval-augmented generation flows using internal company data, vector search, OpenSearch or vector databases, S3-based document storage, metadata layers and application-level orchestration.
We build controlled agentic workflows where LLMs can interact with approved tools, APIs, internal systems and MCP-style gateways, with governance, permissions, logging and auditability.
We build the cloud foundation required for AI workloads across AWS, GCP and Azure, including Kubernetes, EKS/GKE, SageMaker and Bedrock environments, model deployment patterns, endpoint integration, networking, IAM, Terraform, CI/CD, monitoring, logging and cost controls.
We help AI systems become reliable, observable and secure with token and cost tracking, guardrails, access control, prompt/request tracing, audit logging, secure deployment patterns and production hardening.
Many teams already have an AI idea, assistant, internal tool or PoC.
The challenge is making it work safely in production.
Profisea helps bridge that gap by supporting:
Use Case Discovery and Technical Assessment
Target Architecture
Design
Cloud Service
Selection
RAG and Agent
Architecture
Bedrock, SageMaker,
Vertex AI and Azure OpenAI integrations
Security, IAM, Guardrails and Audit Logging
Infrastructure Implementation
CI/CD and Terraform
Automation
Cost Estimation and
Optimization
PoC, MVP and Production
Hardening
GenAI assistants and AI advisor solutions
RAG systems over internal knowledge bases
Agentic automation with controlled tool access
Bedrock and SageMaker migration or modernization
MCP gateway design for internal tools and developer workflows
AI data platforms based on S3, OpenSearch, Iceberg, Glue and Trino
AI security and analytics workflows for classification, summarization and investigation support
Our strength is not only in using AI models. It is in building the cloud-native foundation that allows AI products to run securely, reliably and efficiently.
With strong expertise across cloud infrastructure, DevOps, Kubernetes, AWS, GCP, Azure, Terraform, observability and FinOps, Profisea helps companies move from AI experimentation to real production environments.
If you’re ready to succeed, we are ready to help!
Architecting a secure, production-grade Generative AI platform on AWS to power autonomous business operations.
Read Case Study
Architecting a scalable, enterprise-grade Generative AI infrastructure to power proactive, intelligence-led digital defense on AWS.
Read Case Study
Dreemz is an innovative Israeli startup that developed a unique social platform designed to help people turn their dreams into reality.
Read Case StudyBy submitting the form above, you agree that Profisea will process your personal data. To learn more, please take a moment to read our Privacy Policy. Should you have any questions or if you choose to withdraw your consent later on, please feel free to contact us at info@profisea.com.
Great! We have received your request and will contact you soon